Methods and systems for enabling more efficient coating material development

Abstract

The present disclosure relates to the field of sustainable development of coating materials for the production of coated objects. In particular, the present invention relates to methods, apparatuses and computer elements for determining input material(s) used to prepare coating materials, adjusting existing coating formulation(s) and / or generating new coating material formulation(s), wherein at least one property of coating material(s) associated with such coating material formulation(s) and / or coating layer(s) prepared from such coating material(s) match at least one given property. The present invention further relates to a use of a data structure as updated according to the methods for determining input material(s) for adjusting coating material formulation(s) associated with coating material(s) and / or for generating new coating material formulation(s), wherein at least one property of coating material(s) associated with such coating material formulation(s) and / or coating layer(s) prepared from such coating material(s) match at least one given property. The present invention further relates to methods, apparatuses and computer elements, for determining property data of coating layer(s) prepared from coating material(s) on at least a part of a surface of an object by a coating process.

Description

[0001] METHODS AND SYSTEMS FOR ENABLING MORE EFFICIENT COATING MATERIAL DEVELOPMENT

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to the field of sustainable development of coating materials for the production of coated objects. In particular, the present invention relates to methods, apparatuses and computer elements for determining input material(s) used to prepare coating materials, adjusting existing coating formulation(s) and / or generating new coating material formulation(s), wherein at least one property of coating material(s) associated with such coating material formulation(s) and / or coating layer(s) prepared from such coating material(s) match at least one given property. The present invention further relates to a use of a data structure as updated according to the methods for determining input material(s) for adjusting coating material formulation(s) associated with coating material(s) and / or for generating new coating material formulation(s), wherein at least one property of coating material(s) associated with such coating material formulation(s) and / or coating layer(s) prepared from such coating material(s) match at least one given property. The present invention further relates to methods, apparatuses and computer elements, for determining property data of coating layer(s) prepared from coating material(s) on at least a part of a surface of an object by a coating process.

[0004] TECHNICAL BACKGROUND

[0005] Coating materials are used to produce coatings which protect and enhance the appearance of various surfaces, including surfaces of buildings, automotives, and consumer products. To protect and enhance the appearance of various surfaces, coating materials and resulting coatings must fulfil a number of properties including resistance to mechanical, chemical and environmental influences, optical properties and application properties.

[0006] There are several factors that influence such properties, including the type of substrate being coated, input material(s) present within the coating material, methods used to apply the coating material and / or methods used to dry and / or cure the applied coating material. By considering these factors during development of coating material formulation(s), coating materials and coatings on surfaces can be produced from such coating materials that meet the specific requirements of customers using said coating materials to produce coated objects. However, development of such coating material formulations is cumbersome due to the high number of influences on the properties of the coating material and / or coating that needs to be considered during development, resulting in a large number of candidate coating material formulations that need to be prepared and tested. The amounts of waste generated by the large number of candidate coating material formulations as well as the energy and input material(s) consumed during development may have a high environmental impact. Hence, there is a need to improve the efficiency and sustainability of the coating material development process, allowing to speed up the development of coating material formulations and reducing the environmental impact of the coating development process while still ensuring that required target properties of coating materials associated with such coating material formulations and / or coatings produced from such coating materials are fulfilled.

[0007] SUMMARY OF THE INVENTION

[0008] In an aspect the disclosure relates to a method, in particular a computer-implemented method, for determining input material(s) used to prepare coating materials, wherein at least one property of the coating materials and / or of coating layer(s) prepared from such coating materials match at least one target property, the method comprising:

[0009] • providing target property data associated with the at least one target property,

[0010] • providing a data structure associated with candidate input materials, wherein the data structure provides relationship(s) between use data associated with a use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), active ingredients included in the candidate input materials and property data associated with at least one property of such active ingredients,

[0011] • determining target input material data associated with target input material(s) by determining from the data structure candidate active ingredient(s) based on the target property data and matching property data of the determined candidate active ingredient(s) with property data of further active ingredient(s) included in the provided data structure,

[0012] • providing the determined target input material data associated with the target input material(s).

[0013] In a further aspect the disclosure relates to an apparatus for determining input material(s) used to prepare coating materials, wherein at least one coating property of the coating materials and / or of coating layer(s) prepared from such coating materials have at least one target property, the apparatus comprising:

[0014] • a data providing interface configured to provide target property data associated with the at least one target property and configured to provide a data structure associated with candidate input materials, wherein the data structure provides relationship(s) between use data associated with a use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), active ingredients included in the candidate input materials and property data associated with at least one property of such active ingredients,

[0015] • a target input material determination unit configured to determine target input material data associated with target input material(s) by determining from the data structure candidate active ingredient(s) based on the target property data and matching property data of the determined candidate active ingredient(s) with property data of further active ingredient(s) included in the provided data structure, • a data providing interface configured to provide the determined target input material data associated with the target input material(s).

[0016] In yet a further aspect the disclosure relates to the use of a data structure as updated according to the methods for determining input material(s) as disclosed herein for adjusting coating material formulation(s) and / or for generating new coating material formulation(s), wherein at least one property of coating material(s) associated with such coating material formulation(s) and / or coating layer(s) prepared from such coating material(s) match at least one target property.

[0017] In yet a further aspect the disclosure relates to a method, in particular a computer-implemented method, for adjusting coating material formulation(s), wherein at least one coating property of coating material(s) associated with such adjusted coating material formulation(s) and / or of coating(s) prepared from such coating material(s) match at least one target property, the method comprising:

[0018] • receiving data associated with a coated object including target property data associated with the at least one target property and identifier(s) associated with the coated object and / or coating material(s) used to produce a coating on the coated object,

[0019] • providing formulation data associated with the coating material(s) used to produce the coating on the coated object based on at least one received identifier,

[0020] • providing a data structure associated with candidate input materials, wherein the data structure provides relationship(s) between use data associated with a use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), active ingredients included in the candidate input materials and property data associated with at least one property of such active ingredients,

[0021] • determining target input material data associated with target input material(s) by determining from the data structure candidate active ingredient(s) based on the formulation data and target property data, and matching property data associated with the determined candidate active ingredient(s) to property data of further active ingredient(s) included in the provided data structure,

[0022] • generating adjusted formulation data based on the determined target input material data and the provided formulation data,

[0023] • providing the adjusted formulation data.

[0024] In a further aspect the disclosure relates to an apparatus for adjusting coating material formulation(s), wherein at least one property of coating material(s) associated with such adjusted coating material formulation(s) and / or of coating(s) prepared from such adjusted coating material(s) match at least one target property, the apparatus comprising:

[0025] • a data receiving interface configured to receive data associated with a coated object including target property data associated with the at least one target property and identifier(s) associated with the coated object and / or coating material(s) used to prepare a coating on the coated object, • a data providing interface configured to provide formulation data associated with the coating material(s) used to produce the coating on the coated object based on at least one received identifier and configured to provide a data structure associated with candidate input materials, wherein the data structure provides relationship(s) between use data associated with a use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), active ingredients included in the candidate input materials and property data associated with at least one property of such active ingredients,

[0026] • a target input material determination unit configured to determine target input material data associated with target input material(s) by determining from the data structure candidate active ingredient(s) based on the formulation data and the target property data, and matching property data associated with the determined candidate active ingredient(s) to property data of further active ingredient(s) included in the provided data structure,

[0027] • a formulation generator configured to generate adjusted formulation data based on the determined target input material data and the provided formulation data,

[0028] • a data providing interface configured to provide the adjusted formulation data.

[0029] In a further aspect the disclosure relates to a method, in particular a computer-implemented method, for generating coating material formulation(s), wherein at least one property of coating material(s) produced from such generated coating material formulation(s) and / or of coating(s) prepared from such produced coating material(s) match at least one target property, the method comprising:

[0030] • providing target data associated with a target coating, a target coating process and the at least one target property,

[0031] • providing a data structure associated with candidate input materials, wherein the data structure provides relationship(s) between use data associated with a use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), active ingredients included in the candidate input materials and property data associated with at least one property of such active ingredients,

[0032] • determining target input material data associated with target input material(s) by matching the use data associated with the use of the candidate input materials included in the provided data structure to the provided target data,

[0033] • generating formulation data based on the determined target input material data and the provided target data,

[0034] • providing the generated formulation data.

[0035] In a further aspect the disclosure relates to an apparatus for generating coating material formulation(s), wherein at least one property of coating material(s) produced from such generated coating material formulation(s) and / or of coating(s) prepared from such produced coating material(s) match at least one target property, the apparatus comprising: • a data providing interface configured to provide target data associated with a target coating, a target coating process and the at least one target property and configured to provide a data structure associated with candidate input materials, wherein the data structure provides relationship(s) between use data associated with a use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), active ingredients included in the candidate input materials and property data associated with at least one property of such active ingredients,

[0036] • a target input material determination unit configured to determine target input material data associated with target input material(s) by matching property data associated with the active ingredients and use data associated with the candidate input materials included in the provided data structure to the provided target data,

[0037] • a formulation data generator configured to generate formulation data based on the determined target input material data and the provided target data,

[0038] • a data providing interface configured to provide the generated formulation data.

[0039] In a further aspect the disclosure relates to a method, in particular a computer-implemented method, for determining property data of coating layer(s) prepared from coating material(s) on at least a part of a surface of an object by a coating process, the method comprising:

[0040] • providing coating process data associated with the coating process and identifier(s) associated with a coated object resulting from the coating process and / or coating material(s) used to prepare the coating layer(s),

[0041] • determining formulation data associated with coating material(s) used to prepare the coating layer(s) based on at least one received identifier,

[0042] • providing a data structure associated with candidate input materials, wherein the data structure provides relationship(s) between use data associated with a use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), active ingredients included in the candidate input materials and property data associated with at least one property of such active ingredients,

[0043] • determining coating property data based on the determined formulation data and the provided data structure,

[0044] • providing the generated coating property data.

[0045] In a further aspect the disclosure relates to an apparatus for determining property data of coating layer(s) prepared from coating material(s) on at least a part of a surface of an object by a coating process, the apparatus comprising:

[0046] • a data providing interface configured to provide coating process data associated with the coating process and identifier(s) associated with a coated object produced by the coating process and / or coating material(s) used to prepare the coating layer(s) and configured to provide a data structure associated with candidate input materials, wherein the data structure provides relationship(s) between use data associated with a use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), active ingredients included in the candidate input materials and property data associated with at least one property of such active ingredients,

[0047] • a formulation data determination unit configured to determine formulation data associated with coating material(s) used to produce the coating layer(s) based on at least one received identifier,

[0048] • a coating property determination unit configured to determine coating property data based on the determined formulation data and the provided data structure,

[0049] • a data providing interface configured to provide the generated coating property data.

[0050] In a further aspect the disclosure relates to a computer element, such as a computer readable storage medium, a computer program or a computer program product, comprising instructions, which when executed by a computing node or a computing system, direct the computing node or computing system to carry out the steps of the methods as disclosed herein.

[0051] In a further aspect the disclosure relates to a computer element, such as a computer readable storage medium, a computer program or a computer program product, comprising instructions, which when executed by the apparatuses or systems as disclosed herein, direct these apparatuses or systems to carry out steps these apparatuses or systems are configured to execute.

[0052] Any disclosure, embodiments and examples described herein relate to the methods, the apparatuses, the uses and computer elements lined out above and below. Advantageously, the benefits provided by any of the embodiments and examples equally apply to all other embodiments and examples.

[0053] Embodiments

[0054] In the following, embodiments of the present disclosure will be outlined by ways of embodiments and / or examples. It is to be understood that the present disclosure is not limited to said embodiments and / or examples.

[0055] To improve the coating material development process, transparency on the influences of input material(s) present within coating materials on the properties of such coating materials and / or coating layers produced from such coating materials is crucial.

[0056] By using the data structure defining relationships between the influence of the use of the candidate input materials on the property / ies of coating materials, the active ingredients included in such candidate input materials and the property data associated with such active ingredients, identification of target input material(s) materials based on a similarity in property data of active ingredients included in such input material(s) is enabled. Such relationships may allow to identify target input material(s) not only based on a similarity between provided target properties and known use data associated with the use of candidate input materials within coating materials but also based on similarities between property data of candidate active ingredients (e.g. active ingredients included in input materials associated with use data matching the provided target property data) and property data of further active ingredients (e.g. active ingredients included in input materials associated with use data not matching the provided target property data) included in the data structure. The property data of such candidate active ingredients may hence serve to identify target chemical structure data associated with chemical structure(s) and / or target functional group data associated with functional group(s) required to be present within active ingredients to achieve the provided target property Zies. The property data of such candidate active ingredients may further serve to identify target physical property data associated with physical properties required to be present within active ingredients to achieve the provided target property / ies. Such identified target chemical structure data and / or target functional group data and / or physical property data may then be used to query the data structure to identify further active ingredients associated with chemical structure data and / or functional group data and / or physical property data matching said target chemical structure data and / or said target functional group data and / or physical property data. This allows to identify target input material(s) which may be used within coating material formulation(s) to achieve the at least one target property associated with coating materials and / or coating layers produced therefrom without relying on known use data associated with such input material(s) to identify target input material(s). This improves the flexibility upon developing coating material(s), either by modifying existing coating material formulation(s) or by generating new coating material formulation(s) from scratch, since suitable target input material(s) to be considered during coating material development can be reliably and efficiently identified based on given target property data using said data structure. The data structure may allow to store knowledge associated with the influence(s) of the use of input material(s) within coating material formulations on the properties of associated coating materials and coating layers produced from such coating materials in a structured manner, allowing to use such knowledge to improve the efficiency of the coating material development process.

[0057] By updating existing use data associated with the use of candidate input materials included in the data structure with at least a part of the provided target property data, existing use data may be expanded by such target property data, hence allowing to develop coating material formulation(s) more flexibly. For example, such expansion may allow to identify target input material(s) which may be used to substitute input material(s) present within a coating material formulation to be adjusted more reliably and efficiently without negatively impacting the properties of the associated coating material and / or coating layer(s) prepared from such coating material. In addition, such expansion allows to identify target input material(s) suitable for a more sustainable development process (e.g. a development process associated with less waste generation and reduced input material and energy consumption) more reliably and efficiently without negatively impacting the properties of coating materials containing such target input material(s) and / or coating layer(s) prepared from such coating materials. By using the data structure associated with candidate input materials, target input material(s) suitable to achieve target property / ies of coating materials and / or coating layers produced from such coating materials and required by coating material consumers can be reliably determined. Hence, the data structure may be used identify target input material(s) suitable for adjustment of existing coating material formulations such that the resulting adjusted coating materials and / or coatings prepared from such adjusted coating materials fulfil the target coating property / ies more reliably and efficiently. Such adjustment may be achieved without requiring extensive preparation and testing of candidate coating material formulations, hence allowing to speed up the adjustment process and reducing the environmental impact associated with the coating material development process by avoiding generation of high amounts of waste coating materials and consumption of resources during the development process. Thus, the use of such a data structure may result in a more sustainable adjustment of existing coating materials while ensuring that the adjusted coating materials and coating layers prepared therefrom fulfil predefined requirements, such as customer requirements. The relationships encoded in the data structure allow to identify suitable target input material(s) based on a similarity of chemical structure(s) and / or functional group(s) and / or physical property / ies, hence allowing to identify suitable target input material(s) irrespective of known use data associated with the use of such candidate input materials within coating materials. This may enable identification of target input material(s) which are not associated with use data matching provided target property data, hence allowing to broaden the spectrum of suitable target input material(s) usable for adjustment of coating material formulation(s). This may allow more flexible adjustment of existing coating material formulations with respect to available target input material(s). In addition, environmental impact data associated with candidate input material(s) may be considered as a constraint during adjustment of the coating material formulation, hence allowing to ensure that determined target input material(s) fulfil given environmental impact criteria. This may allow to not only consider target property data, but also further required properties, such as the environmental impact associated with the coating materials and / or the coating produced therefrom, during determination of target input material(s), hence allowing development of more sustainable coating materials and coatings produced therefrom.

[0058] In addition or alternatively, the data structure may be used to identify target input material(s) suitable for generation of new coating material formulations such that the resulting coating materials and / or coatings prepared from such coating materials fulfil given target property / ies more reliably and efficiently. Such generation may be achieved without requiring extensive preparation and testing of candidate coating material formulations, hence allowing to speed up the generation process and reducing the environmental impact associated with the coating material development process by avoiding generation of high amounts of waste coating materials and consumption of resources during the development process. Thus, the use of such a data structure may result in a more sustainable generation of new coating materials while ensuring that the coating materials and coating layers prepared therefrom fulfil predefined requirements, such as customer requirements. In addition, environmental impact data associated with candidate input material(s) may be considered as a constraint during generation of new coating material formulations, hence allowing to ensure that determined target input material(s) fulfil given environmental impact criteria. This may allow to not only consider target property data, but also further required properties, such as the environmental impact associated with the coating materials and / or the coating produced therefrom, during determination of target input material(s), hence allowing development of more sustainable coating materials and coatings produced therefrom.

[0059] By using the data structure including use data associated with the use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), coating property / ies of coatings produced from one or more coating material(s) may be determined based on coating process data acquired during production of the coatings from one or more coating material(s). This allows to determine coating property / ies of coatings quickly and reliably without having to determine such properties via sensor(s). In addition, this allows to tune application and / or curing conditions to achieve desired properties of such produced coatings.

[0060] The methods may be executed by one or more computing node(s) associated with the producer of the coating material. The one or more computing node(s) may be associated with a coating material production producing the coating material or the adjusted coating material. The coating material may be produced based on target input material(s) determined according to the methods disclosed herein, based on adjusted coating material formulation(s) determined according to the methods disclosed herein or based on coating material formulation(s) determined according to the methods disclosed herein.

[0061] Input material may refer to any good which is bought from suppliers and brought to a respective coating material production plant. The input material may include starting material used in the production process of the production plant to produce the coating material. The input material may include intermediate chemical products produced by a production plant of the coating material production and used by a subsequent production plant of the coating material production as input material. Input material may include recycled material and / or renewable material and / or bio-based material. Input material may include a recycled content and / or a renewable content and / or a bio-based content. The input material may comprise or be any input material entering the coating material production. The input material may comprise or be any input material provided at any entry point of the coating material production. The input material may be a solid input material. The input material may be a liquid input material. The input material may be a dispersion. Dispersions may include mixtures in which solid particles are distributed throughout a medium, such as a liquid. The particles can be suspended in the medium by a variety of mechanisms, such as by Brownian motion, electrostatic repulsion, or by the presence of surfactants or other dispersing agents. Dispersions may include suspensions, emulsions and colloids. A suspension may refer to a dispersion in which the particles are large enough to settle out of the medium over time. An emulsion may refer to a dispersion in which the particles are present within the medium in the form of droplets. A colloid may refer to a dispersion in which the particles are intermediate in size between those in suspensions and emulsions, and do not settle out of the medium over time.

[0062] Candidate input material may refer to input material(s) usable to prepare coating materials. Candidate input material(s) may include input material(s) commonly used to prepare coating material(s). Candidate input material(s) may be associated with candidate input material data. Such candidate input material data may be included in one or more data models present within the data structure. The candidate input material may include active ingredients. Active ingredient(s) may be associated with the influence of the use of the candidate input material on the property / ies of the coating material. Target input materials may refer to input materials selected from candidate input materials based on given conditions, such as given target property data.

[0063] Object may refer to any two- or three-dimensional object. The object may comprise one or more surface(s). The object may be a vehicle. The vehicle may be a motor vehicle, such as a car, a van, a minivan, a bus, a SUV (sports utility vehicle), a truck, a semitruck, a tractor, a motorcycle, a trailer, an ATV (all-terrain vehicle), a pickup truck, a heavy duty mover, such as bulldozer, mobile crane and earth mover, an airplanes, boats, ships or other device propelled through space with a motor or engine. The vehicle may be propelled by a motor burning fuel for power and / or by an engine using electricity. Coated object may refer to an object where at least a part of the surface of the object comprises a coating. The coating may include one or more coating layer(s). The coating may be produced by a coating process. The coating process may include application of coating material(s) and drying and / or curing of the applied coating materials. The coating process may further include pretreatment step(s) to prepare the surface(s) of the object. Pretreatment step(s) may be performed prior to application of coating material(s). Application may include applying coating material(s) to at least a part of the surface. A plurality of coating materials may be applied successively. The applied coating material(s) may form coating layer(s) after application of the coating material to the surface(s). The formed coating layer(s) may be dried and / or cured. Curing may be performed per coating layer. Curing may be performed jointly, e.g. two or more coating layers may be jointly cured. This may allow to save energy by reducing the number of curing steps and hence the required energy consumption.

[0064] Property may refer to at least one property of an active ingredient, a coating material and / or a coating produced from such coating material. Properties of active ingredients may include chemical and / or physical properties. Properties of coating materials may include environmental attribute(s) of coating materials, viscosity, stability, stirring stability, settling stability, sagging resistance, leveling properties, popping resistance, pinhole resistance, crater resistance, mottling resistance, travel resistance, color stability, slumping resistance and / or seeding resistance. Properties of coatings may include environmental attribute(s) of coatings, thickness, hardness, flexibility, compatibility with environmental influences, such as humidity and / or UV light, corrosion resistance, adhesion, chemical resistance, roughness, smoothness, haptics, gloss, color and / or texture. The environmental attribute may be a data point or data set digitally specifying the environmental impact of the produced coating material and / or coating layer(s). The environmental attribute may relate to a recycled content of the coating material and / or coating layer(s). The environmental attribute may specify recycled content of the coating material and / or coating layer(s). The environmental attribute may include a quantitative data point relating to the type of impact e.g., in view of the coating materials and / or coating layers recycled content. Environmental attribute(s) may refer to any property or characteristic related to the environmental impact. Environmental attribute(s) may refer to environmental impact data associated with the coating materials and / or the coating layers. Environmental impact data may be associated with or relate to any property or characteristic related to the environmental impact. Environmental characteristic(s) may for example include impact categories such as carbon footprint, greenhouse gas emissions or global warming potential, primary energy demand, cumulative energy demand, biotic and abiotic resource consumption, air emissions, stratospheric ozone depletion potential, ozone formation, terrestrial and / or marine acidification, water consumption, water depletion, water availability, water pollution, noise pollution, freshwater and / or marine eutrophication potential, human carcinogenic and / or non-carcinogenic toxicity, photochemical oxidant formation, particulate matter formation, terrestrial, freshwater and / or marine ecotoxicity, ionizing radiation, agricultural and / or urban land occupation, land transformation, land use, indirect land use, deforestation, biodiversity, mineral resource consumption, and / or fossil resource consumption. The data point or set may specify the product carbon footprint (PCF) of the candidate input material. The data point or set may include data relating to greenhouse gas emissions e.g. released in production of the candidate input material. Greenhouse gas emissions may include emissions such as carbon dioxide (CO2) emission, methane (CH4) emission, nitrous oxide (N2O) emission, hydrofluorocarbons (HFCs) emission, perfluorocarbons (RFCs) emission, sulphurhexafluoride (SFe) emission, nitrogen trifluoride (NF3) emission, combinations thereof and additional emissions. Product Carbon Footprint (PCF) may sum up greenhouse gas emissions and removals from the consecutive and interlinked process steps related to a particular candidate input material. Cradle-to-gate PCF may sum up greenhouse gas emissions based on selected process steps: e.g. from the extraction of resources up to the factory gate where the candidate input material leaves the company producing such candidate input material. Such PCFs may be called partial PCFs. Target property may refer to at least one predefined or given property of a coating material and / or a coating layer produced from a coating material. The target properties may be defined by entities producing coated objects from coating material(s). The target properties may refer to properties defined in a specification associated with the coated object. The target properties may ensure that the coating on the surface of the object has the quality and / or appearance required during the use of the coated object. For instance, target properties may ensure that the coating present on the surface of a vehicle has the mechanical resistance, chemical resistance, environmental influence resistance and appearance desired by vehicle users, such as end customers.

[0065] Active ingredient may refer to a chemical compound associated with at least one property. The active ingredient may influence the at least one property. Influencing the at least one property may include improving or deteriorating the at least one property. Property data of active ingredients may refer to chemical and / or physical property data and / or origin data. Chemical property data may be associated with or may signify chemical properties of active ingredients. Chemical properties may include toxicity, chemical stability in a given environment, flammability, oxidation state(s), ability to corrode, combustibility, acidity and basicity, chemical structure, functional group(s), recyclate content used for producing or manufacturing the active ingredient, bio-based content used for producing or manufacturing the active ingredient and / or renewable content used for producing or manufacturing the active ingredient. Physical property data may be associated with or may signify physical properties. Physical properties may include physical state, color, capacitance, odour, pH, melting point, freezing point, boiling point or initial boiling point and boiling point range, electric charge, electrical conductivity, electrical impedance, electric potential, flash point, flammability, lower explosion limit, upper explosion limit, auto ignition temperature, vapour pressure, decomposition temperature, kinematic viscosity, solubility, partitioning coefficient n-octanol water, relative density or density, relative vapour density, particle characteristics, flow time, fluidity, luminescence, luster, opacity, permeability, permittivity, reflectivity, refractive index, , storage stability, solid content, specific heat, strength, stiffness, temperature, tension, thermal conductivity, thermal resistance and / or wave impedance.

[0066] The data structure may refer to a superset of data models defined for one or more candidate input material(s). For instance, a superset of data models may be associated with a particular candidate input material and may contain a plurality of data models defined for such input material. In another instance, the superset of data models may be associated with a plurality of different candidate input materials. The superset of data models may contain a plurality of data models. The data models contained in the superset may be different from each other. The plurality of data models may include at least two different data models. The data structure may contain a tree structure comprising a root entity or root node connected to the plurality of data model(s). The data structure may include a hierarchical tree structure with a set of connected nodes represented by data models. The data structure may include a hierarchical tree structure per candidate input material associated with the data structure. Each data model in the tree may be connected to one or more child node(s) (e.g. sub data model(s)) and to exactly one parent node, except for the root node, which has no parent node or aspect model. The root entity may correspond to the candidate input material the data structure is associated with. For instance, a data structure associated with a particular candidate input material may define the particular candidate input material as root entity. Likewise, a data structure associated with a plurality of candidate input materials may define each of the plurality candidate input materials as root entity.

[0067] In an embodiment, the input material consists of a single chemical compound or includes at least two different chemical compounds. At least one of the chemical compound(s) included in the input material may be an active ingredient. The input material may hence represent a pure chemical compound or a mixture of different chemical compounds. The mixture of different chemical compounds may include liquid and / or solid chemical compounds. The input material(s) may include solvent(s), binder(s) or resin(s), pigment(s), additive(s) and / or crosslinking agent(s). Common solvents include water, ethanol, isopropyl alcohol, and mineral spirits. Resin(s) or binder(s) may constitute the main film-forming component(s) in coating materials. Examples of resins include (i) poly(meth)acrylates, more particularly hydroxy-functional and / or carboxylate-functional and / or amine-functional poly(meth)acrylates, (ii) polyurethanes, more particularly hydroxy-functional and / or carboxylate-functional and / or amine-functional polyurethanes, (iii) polyesters, more particularly polyester polyols and polycarbonate polyols, (iv) polyethers, more particularly polyether polyols, (v) copolymers of the stated polymers, and (vi) mixtures thereof, preferably from hydroxy-functional poly(meth)acrylates, hydroxy-functional polyurethanes, hydroxy-functional polyesters, hydroxy-functional polyethers and copolymers of said polymers. Pigment(s) may be used to achieve a colored coating. Pigments may include color pigments and effect pigments. Color pigments may include inorganic pigments, such as titanium dioxide, iron oxide, and carbon black and / or organic pigments, such as quinacridone, phthalocyanine, and carbazole pigments. Effect pigments may include flake aluminum pigments, gold bronzes, fire-colored bronzes, iron oxide aluminum pigments, pearlescent pigments, metal oxide mica pigments, flake graphite, flake iron oxide, multilayer effect pigments from PVD films and mixtures thereof. Fillers may be used to improve the strength, durability, and texture of the coating material. Common fillers include silica, calcium carbonate, and talc. Examples of additives include catalysts, UV absorbers; light stabilizers such as HALS compounds, benzotriazoles or oxalanilides; rheology modifiers such as sagging control agents (urea crystal modified resins), organic thickeners and inorganic thickeners; free-radical scavengers; slip additives; polymerization inhibitors; defoamers; wetting agents; fluorine compounds; adhesion promoters; leveling agents; film-forming auxiliaries such as cellulose derivatives; fillers, such as nanoparticles based on silica, alumina or zirconium oxide; flame retardants and mixtures thereof. Crosslinking agent(s) may facilitate crosslinking of the binder or resin upon drying and / or curing of the applied coating material. Suitable crosslinking agent(s) include blocked polyisocyanate compounds, polyisocyanate compounds comprising free isocyanate group(s), carbodiimide compounds or mixtures thereof.

[0068] In an embodiment, the active ingredient is associated with or related to the use data associated with the respective candidate input material including the active ingredient. The active ingredient may be the key factor for achieving at least one property (e.g. at least one property of the coating material including the candidate input material and / or coating layer(s) produced from such coating material) associated with the use data. Hence, the active ingredient may significantly influence the property / ies associated with the use data. For instance, the active ingredient may result in an increase or deterioration of one or more property / ies of the coating material including the candidate input material and / or coating layer(s) produced from such coating material.

[0069] In an embodiment, the target property data includes at least one target property associated with input material(s) to be included in the coating material, the coating material and / or coating layer(s) produced from the coating material. The target property may be selected from at least one chemical and / or physical property associated with the input material(s), environmental attribute(s) associated with input material(s), the coating material and / or the coating layer(s), viscosity associated with the coating material, sagging resistance associated with the coating material, leveling properties associated with the coating material, stability associated with the coating material, stirring stability associated with the coating material, settling stability associated with the coating material, popping resistance associated with the coating material, pinhole resistance associated with the coating material, crater resistance associated with the coating material, mottling resistance associated with the coating material, travel resistance associated with the coating material, color stability associated with the coating material, slumping resistance associated with the coating material, seeding resistance associated with the coating material, hardness associated with the coating layer(s), flexibility associated with the coating layer(s), compatibility of the coating layer(s) with respect to environmental influences, corrosion resistance associated with the coating layer(s), adhesion associated with the coating layer(s), chemical resistance associated with the coating layer(s), roughness associated with the coating layer(s), smoothness associated with the coating layer(s), haptics associated with the coating layer(s), gloss associated with the coating layer(s), color associated with the coating layer(s)and / or texture associated with the coating layer(s).

[0070] In an embodiment, the data structure defines a plurality of data models per candidate input material and defines relationships between the plurality of data models. The data structure may include a hierarchical tree structure with a set of connected nodes represented by the data models. The data structure may provide a relationship between coating material properties and / or coating layer properties associated with the use of candidate input materials within coating materials, active ingredients included in such input materials and property data of such active ingredients. Such relationships may allow to identify similarities between data, such as property data associated with active ingredients, present within the data structure, hence allowing to identify target input material(s) based on additional criteria (e.g. similarity in property data of active ingredients) apart from target property data. This may increase the number of identified target input material(s), enabling a more flexible adjustment of coating material formulations and / or a more flexible generation of new coating material formulations. The data models may include a data model defining use data associated with the candidate input materials, a data model defining composition data associated with the candidate input materials, a data model defining active ingredient(s) within the candidate input materials and / or a data model defining property data associated with such active ingredients.

[0071] Use data associated with the candidate input materials may include coating material type data, coating data, coating process data, property data and amount data. Coating material type data may define the coating material type of the coating material including the respective input material, such as electrocoat material, primer material, filler material, basecoat material, clearcoat material. Coating data may define the coating layer structure type, such as a single layer coating, multilayer coating and / or the coating layer(s) present within the coating layer structure, such as electrocoat-primer coat-basecoat-clearcoat. Coating process data may define the application type (e.g. spray coating, dip coating, roll coating, bar coating, etc.), application equipment data (e.g. ESTA, bath, pneumatic application equipment), application data associated with the respective application equipment, the curing type (e.g. air curing, oven curing, UV curing, IR curing) and / or curing data associated with the respective curing type. Property data may define property / ies of coating material(s) achieved by the use of said candidate input material within such coating material(s) of a defined coating material type and / or property / ies of coating layer(s) achieved by the use of such candidate input material(s) within coating material(s) of a defined coating material type which are used to prepare coating layer(s) of a defined coating layer structure type or coating layer structure via a defined coating process. Amount data may define the amount of candidate input material required to achieve the respective property / ies. The data model defining use data may hence provide a relationship between coating material type the respective candidate input materials are used in, the coating layer structure or the coating layer structure type prepared from coating materials containing the respective candidate input materials, coating process data used to prepare coatings from the respective candidate input material and property data achieved by the use of the respective candidate input materials within the coating material type to prepare a given coating layer structure or coating layer structure type using a given coating process. Such relationship may allow to provide insights into influences of candidate input material(s) on properties of coating materials and / or coating layers under defined circumstances, e.g. using a defined coating material type, coating layer structure or coating layer structure type and coating process.

[0072] Composition data may include compound identifier(s), compound name(s) and compound(s) amount data. Compound identifier(s) may define identifier(s) of chemical compound(s) present within the input material. The identifier(s) may be unique identifier(s) uniquely identifying a given chemical compound within the scope of the data structure. The identifier(s) may include letters and / or numbers. Compound name(s) may define compound name(s) of chemical compound(s) included in the candidate input material. Compound(s) amount data may define the amount of chemical compound(s) present within the candidate input material. The compound(s) amount data may define the amount for at least a part of the chemical compound(s) being present within the candidate input material. The compound(s) amount data may define the amount for each chemical compound being present within the candidate input material.

[0073] The data model defining active ingredients present within the candidate input materials may include compound identifier(s) and associated classifiers. The compound identifier(s) may correspond to the compound identifier(s) included in the composition data. The classifier may be used to classify a respective chemical compound defined by the composition data as being contained within a respective candidate input material as active ingredient.

[0074] Property data associated with active ingredients may include identifier(s), chemical property data, physical property data and origin data. Identifier(s) may define identifier(s) of the respective active ingredient. The identifier(s) may be unique identifier(s) uniquely identifying a given active ingredient within the scope of the data structure. The identifier(s) may correspond to the compound identifier(s). The identifier(s) may include CAS number(s). Chemical property data may define at least one chemical property of the active ingredient. Physical property data may define at least one physical property of the respective active ingredient. Origin data may define the origin of the respective active ingredient. The origin may correspond to the country of origin. The origin may correspond to a production location of the active ingredient. The origin may correspond to a planting and harvesting location of the active ingredient.

[0075] In an embodiment, the candidate active ingredients are determined based on the provided target property data by matching use data associated with candidate input materials with the provided target property data and determining active ingredients associated with matching use data. Active ingredients associated with matching use data may be determined via relationships between the data model including the matching use data and data models including composition data associated with the composition of candidate input materials and data being indicative of active ingredients present within such composition.

[0076] In an embodiment, matching property data of determined candidate active ingredient(s) includes applying shortest path algorithms, nearest path algorithms, similarity search algorithms and / or nearest neighbor algorithms on the provided data structure.

[0077] In an embodiment, the target input material data associated with target input material(s) is determined by matching chemical property data and / or physical property data included in data model(s) defining property data of determined candidate active ingredient(s) with chemical property data and / or physical property data included in data model(s) defining property data associated with further active ingredients. Target input material(s) may include candidate input material(s) associated with use data matching the provided target property data and candidate input material(s) associated with property data of associated active ingredients (e.g. active ingredients included in such candidate input materials) matching property data of determined candidate active ingredients. Further active ingredients may include active ingredients included in candidate input material(s) associated with use data not matching the target property data. The chemical property data may define chemical structure data and / or functional group data. The chemical structure data may be associated with the chemical structure of the active ingredient. The functional group data may be associated with functional group(s) present within the chemical structure of the active ingredient. A functional group may represent a group of atoms in the chemical compound with distinctive chemical properties, regardless of the other atoms in the chemical compound. The atoms in a functional group are linked to each other and to the rest of the chemical compound by covalent bonds. The physical property data may define one or more physical properties of the active ingredient(s). Matching property data of determined candidate active ingredients to property data of further active ingredients allows to determine target input material(s) based on a similarity in chemical structure and / or functional groups and / or physical property / ies, hence allowing to identify target input material(s) not solely on the similarity between known properties associated with such candidate input materials and provided target properties. This may allow to identify a larger number of target input material(s) usable for adjustment of existing coating material formulations and / or for the generation of new coating material formulations, hence improving the flexibility of the coating material development process. In an embodiment, the target input material data associated with target input material(s) is determined by

[0078] - determining preliminary target input material data by determining from the data structure candidate active ingredient(s) based on the target property data and matching property data of the determined candidate active ingredient(s) with property data of further active ingredient(s) included in the provided data structure, and

[0079] - refining the preliminary target input material data by matching environmental attribute(s) associated with determined preliminary target input material data with environmental attribute(s) included in the provided target property data.

[0080] The preliminary target input material data may be refined by comparing environmental attribute(s) included in the provided target property data to environmental attribute(s) associated with the preliminary target input materials. The provided target property data may define environmental impact thresholds for input material(s) to be used within coating material(s). Such thresholds may be compared to environmental attribute(s) associated with the determined preliminary target input material data to determine target input material data associated with environmental attribute(s) below such thresholds.

[0081] In an embodiment, the method further includes a step of updating use data associated with the target input material(s) with at least a part of the target property data. Updating may include generating data point(s) based on the target property data and adding the generated data point(s) to respective use data. Updating use data included in existing data models of the data structure with newly identified property data allows to expand the existing use of candidate input materials, such as existing property data indicating influence(s) of the use of candidate input material(s) in coating materials on coating material properties and / or coating layer properties, with such target properties, hence broadening the use data available for existing candidate input materials. Such expansion allows to develop coating materials more flexibly and efficient. For example, such expansion may allow to identify target input material(s) which may be used to substitute input material(s) present within a given coating material formulation to be adjusted more reliably and efficiently without negatively impacting the properties of the associated coating material and / or coating layer(s) prepared from such coating material. In addition, such expansion allows to identify target input material(s) more reliably and efficiently for preparation of coating materials having a reduced environmental impact without negatively impacting the properties of the coating materials and / or coating layer(s) prepared from such coating material. This may enable production of more sustainable coating material(s) as well as production of more sustainable coated objects.

[0082] In an embodiment of the method for adjusting coating material formulation(s) associated with coating materials the formulation data includes input material identifiers associated with input materials used to prepare the coating material and amount data associated with such input material identifiers. The formulation data may further include instructions to prepare the coating material. The formulation data may be stored in a database and may be interrelated with a coating material identifier. The coating material identifier may be used to gather associated formulation data form the database.

[0083] In an embodiment of the method for adjusting coating material formulation(s) associated with coating materials determining from the data structure candidate active ingredient(s) based on the formulation data and the provided target property data includes

[0084] - determining matching candidate input materials by matching input material identifier(s) included in the formulation data to candidate input material identifiers included in the data structure and

[0085] - determining candidate active ingredients by matching provided target property data to use data associated with determined matching candidate input materials.

[0086] In an embodiment of the method for adjusting coating material formulation(s) associated with coating materials generating adjusted formulation data includes exchanging input material identifier(s) present within the provided formulation data by target input material identifier(s) associated with determined target input material data and / or adjusting amount data present within the formulation data based on amount data associated with the determine target input material data. The amount data associated with target input material data may be included in use data associated with such target input material(s).

[0087] In an embodiment of the method for adjusting coating material formulation(s) associated with coating materials generating adjusted formulation data includes refining the target input material data by matching environmental attribute(s) associated with determined preliminary target input material data with environmental attribute(s) included in the provided target property data and generating adjusted formulation data based on the refined target input material data and the provided formulation data. The preliminary target input material data may be refined by comparing environmental attribute(s) included in the provided target property data to environmental attribute(s) associated with the preliminary target input materials. The provided target property data may define environmental impact thresholds for input material(s) to be used within coating material(s). Such thresholds may be compared to environmental attribute(s) associated with the determined preliminary target input material data to determine target input material data associated with environmental attribute(s) below such thresholds.

[0088] In an embodiment of the method for adjusting coating material formulation(s) associated with coating materials generating adjusted formulation data includes considering environmental attribute(s) included in the provided target property data as constraints during generation of the adjusted formulation data. The environmental attribute(s) included in the provided target property data may be associated with the environmental impact of coating materials. The environmental attribute(s) may include environmental impact threshold(s) associated with environmental impact data of coating materials. Environmental attribute(s) associated with the adjusted formulation data generated based on the determined target input material data and the provided formulation data may be compared to environmental attribute(s) included in the provided target property data to refine adjusted formulation data according to provided environmental attribute constraints. This may allow to generate adjusted formulation data fulfilling not only target coating material properties and / or coating layer properties, but also target environmental attribute(s), hence allowing to generate adjusted formulation data tailored to the requirements of customers with respect to environmental impact associated with coating materials prepared from such adjusted coating material formulations.

[0089] BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0090] In the following, the present disclosure is further described with reference to the enclosed figures. The same reference numbers in the drawings and this disclosure are intended to refer to the same or like elements, components, and / or parts.

[0091] FIG. 1 illustrates schematically a process for adjusting existing coating materials and / or for developing new coating materials.

[0092] FIG. 2 illustrates a block diagram of an example system for determining input material(s) used to prepare coating materials, wherein at least one property of the coating materials and / or of coating layer(s) prepared from such coating materials match at least one target property in accordance with an embodiment of the present disclosure.

[0093] FIG. 3 illustrates a data structure associated with candidate input material(s) usable to prepare coating material(s) and including various data models in accordance with an embodiment of the present disclosure.

[0094] FIG. 4 illustrates various data included in the data models illustrated in FIG. 3 in accordance with an embodiment of the present disclosure.

[0095] FIG. 5 illustrates a flow chart of an example method for determining input material(s) used to prepare coating materials, wherein at least one property of the coating materials and / or of coating layer(s) prepared from such coating materials match at least one target property in accordance with an embodiment of the present disclosure.

[0096] FIG. 6 illustrates a block diagram of an example system for adjusting coating material formulation(s), wherein at least one coating property of coating material(s) associated with such adjusted coating material formulation(s) and / or of coating(s) prepared from such coating material(s) match at least one target property in accordance with an embodiment of the present disclosure.

[0097] FIG. 7 illustrates an example system and associated methods for adjusting coating material formulation(s), wherein at least one coating property of coating material(s) associated with such adjusted coating material formulation(s) and / or of coating(s) prepared from such coating material(s) match at least one target property received from a coating material consumer in accordance with an embodiment of the present disclosure.

[0098] FIG. 8 illustrates an example system for controlling the production of adjusted coating material(s) based on adjusted coating material formulation data in accordance with an embodiment of the present disclosure.

[0099] FIG. 9 illustrates a flow chart of an example method for adjusting coating material formulation(s), wherein at least one coating property of coating material(s) associated with such adjusted coating material formulation(s) and / or of coating(s) prepared from such coating material(s) match at least one target property received from a coating material consumer in accordance with an embodiment of the present disclosure.

[0100] FIG. 10 illustrates a block diagram of an example system for generating coating material formulation(s), wherein at least one property of coating material(s) produced from such generated coating material formulation(s) and / or of coating(s) prepared from such produced coating material(s) match at least one target property in accordance with an embodiment of the present disclosure.

[0101] FIG. 11 illustrates a flow chart of an example method for generating coating material formulation(s), wherein at least one property of coating material(s) produced from such generated coating material formulation(s) and / or of coating(s) prepared from such produced coating material(s) match at least one target property in accordance with an embodiment of the present disclosure.

[0102] FIG. 12 illustrates a system and associated methods for determining property data of coating layer(s) prepared from coating material(s) based on received coating process data associated with a coating process to prepare such coating layer(s) from the coating material(s) in accordance with an embodiment of the present disclosure.

[0103] FIG. 13 illustrates a flow chart an example method for determining property data of coating layer(s) prepared from coating material(s) based on received coating process data associated with a coating process to prepare such coating layer(s) from the coating material(s) in accordance with an embodiment of the present disclosure.

[0104] FIG. 14 illustrates a schematic drawing of an apparatus that may be used to implement the methods and systems described in FIG. 2 to FIG. 13 in accordance with an example embodiment of the present disclosure. FIG. 15 illustrates a schematic drawing of a client server setup that may be used to implement the methods and systems described in FIG. 2 to FIG. 13 in accordance with an example embodiment of the present disclosure.

[0105] DETAILED DESCRIPTION

[0106] The following embodiments are mere examples for implementing the methods, the systems or the computer elements disclosed herein and shall not be considered limiting.

[0107] FIG. 1 illustrates schematically a process for adjusting existing coating materials and / or for developing new coating materials. Adjusting existing coating material(s) may include adjusting the formulation associated with such existing coating material(s). The formulation may be adjusted by adjusting the amount(s) of ingredients present within the formulation and / or by exchanging ingredients present within the formulation by other ingredients. Developing new coating materials may include developing such new coating materials “from scratch”, e.g. not using an existing coating material formulations as a basis for the development process.

[0108] The adjustment and / or development process of a coating material may involve several stages. In the research and development phase 102, requirements for the coating material, such as the target substrate material, target properties, such as target coating material properties and / or target coating properties (e.g. target properties of the coating layer resulting from application and / or curing of the coating material), target coating layer structure, target coating material type (e.g. electrocoating, primer, primer-surface, filler, basecoat, clearcoat) and / or target application and / or curing process may be determined. Target properties may include coating layer thickness, coating thickness, adhesion, durability, UV resistance, mechanical resistance (such as flexibility, hardness), chemical resistance, environmental influence resistance (such as humidity resistance, UV exposure, temperature exposure, corrosion resistance), appearance (e.g. gloss, color and / or texture) and / or environmental impact associated with the coating material.

[0109] Requirements may be determined from input data. Input data may include target properties and / or a target coating material type and / or target coating process and / or target substrate material. Input data may be provided by coating material consumer(s), such as entities producing coated objects. Entities producing coated objects may include OEMs (original equipment manufacturers) and / or entities producing coated parts, such as coated automotive parts.

[0110] Based on the requirements, candidate coating material formulations may be developed. Candidate coating material formulations may be developed based on existing coating material formulations or from scratch. Candidate coating material formulations may include material identifier(s) and respective amounts. Material identifier(s) may include an input material name, a unique number, a unique combination of letters and numbers or a combination thereof. Candidate coating material formulations may further include instructions to prepare the associated candidate coating material.

[0111] In the formulation and synthesis phase 104, candidate coating materials may be prepared from candidate coating material formulations using respective input material(s) defined in the candidate coating material formulation. Input material(s) may include binders, pigments, solvents, thickeners, stabilizers, defoamers and / or pH adjusters. Input material(s) may be sourced from suppliers or may be prepared from chemical material(s) provided by suppliers by the coating material producer. The coating material may be produced by mixing the input material(s) listed in the coating material formulation. Phase 104 may further include determining chemical and / or physical properties of the prepared coating materials, such as toxicity, chemical stability in a given environment, flammability, oxidation state(s), ability to corrode, combustibility, acidity and basicity, chemical composition, recyclate content used for producing or manufacturing the coating material, bio-based content used for producing or manufacturing the coating materials, renewable content used for producing or manufacturing the coating materials, pH value, boiling point, capacitance, color, concentration, density, electric charge, electrical conductivity, electrical impedance, electric potential, flow rate, fluidity, luminescence, luster, mass, melting point, opacity, permeability, permittivity, reflectivity, refractive index, solubility, storage stability, solid content, specific heat, strength, stiffness, temperature, tension, thermal conductivity, thermal resistance, viscosity, volume and / or wave impedance. The chemical and / or physical properties of the candidate coating material(s) may be measured with sensor(s) configured to measure such properties. The chemical and / or physical properties may be determined from data acquired by such sensor(s). The chemical and / or physical properties may be compared to target coating material properties to select candidate coating materials meeting such target coating material properties.

[0112] In the coating material application and curing phase 106, at least a part of the candidate coating materials prepared in phase 104 may be applied to a substrate to prepare candidate coatings. The substrate may be an uncoated metal substrate, a metal substrate being coated with a cured electrocoat layer and / or a cured filler layer and / or a cured multilayer coating; a plastic substrate optionally being coated with a cured primer layer; or a substrate comprising metallic and plastic parts and optionally being coated with a cured electrocoat layer and / or a cured filler layer and / or a cured primer-surfacer layer and / or a cured primer layer. The substrate may correspond to the target substrate material signified by the input data provided phase 102. The candidate coating materials may be applied by methods known to those skilled in the art for application of coating materials, such as dipping, bar coating, spraying, rolling or the like. Spray application may include compressed air spraying (pneumatic application), airless spraying, high-speed rotation, electrostatic spray application (ESTA), optionally in association with hot-spray application, for example hot-air spraying. Application of the candidate coating material(s) to at least a part of the surface of the substrate may result in the formation of a candidate coating layer. The candidate coating layer may be formed by levelling of the applied candidate coating material. The formed candidate coating layer may be dried and / or cured at elevated temperatures. The formed candidate coating layer may be dried and / or cured using heat and / or irradiation, such as UV irradiation.

[0113] Further coating materials may be applied on top of the dried and / or cured candidate coating layer. Further applied coating material(s) may be cured separately or jointly with the candidate coating layer. Application of further coating material(s) may allow to prepare a coating layer structure comprising the candidate coating layer and matching the target coating layer structure.

[0114] In the testing and characterization phase 108, the properties (e.g. coating properties) of the coating formed on the substrate and comprising the candidate coating layer, such as a multilayer coating comprising the candidate coating layer, may be analyzed. Coating properties may include mechanical properties, such as hardness, flexibility, compatibility with environmental influences, such as humidity, heat, temperature, UV exposure, corrosion resistance, adhesion, chemical resistance, appearance, such as gloss, color and / or texture. The coating properties may be measured using respective sensor(s). The coating properties may be determined from data acquired by the sensor(s). The coating properties of candidate coating(s) may be compared to target coating properties. If the coating properties do not match the target coating properties, the process may return to phase 104 and the properties of the coating material may be optimized, for example by adjusting the composition, thickness, application and / or curing conditions. If coating properties of at least one candidate coating match the target coating properties, the process may proceed to phase 110.

[0115] In phase 110, scale-up and commercialization may be performed. In this phase, a scalable synthesis process for the candidate coating materials deemed suitable in phase 108 may be determined.

[0116] In phase 112, quality control and assurance may be performed. This may include development of quality control procedures for the coating material production process, implementation of quality assurance protocols to ensure consistent coating material quality and performance of regular inspections and audits to maintain quality standards.

[0117] FIG. 2 illustrates a block diagram of an example system 202 for determining input material(s) used to prepare coating materials, wherein at least one property of the coating materials and / or of coating layer(s) prepared from such coating materials match at least one target property in accordance with an embodiment of the present disclosure. The input material(s) may be used to produce coating material(s). The input material(s) may be recycled material(s) and / or bio-based input material(s) and / or renewable input material(s). The input material(s) may include a recycled content and / or a biobased content and / or a renewable content. The coating layer may be an electrocoating layer, a primer layer, a filler layer, a basecoat layer or a clearcoat layer. The system may be used to implement the method illustrated in FIG. 5. Properties of coating materials may be influenced by coating material ingredients (e.g. input material(s) used to prepare the coating material) present within a coating material of a given coating material type. Properties of coating layers may be influenced by coating material ingredients present within a coating material of a given coating material type, the application and / or curing process used to prepare the coating from one or more coating material(s) and / or the layer thickness of coating layer(s) and / or the coating.

[0118] The input material(s) may include solvents(s), binder(s) or resin(s), pigment(s), additive(s) and / or crosslinking agent(s). Common solvents include water, ethanol, isopropyl alcohol, and mineral spirits. Resins(s) or binder(s) constitute the main film-forming components in coating materials. They can be natural or synthetic and are responsible for the coatings durability and gloss. Examples of resins include (i) poly(meth)acrylates, more particularly hydroxy-functional and / or carboxylate-functional and / or amine- functional poly(meth)acrylates, (ii) polyurethanes, more particularly hydroxy-functional and / or carboxylate-functional and / or amine-functional polyurethanes, (iii) polyesters, more particularly polyester polyols and polycarbonate polyols, (iv) polyethers, more particularly polyether polyols, (v) copolymers of the stated polymers, and (vi) mixtures thereof, preferably from hydroxy-functional poly(meth)acrylates, hydroxy-functional polyurethanes, hydroxy-functional polyesters, hydroxy-functional polyethers and copolymers of said polymers. Pigment(s) may be used to achieve a colored coating. Pigments may include color pigments and effect pigments. Color pigments may include inorganic pigments, such as titanium dioxide, iron oxide, and carbon black and / or organic pigments, such as quinacridone, phthalocyanine, and carbazole pigments. Effect pigments may include flake aluminum pigments, gold bronzes, fire-colored bronzes, iron oxide aluminum pigments, pearlescent pigments, metal oxide mica pigments, flake graphite, flake iron oxide, multilayer effect pigments from PVD films and mixtures thereof. Fillers may be used to improve the strength, durability, and texture of the coating material. Common fillers include silica, calcium carbonate, and talc. Examples of additives include catalysts, UV absorbers; light stabilizers such as HALS compounds, benzotriazoles or oxalanilides; rheology modifiers such as sagging control agents (urea crystal modified resins), organic thickeners and inorganic thickeners; free-radical scavengers; slip additives; polymerization inhibitors; defoamers; wetting agents; fluorine compounds; adhesion promoters; leveling agents; film-forming auxiliaries such as cellulose derivatives; fillers, such as nanoparticles based on silica, alumina or zirconium oxide; flame retardants and mixtures thereof. Crosslinking agent(s) may facilitate crosslinking of the binder or resin upon curing of the formed coating layer. Suitable crosslinking agent(s) include blocked polyisocyanate compounds, polyisocyanate compounds comprising free isocyanate group(s), carbodiimide compounds or mixtures thereof.

[0119] The input material(s) may consist of a single chemical compound. Input material(s) may include a mixture of two or more different chemical compound(s). For example, resin(s) may include a first chemical compound being a polymer and a second chemical compound being a solvent. Input material(s) may be associated with coating material property / ies and / or coating layer property / ies (see also FIG. 3 and FIG. 4). For instance, input material(s) may influence coating material properties and / or coating layer properties. The respective property may be associated with one or more compound(s) present within the input material (e.g. active ingredient(s)). The property may signify properties of coating materials resulting from the use of the input material within the coating material. The property may signify properties of coatings resulting from the use of a coating material containing such input material. Coatings may include single layer or multilayer coatings. If the input material contains more than one chemical compound, the property may be associated with a particular chemical compound or group of chemical compound(s). Such chemical compound(s) may be denoted active ingredient(s).

[0120] The input material determinator 208 may include input material selector 202. Input material selector 202 may be configured to determine target input material(s) based on target property data provided to input material selector 202. Target property data may include one or more target property / ies of active ingredient(s), a coating material and / or a coating. The coating may include one or more coating layer(s). Target property data may be provided from a database, for example based on an identifier associated with such target property data stored in such database. Target property data may be provided by a third party, for example as part of a requirement of such third party with respect to coating properties. Input material selector 202 may have access to data structure 206 associated with candidate input material(s). Target property data may include at least one chemical and / or physical property associated with the input material(s), environmental attribute(s) associated with input material(s), the coating material and / or the coating layer(s), viscosity associated with the coating material, sagging resistance associated with the coating material, leveling properties associated with the coating material, stability associated with the coating material, stirring stability associated with the coating material, settling stability associated with the coating material, popping resistance associated with the coating material, pinhole resistance associated with the coating material, crater resistance associated with the coating material, mottling resistance associated with the coating material, travel resistance associated with the coating material, color stability associated with the coating material, slumping resistance associated with the coating material, seeding resistance associated with the coating material, hardness associated with the coating layer(s), flexibility associated with the coating layer(s), compatibility of the coating layer(s) with respect to environmental influences, corrosion resistance associated with the coating layer(s), adhesion associated with the coating layer(s), chemical resistance associated with the coating layer(s), roughness associated with the coating layer(s), smoothness associated with the coating layer(s), haptics associated with the coating layer(s), gloss associated with the coating layer(s), color associated with the coating layer(s)and / or texture associated with the coating layer(s). The data structure 206 may include candidate input material data associated with one or more candidate input material(s). The data structure 206 may provide providing relationship(s) between use data of candidate input materials, composition data of candidate input materials, composition component data signifying active ingredients present within the candidate input materials and property data of such active ingredients. The data structure 206 may be stored on one or more databases. The databases may be distributed databases. The distributed databases may include one or more data model(s) of the data structure. Relationships between the data model(s) may allow to identify all data models associated with a given candidate input material within the database(s). The data structure 206 may be a graph-structured data structure.

[0121] With reference to FIG. 3, data structure 206 may define a plurality of data models, such as input material use data model 304, composition data model 306, composition component data model 308 and active ingredient property data model 310. The plurality of data models may be defined per candidate input material 302. The plurality of data models may include the candidate input material data associated with respective candidate input material(s). The data structure 206 may contain data models for a plurality of candidate input materials. The data models may represent data sets present within one or more databases. The one or more data models may represent entities of a graph-based structure. The candidate input material 302 may be identified using an input material identifier 430. The input material identifier 430 may include identifier(s) uniquely identifying the candidate input material 302 within the data structure 206. The input material identifier may include a batch number, a LOT number, a unique string including letters and / or numbers, or a combination thereof. The candidate input material 302 may be associated with environmental attribute(s) 432. Environmental attribute(s) 432 may specify the environmental impact of the respective candidate input material 302. The environmental attribute may be a data point or data set digitally specifying the environmental impact of the candidate input material as outlined previously. The data point or set may specify the product carbon footprint (PCF) of the candidate input material. The data point or set may include data relating to greenhouse gas emissions e.g. released in production of the candidate input material. Greenhouse gas emissions may include emissions such as carbon dioxide (CO2) emission, methane (CH4) emission, nitrous oxide (N2O) emission, hydrofluorocarbons (HFCs) emission, perfluorocarbons (RFCs) emission, sulphurhexafluoride (SFe) emission, nitrogen trifluoride (NF3) emission, combinations thereof and additional emissions. Product Carbon Footprint (PCF) may sum up greenhouse gas emissions and removals from the consecutive and interlinked process steps related to a particular candidate input material. Cradle-to-gate PCF may sum up greenhouse gas emissions based on selected process steps: e.g. from the extraction of resources up to the factory gate where the candidate input material leaves the company producing such candidate input material. Such PCFs may be called partial PCFs.

[0122] The data structure 206 may define relationships between one or more data model(s) of the plurality of data models defined in said data structure 206. The relationships may define a tree structure for the plurality of data models defined in the data structure 206, for example as shown in FIG. 4. The tree structure may include one or more levels resulting in a hierarchical order of the data models defined in said data structure 206. The relationship between data model(s) on a higher tree level with respect to data model(s) in the following lower tree level may be described as a parent - child relationship, e.g. data models in the higher tree level may be denoted as parent data models while data model(s) associated with said parent data model(s) in the following lower tree level may be denoted as child data model(s). For instance, candidate input material 302 may be denoted as parent data model (or root data model / root node) and input material use data model 304 may be denoted as child data model. The tree structure may be defined per candidate input material associated with the data structure 206. Hence, the data structure may include a tree structure per candidate input material 302 associated with candidate input material data included in the data structure 206.

[0123] The relationship(s) may be defined by relationship representation(s) specifying parent data model(s) associated with child data model(s) and / or child data model(s) associated with a respective parent data model. The relationship representation may be associated with the respective parent data model. The relationship representation may be associated with the respective child data models. The relationship representation may specify the relationship type between the respective parent data model and child data models associated with the respective parent data model. For instance, the relationship representation associated with the root entity 302 (or root node) may specify the child data model 304 associated with said root entity and the relationship type between the root entity and the child data model. The relationship type may specify whether respective child data models may be mandatory data models or non-mandatory data models. Mandatory data models may be associate with a 1 :1 or 1 :many relationship type while nonmandatory data models may be associated with a 1 :0 relationship type.

[0124] The relationship type may specify the number of child data models associated with the respective parent data model. For instance, a 1 :1 relationship type may define that exactly one child data model, such as aspect data 304, is present with respect to root data model 302. In another instance, a 1 :many relationship type may be used to define that more than one child data model, such as data model 308, may be associated with the respective parent data model, such as data model 306.

[0125] Each data model may contain one or more data point(s) associated with the respective candidate input material 302. Data point(s) may represent attributes and associated data types. The data point(s) may be associated with a data class or a data category. With continued reference to FIG. 3 and with reference to FIG. 4, input material use data model 304 may include the following data classes: coating material type data 402, coating data 404, coating process data 406, coating property data 408 and amount data 410. Coating material type data 402 may contain attribute(s) and associated data types indicating the type of the coating material the respective input material is used within. For instance, the attribute may be a classifier indicating the coating material type, such as electrocoat material, primer material, filler material, basecoat material, clearcoat material, the candidate input material is used within and the data type may represent a string. Coating data 404 may contain attribute(s) and associated data types indicating the coating layer structure of the coating prepared using the coating material including the candidate input material. The attribute may be a classifier indicating the coating layer structure type, such as a single layer coating, multilayer coating or an array indicating the coating layer(s) present within the coating layer structure, such as electrocoat-primer coat-basecoat-clearcoat and the data type may be a string. Coating process data 406 may contain attribute(s) and associated data types indicating the coating process used to prepare the coating. The attribute(s) may indicate the application type (e.g. spray coating, dip coating, roll coating, bar coating, etc.), application equipment data (e.g. ESTA, bath, pneumatic application equipment), application data associated with the respective application equipment, the curing type (e.g. air curing, oven curing, UV curing, IR curing) and / or curing data associated with the respective curing type. Data types may include integers and / or strings and / or floats. Application data may include shaping air value(s), flow rate, bell speed, high voltage, distance to object, distance to track, traction speed, voltage, current density, deposition time, temperature or a combination thereof. Application equipment data may include the manufacturer, model, year of manufacturing, atomizer type / model, shaping air ring type / model, bell cup or air cap type / model and / or bath volume. Curing data may include curing temperature(s), curing time(s), humidity, air flow and / or temperature ramping. Coating property data 408 may contain attribute(s) and associated data type(s) indicating property / ies of a coating material achieved by the use of the candidate input material within such coating material of a defined coating material type and / or property / ies of coating layer(s) achieved by the use of such candidate input material(s) within coating material(s) of a defined coating material type which are used to prepare coating layer(s) of a defined coating layer structure type or coating layer structure via a defined coating process. Coating property / ies may be associated with or relate to improvements or deteriorations with respect to chemical and / or mechanical resistance, environmental influence resistance, mechanical and / or chemical stability and / or appearance (e.g. gloss, color and / or texture and / or roughness and / or smoothness and / or haptics) of the coating, levelling properties of coating materials, sagging properties of coating materials, stability of coating materials, stirring stability of coating materials, settling stability of coating materials, popping resistance of coating materials, pinhole resistance of coating materials, crater resistance of coating materials, mottling resistance of coating materials, travel resistance of coating materials, color stability of coating materials, slumping resistance of coating materials and / or seeding resistance of coating materials,. Coating property / ies may be associated with or relate to environmental attribute(s) associated with the candidate input material. Coating property / ies may be associated with or relate to at least one chemical and / or physical property associated with the candidate input material. The attribute(s) may indicate the coating material property / ies and / or coating layer property / ies influenced by the candidate input material. Data type(s) may include string(s) and / or integer(s). Amount data 410 may contain attribute(s) and associated data type(s) indicating the amount of candidate input material required to achieve the respective property / ies. Data types may include integer(s) and / or string(s). The input material use data model 304 may hence provide a relationship between coating material type the candidate input material is used in, coating layer structure prepared from coating materials containing the candidate input material, coating process data used to prepare the coating from candidate input material containing coating material and property data achieved by the use of the candidate input material within the coating material and / or achieved by the use of the candidate input material within a given coating material type to prepare a given coating layer structure using a given coating process. Such relationship may allow to provide insights into influences of candidate input material(s) on properties of coating materials and / or coating layers under defined circumstances, e.g. using a defined coating material type, coating layer structure and coating process. Input material use data model 304 may define sub data model(s). In this embodiment, input material use data model 304 defines a composition data model 306. The composition data model 306 may have a 1 :1 relationship with parent data model 304. Hence, composition data model 306 may be a mandatory data model of data structure 206. Composition data model 306 may include the following data classes: compound identifier(s) 412, compound name(s) 414, compound(s) amount data 416. Compound identifier(s) 412 may contain attribute(s) and associated data types indicating the identifier(s) of chemical compound(s) present within the candidate input material 302. The identifier(s) may be unique identifier(s) uniquely identifying a given chemical compound within the scope of the data structure 206. The identifier(s) may include letters and / or numbers. The data type may be string. Compound name(s) 414 may contain attribute(s) and associated data types indicating compound name(s) of chemical compound(s) included in the input material 302. The data type may be string. Compound(s) amount data 416 may indicate the amount of chemical compound(s) present within the candidate input material 302. The compound(s) amount data 416 may indicate the amount for at least a part of the chemical compound(s) being present within the candidate input material 302. The compound(s) amount data 416 may indicate the amount for each chemical compound being present within the candidate input material 302. The data type may be an integer or a float.

[0126] Composition data model 306 may define sub data model(s). In this embodiment, composition data model 306 defines a composition component data model 308. Composition component data model 308 may have a 1 :1 or a 1 :many relationship with the parent data model 306. This allows to consider the varying number of components present within different chemical composition. Composition component data model 308 may include the following data classes: compound identifier(s) 412, classifier active ingredient 418. Classifier active ingredient 418 may contain attribute(s) and associated data types indicating which chemical compound(s) present within the candidate input material 302 are active ingredient(s), e.g. are resulting in the property / ies previously mentioned if used within coating material(s) used to prepare coatings. The attribute may be a classifier and the data type may be a Boolean.

[0127] Composition component data model 308 may define sub data model(s). In this embodiment, composition component data model 308 defines an active ingredient property data model 310. Composition component data model 308 may have a 1 :0 or a 1 :1 relationship with parent data model 308. Hence, the active ingredient property data model 310 may represent a non-mandatory data model. This allows to consider that only a part of the chemical compounds present within the input material 302 represent active ingredients. Active ingredient property data model 310 may include the following data classes: Identifier(s) 420, chemical property data 422, physical property data 424 and origin data 426. Identifier(s) 420 may contain attribute(s) and associated data types indicating the identifier(s) of the respective active ingredient. The identifier(s) may be unique identifier(s) uniquely identifying a given active ingredient within the scope of the data structure. The identifier(s) may correspond to the compound identifier(s). The identifier(s) may include CAS numbers. The data type may be string. Chemical property data 422 may contain attribute(s) and associated data types indicating the chemical properties of the active ingredient. Chemical properties may include toxicity, chemical stability in a given environment, flammability, oxidation state(s), ability to corrode, combustibility, acidity and basicity, chemical structure, functional group(s), recyclate content used for producing or manufacturing the active ingredient, bio-based content used for producing or manufacturing the active ingredient and / or renewable content used for producing or manufacturing the active ingredient The data type(s) may include string(s). Physical property data 424 may contain attribute(s) and associated data types indicating physical properties of the respective active ingredient. Physical properties may include physical state, color, capacitance, odour, pH, melting point, freezing point, boiling point or initial boiling point and boiling point range, electric charge, electrical conductivity, electrical impedance, electric potential, flash point, flammability, lower explosion limit, upper explosion limit, auto ignition temperature, vapour pressure, decomposition temperature, kinematic viscosity, solubility, partitioning coefficient n-octanol water, relative density or density, relative vapour density, particle characteristics, flow time, fluidity, luminescence, luster, opacity, permeability, permittivity, reflectivity, refractive index, , storage stability, solid content, specific heat, strength, stiffness, temperature, tension, thermal conductivity, thermal resistance and / or wave impedance. The data type(s) may include string(s). Origin data 426 may include attribute(s) and data type(s) signifying the origin of the respective active ingredient. The origin may correspond to the country of origin. The origin may correspond to a production location of the active ingredient. The origin may correspond to a planting and harvesting location of the active ingredient. Data type(s) may include string(s).

[0128] Referring back to FIG. 2 and with continued reference to FIG. 3 and FIG. 4, input material selector 202 may be configured to select from the candidate input materials associated with the data structure 206 one or more target input material(s) based on the provided target property data. Input material selector 202 may be configured to determine from the data structure 206 preliminary candidate input material data by matching the target property data to coating property data included in the candidate input material use data model(s) 304 associated with candidate input material(s). Matching may include the application of shortest path algorithms, nearest path algorithms, similarity search algorithms and / or nearest neighbor algorithms on the data structure 206. Input material selector 202 may be configured to determine candidate active ingredient data included in such preliminary candidate input material data using respective composition data models 306 and composition component data models 308 indicating chemical compound(s) within preliminary candidate input material(s) as active ingredient. Input material selector 202 may be configured to determine target input material data associated with target input material(s) by matching chemical property data included in active ingredient property data model 310 of such identified preliminary active ingredients with chemical property data included in active ingredient property data models associated with further candidate input material(s), e.g. candidate input material(s) not being identified as preliminary candidate input material(s). For instance, the chemical structure data and / or functional group data included in the chemical property data of data model 310 and being associated with preliminary active ingredients may be matched to chemical structure data and / or functional group data of other data models 310 associated with further active ingredients and being included in data structure 206. In addition or alternatively, physical property data of data model 310 and being associated with preliminary active ingredients may be matched to physical property data of other data models 310 associated with further active ingredients and being included in data structure 206. Target input material data may include input material identifier(s) of input material(s) including active ingredients associated with chemical structure data and / or functional group data and / or physical property data matching the chemical structure data and / or functional group data and / or physical property data associated with preliminary active ingredients.

[0129] The chemical structure data and / or functional group data and / or physical property data associated with preliminary active ingredients may hence indicate or relate to or signify guiding structure(s) in terms of chemical structure and / or functional group(s) and / or physical property / ies required to achieve the given target property / ies. Such identified guiding structure(s) and / or property / ies may then be used to query the data structure 208 for further active ingredients included in input material(s) and being associated with chemical structure data and / or functional group data and / or physical property data matching said guiding structure(s) but not being related to coating property data matching the provided target property data. This allows to identify further input material(s) which may be used to achieve the given target coating material property without relying on known coating property data associated with such input material(s) to identify suitable input material(s). This may allow to improve the flexibility upon developing new coating material(s), either by modifying existing coating materials or by generating new coating materials from scratch, since the number of input material(s) available to achieve required coating properties is increased significantly by said approach.

[0130] Input material selector 202 may be configured to refine determined target input material data by matching environmental attribute(s) associated with determined target input material data with environmental attribute(s) included in the provided target property data. The determined target input material data may be refined by comparing environmental attribute(s) included in the provided target property data to environmental attribute(s) associated with the target input materials. The provided target property data may define environmental impact thresholds for input material(s) to be used within coating material(s). Such thresholds may be compared to environmental attribute(s) associated with the determined preliminary target input material data to determine target input material data associated with environmental attribute(s) below such thresholds.

[0131] Input material selector 202 may be configured to provide the determined target input material data and / or the refined target input material data. Providing may include providing said determined target input material and / or refined target input material data via a communication interface for display. This may allow a user to identify target input material(s) associated with the determined target input material data and / or refined target input material data. Input material selector 202 may be configured to provide the determined target input material data / refined target input material data and received target property data to data structure updater 204. Data structure updater 204 may be configured to update data structure 206. Data structure updater 204 may be configured to add at least a part of the target property data as data point(s) of data class coating property data 408 to input material use data model(s) 304 associated with candidate input material(s) matching the target input material data and / or refined target input material data. Data structure updater 204 may be configured to determine input material use data model(s) 304 associated with candidate input material(s) matching the target input material data and / or refined target input material data. Data structure updater 204 may be configured to match the target input material data to input material identifier(s) of candidate input materials 302 included in the data structure 206 to determine candidate input material(s) matching the target input material data. Data structure updater 204 may be configured to match the refined target input material data to input material identifier(s) of candidate input materials 302 included in the data structure 206 to determine candidate input material(s) matching the refined target input material data. Data structure updater 204 may be configured to generate data point(s) based on the target property data and to add the generated data point(s) to respective data models 304. Updating use data included in existing data models 304 of the data structure 206 with newly identified property data allows to expand the existing use of candidate input materials, such as existing property data indicating influence(s) of the use of candidate input material(s) in coating materials on coating material properties and / or coating layer properties, with such target properties, hence broadening the use data available for existing candidate input materials. Such expansion allows to develop coating materials more flexibly and efficient. For example, such expansion may allow to identify target input material(s) which may be used to substitute input material(s) present within a given coating material formulation to be adjusted more reliably and efficiently without negatively impacting the properties of the associated coating material and / or coating layer(s) prepared from such coating material. In addition, such expansion allows to identify target input material(s) more reliably and efficiently for preparation of coating materials having a reduced environmental impact without negatively impacting the properties of the coating materials and / or coating layer(s) prepared from such coating material. This may enable production of more sustainable coating material(s) as well as production of more sustainable coated objects.

[0132] FIG. 5 illustrates a flow chart of an example method for determining input material(s) used to prepare coating materials, wherein at least one property of the coating materials and / or of coating layer(s) prepared from such coating materials match at least one target property in accordance with an embodiment of the present disclosure. The input material(s) may include input material(s) mentioned in the context of FIG. 2. The coating layer may be a coating layer as described in the context of FIG. 2. The method may be implemented by the system illustrated in FIG. 2.

[0133] Target property data may be provided (see block 502). Target property data includes at least one target property associated with input material(s) to be included in the coating material, the coating material and / or coating layer(s) produced from the coating material. The target property may be selected from at least one chemical and / or physical property associated with the input material(s), environmental attribute(s) associated with input material(s), the coating material and / or the coating layer(s), stability of the coating material, stirring stability of the coating material, settling stability of the coating material, sagging resistance associated with the coating material, leveling properties associated with the coating material, popping resistance associated with the coating material, pinhole resistance associated with the coating material, crater resistance associated with the coating material, mottling resistance associated with the coating material, travel resistance associated with the coating material, color stability associated with the coating material, slumping resistance associated with the coating material, seeding resistance associated with the coating material, hardness associated with the coating layer(s), flexibility associated with the coating layer(s), compatibility of the coating layer(s) with respect to environmental influences, corrosion resistance associated with the coating layer(s), adhesion associated with the coating layer(s), chemical resistance associated with the coating layer(s), roughness associated with the coating layer(s), smoothness associated with the coating layer(s), haptics associated with the coating layer(s), gloss associated with the coating layer(s), color associated with the coating layer(s)and / or texture associated with the coating layer(s). The target coating property data may be provided as described in the context of FIG. 2.

[0134] A data structure associated with candidate input materials may be provided (see block 504). The data structure 206 may provide relationship(s) between use data associated with the use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), active ingredients included in the candidate input materials and property data associated with at least one property of such active ingredients. The data structure 206 may include one or more data model(s) defining candidate input material(s), associated use data, associated composition data, associated composition component data signifying active ingredients within the candidate input materials and associated property data of such active ingredients. The data structure may include a data structure as illustrated in FIG. 3 and FIG. 4 and as described in more detail in the context of FIG. 2.

[0135] Target input material data associated with target input material(s) may be selected from candidate input materials based on the provided target coating property data and data structure (see block 506). The target input material data may be determined by determining preliminary candidate active ingredient data associated with preliminary candidate input material data based on the target property data and matching property data of determined preliminary candidate active ingredient data with property data of further candidate active ingredient(s) included in the provided data structure as described in the context of FIG. 2. This may allow to determine further candidate active ingredient(s) and associated target input material data based on matching chemical structure data and / or functional group data and / or physical property data, e.g. based on guiding structures as described in the context of FIG. 2. Identification of further target input material(s) based on a similarity in chemical structure and / or functional group(s) may allow to expand the choice of suitable target input material(s) without a negative influence on the properties of coating materials and / or coating layer(s) produced from coating material(s) containing such target input material(s). This may allow to improve the flexibility upon developing new coating material(s), either by modifying existing coating materials or by generating new coating materials from scratch, since the number of target input material(s) available to achieve required properties is increased significantly by said approach.

[0136] Determining target input material data may further include refining the preliminary target input material data by matching environmental attribute(s) associated with determined target input material data with environmental attribute(s) included in the provided target property data. The determined target input material data may be refined by comparing environmental attribute(s) included in the provided target property data to environmental attribute(s) associated with the determined target input materials. The provided target property data may define environmental impact thresholds for input material(s) to be used within coating material(s). Such thresholds may be compared to environmental attribute(s) associated with the determined target input material data to determine target input material data associated with environmental attribute(s) below such thresholds.

[0137] The determined target input material data may be provided (see block 508). The target input material data may be provided as described in the context of FIG. 2.

[0138] Property data associated with the determined target input material(s) and included in the data structure may be updated based on the received target property data, this step being generally optional (see block 510). The property data of target input material may be updated within the data structure as described in the context of FIG. 2. Updating use data included in existing data models of the data structure with newly identified property data allows to expand the existing use of candidate input materials, such as existing property data indicating influence(s) of the use of candidate input material(s) in coating materials on coating material properties and / or coating layer properties, with such target properties, hence broadening the use data available for existing candidate input materials. Such expansion allows to develop coating materials more flexibly and efficient. For example, such expansion may allow to identify target input material(s) which may be used to substitute input material(s) present within a given coating material formulation to be adjusted more reliably and efficiently without negatively impacting the properties of the associated coating material and / or coating layer(s) prepared from such coating material. In addition, such expansion allows to identify target input material(s) more reliably and efficiently for preparation of coating materials having a reduced environmental impact without negatively impacting the properties of the coating materials and / or coating layer(s) prepared from such coating material. This may enable production of more sustainable coating material(s) as well as production of more sustainable coated objects.

[0139] FIG. 6 illustrates a block diagram of an example system 614 for adjusting coating material formulation(s), wherein at least one coating property of coating material(s) associated with such adjusted coating material formulation(s) and / or of coating(s) prepared from such coating material(s) match at least one target property in accordance with an embodiment of the present disclosure. The input material(s) may be input material(s) as described in the context of FIG. 2. The coating layer may be a coating layer as described in the context of FIG. 2. The system may be used to implement the methods illustrated in FIG. 7 and FIG. 9.

[0140] As described in the context of FIG. 2, properties may be influenced by the coating material ingredients (e.g. input material(s) used to prepare the coating material present within a coating material of a given coating material type. Properties may be influenced by the coating material ingredients (e.g. input material(s) used to prepare the coating material present, application and / or curing process used to prepare the coating from one or more coating material(s) and / or layer thickness of coating layer(s) and / or the coating. Hence, adjustment of a coating material formulation by exchange of one or more input material(s) included in said formulation and / or by adjustment of amount(s) of such input material(s) may negatively influence properties of coating materials and / or coating layer(s) produced from such coating materials. In addition, adjustment of properties to obtain desired or target properties by exchange of input material(s) and / or adjustment of input material amounts requires careful selection of input material(s) to be exchanged or amounts to be adjusted to ensure that such desired or target properties are achieved.

[0141] The coating material customizer 614 illustrated in FIG. 6 may be configured to determine adjusted coating material formulation data to achieve given target property / ies of coating material(s) and / or coatings produced on surface(s) of an object using such coating material(s). The coatings may include one or more coating layers as described in the context of FIG. 2. The coatings may be produced as described in the context of FIG. 1. The object may include any two- or three-dimensional object. The object may include vehicles. The object may include vehicle bodies and / or vehicle parts.

[0142] With reference to FIG. 7, the coating materials to be adjusted may be produced by a chemical production 704 from one or more production inputs input material(s) 702. The chemical production 704 may be a chemical production network. The chemical production network may include multiple interlinked processing steps. The chemical production network may be an integrated chemical production network with connected or interconnected production chains. The chemical production network may include multiple different production chains that have at least one intermediate product in common. The chemical production network may include multiple stages of the chemical value chain. The chemical production network may include the producing, refining, processing and / or purification of chemical products. The chemical production network may include multiple production chains that produce from one or more input material(s) chemical products that exit the chemical production network. The chemical production network may include multiple tiers of a chemical value chain. The chemical production network may include physically connected or interconnected supply chains and / or production sites. The production sites may be at the same location or at different locations. In the latter case, the production sites may be connected or interconnected by means of dedicated transportation systems such as pipelines, supply chain vehicles, like trucks, ships or other cargo transportation means.

[0143] The chemical production 704 may chemically convert production input(s) 702 via chemical intermediates to one or more input materials(s) that are used to produce coating materials 706 exiting the chemical production 704. The chemical production 704 may produce coating materials 706 by one or more physical processes, such as mixing processes, from one or more input material(s).

[0144] The chemical production network may product the coating materials 706 via multiple production steps. The production steps may be defined by the system boundary 712 of the chemical production network. The system boundary may be defined by location or control over production processes. The system boundary may be defined by the site of the chemical production network. The system boundary may be defined by production processes controlled by one entity or multiple entities jointly. The system boundary may be defined by a value chain with staggered production processes to a coating material, which may be controlled by multiple entities separately. The chemical production network may include a chemical reaction step, a separation step to separate outputs of one process step and further processing steps to convert such outputs to coating materials leaving the system boundary of the chemical production network.

[0145] The coating materials 706 may be produced via one or more process steps from the production input(s) 702 within chemical production 704. The process steps may involve chemical reactions and / or physical processes and / or processes involving coating materials and discrete input materials, such as filling processes. The production input(s) 702 may be used in one or more of such production step(s). The production input(s) 702 may enter the system boundary 712 of the chemical production 704 at the entry point, such as a production plant or a material storage associated with the chemical production 704. The amount of production input(s) 702 entering the system boundary 712 of the chemical production 704 may be measured, for example using sensor(s). Sensors may include sensors configured to measure an amount of production input(s) 702, such as a weight and / or a volume. Chemical and / or physical properties of the production input(s) 702 may be measured, for example using sensor(s), upon passing system boundary 712 of the chemical production 704. The measured data may be used to determine at least one chemical and / or physical property of the respective production input(s) 702.

[0146] An operating system 714 of the chemical production 704 may monitor and / or control the chemical production 704 based on operating parameters of the different processes. The operating system 714 may receive production demand data associated with the production planning for the chemical production 704. The production demand data may be produced from target production capacities for one or more output product(s) produced by the chemical production 704. The production demand data may be produced from pre-defined production capacities or data-driven models that relate production capacities to market demand data or quantities consumed at the consumption location. The production demand data may include target capacities for output products produced by the chemical production 704. The operating system 714 may further receive a bill of materials associated with output products to be produced. The bill of materials may include material data associated with the input materials used to produce the output product, process data associated with the production chain for producing the output product and / or output product data associated with the output product, such as a product specification data or data on the amount of output product to be produced.

[0147] Based on the received production demand data and the bill of materials, material demand data may be determined. The material demand data may include data on the amount of input material required to produce the target capacities of the coating materials 706. The material demand data may include input material identifiers associated with input materials required to produce the coating materials 706 and data on amounts of input material for respective input materials. The material demand data may include one or more material specifier(s) per input material identifier signifying the material specification. The material demand data may include data on the material amount per input material identifier signifying the amount of material to be supplied. The material demand data may specify the production chain(s) of the chemical production 704. The material demand data may include a bill of materials for one or more production chain(s) of the chemical production 704. The material demand data may include one or more recipe(s) specifying one or more material(s) for production process(es) of the chemical production 704. The determined material demand data may be provided for access by a supplier system associated with a supplier outside the physical system boundary of the chemical production 704. Material supply may be triggered by the supplier system accessing the material demand data.

[0148] The amount of coating materials 706 resulting from processes performed within chemical production 704 may be measured using a sensor. The measured data may be stored in one or more databases associated with operating system 714. Moreover processes performed within chemical production 704 may be monitored using sensors and the generated monitoring data may be stored in one or more databases associated with operating system 714. The monitoring data may be interrelated with a digital coating material identifier associated with the respective coating material 706. Physical and / or chemical properties of produced coating materials may be measured by sensors. Physical and / or chemical properties may include the properties previously described. The measured and / or determined chemical and / or physical properties of the produced coating materials may be stored in one or more databases associated with operating system 714. The measured and / or determined chemical and / or physical properties of the coating materials products may be interrelated with a digital coating material identifier associated with the respective coating material.

[0149] The produced coating materials 706 may be provided at one or more exit points of the chemical production 704. The coating materials 706 may exit the system boundary 712 of the chemical production 704. The produced coating material 706 may be provided to a coating material consumer, such as an entity operating a production 728 producing coated objects 732. The entity may be an OEM producing coated end products, such as coated automotive. The entity may be a part producer producing coating parts, such as a coated automotive parts. The production, such as OEM production 724, may produce coated objects, such as coated automotives or parts thereof, from coating materials 706 provided by chemical production 704 and further production inputs 734. The coating process and / or coated objects 732 may be subjected to a quality control. During quality control, properties of the coating material and / or coatings produced on the object may be measured and / or determined from acquired sensor data. For instance, color data and / or texture data of the coated object(s) may be determined. The determined color and / or texture data may be compared to target color and / or texture data. In case the deviation between the determined color and / or texture data and the target color and / or texture data is above a given threshold value, coated object data may be generated and provided to the entity operating chemical production 704. The generated coated object data may include an object identifier and / or coating material identifier(s) of coating material(s) used to produce the coating and incident data. Incident data may include determined coating data for the coated object as well as respective target property data. Provision of coated object data may trigger adjustment of the formulation data associated with the coating material(s) used to produce the coated object to fulfil the provided target properties.

[0150] Returning to FIG. 6 and with continued reference to FIG. 7, coated object data may be received at coating material customizer 614. Coated object data may include data being indicative of the object, coating material identifier(s) and target property data. Data being indicative of the object may include an object identifier, such as a serial number, a part number, a vehicle identification number or a combination thereof. Target property data may include one or more target property / ies of the coating material and / or the coating present on the object. Coating material customizer 614 may be included in the operating system 714 of the chemical production 704. Coating material customizer 614 may be associated with the operating system 714 (not shown). Coating material customizer 614 may include formulation data parser 602. Formulation data parser 602 may be configured to gather formulation data associated with coating material(s) used to prepare the coated object based on received coated object data. Formulation data parser 602 may be configured to parse the received coated object data to determine the object identifier and / or the coating material identifier included in the received coated object data. Based on the determined object identifier and / or coating material data, formulation data parser 602 may be configured to gather formulation data associated with the coating material(s) from database 612 storing formulation data associated with produced coating materials. Formulation data parser 602 may be configured to provide gathered formulation data to input material property & structure characterizer 604. The gathered formulation data may include input material identifiers associated with input materials used to prepare the coating material and amount data associated with such input material identifiers. The formulation data may further include instructions to prepare the associated coating material.

[0151] Input material property & structure characterizer 604 may be configured to determine target input material data associated with one or more target input material(s) selected from available candidate input materials. Input material property & structure characterizer 604 may be configured to determine target input material data using data structure 206 associated with candidate input material(s). The data structure 206 may provide providing relationship(s) between use data associated with the use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), active ingredients included in the candidate input materials and property data associated with at least one property of such active ingredients. Data structure 206 may correspond to data structure 206 described in the context of FIG. 2 to FIG. 4.

[0152] Input material property & structure characterizer 604 may be configured to select from the candidate input materials associated with the data structure 206 one or more target input material(s) based on the provided target property data and the formulation data. Input material property & structure characterizer 604 may be configured to determine from the data structure 206 preliminary candidate input material data by determining matching candidate input materials by matching input material identifier(s) included in the formulation data to candidate input material identifiers included in the data structure and determining candidate active ingredients by matching provided target property data to use data associated with determined matching candidate input materials. Candidate active ingredients may be determined as described in the context of FIG. 2. Target input material data may include input material identifier(s) of input material(s) including active ingredients associated with chemical structure data and / or functional group data matching the chemical structure data and / or functional group data associated with preliminary active ingredients.

[0153] Input material property & structure characterizer 604 may be configured to provide the determined target input material data to formulation generator 608 of coating material customizer 614. Formulation generator 608 may be configured to adjust formulation data of coating materials. Adjustment may include exchanging input material identifier(s) present within the provided formulation data by target input material identifier(s) associated with determined target input material data and / or adjusting amount data present within the formulation data based on amount data associated with the determine target input material data. The formulation data may include input material identifier(s) of input material(s) used to produce the respective coating material and input material amount(s) associated with such input material identifier(s). The formulation data may further include instructions to prepare the respective coating material. Formulation generator 608 may be configured to gather respective formulation data from database 612 based on received coated object data, for example as described in relation to formulation data parser 602 above. Formulation generator 608 may receive formulation data gathered by formulation data parser 602 (not shown in FIG. 6).

[0154] Based on received or gathered formulation data and received target input material data, formulation generator 608 may be configured to adjust the received or gathered formulation data. Adjusting the formulation data may be based on t knowledge sources, such as knowledge graphs, for example as described in S. Sunkle et. al. “Integrated “Generate, Make, and Test” for Formulated Products using Knowledge Graphs”, Data Intelligence 2021 ; 3 (3): 340-375, or graph neural networks for example as described in Reiser, P., Neubert, M., Eberhard, A. et al. Graph neural networks for materials science and chemistry. Commun Mater 3, 93 (2022). Adjustment of the formulation data may include considering constraints, such as value constraints, environmental attribute constraints, production location constraints and / or storage amount(s) of input material(s). Value constraints may be associated with the total costs associated with production of the adjusted coating materials. Such constraints may be stored within the graph structure of the knowledge source to allow consideration of such constrains during formulation data adjustment. Considering such constraints allows to ensure that the adjusted coating material formulation can be produced and provided to the consumer.

[0155] Formulation generator 608 may be configured to refine the target input material data by matching environmental attribute(s) associated with determined target input material data with environmental attribute(s) included in the provided target property data and generating adjusted formulation data based on the refined target input material data and the provided formulation data. The determined target input material data may be refined by comparing environmental attribute(s) included in the provided target property data to environmental attribute(s) associated with the determined target input materials. The provided target property data may define environmental impact thresholds for input material(s) to be used within coating material(s). Such thresholds may be compared to environmental attribute(s) associated with the determined preliminary target input material data to determine target input material data associated with environmental attribute(s) below such thresholds.

[0156] Formulation generator 608 may be configured to provide the adjusted formulation data. With reference to FIG. 8, formulation generator 608 of coating material customizer 614 may be configured to provide the adjusted formulation data to control data generator unit 816. Control data generator 816 may be configured to generate control and / or monitoring data to control a coating material production based on received coated object data associated with a produced coated object 732. Coated object data may be provided via code reader 806. Code reader 806 may be configured to read a physical identifier element, such as a code, a serial number, a VIN, etc., attached to the coated object. The identifier element may encode the serial number or a VIN associated with the coated object. Based on the data provided by code reader 806, coated object data may be generated. Coated object data may be generated by gathering target property data and / or coating material identifier(s) associated with such data provided by code reader 806.

[0157] Control data generator unit 816 may include coating material customizer 614 configured to provide adjusted formulation data. Control data generator unit 816 may further include control data generator 814 configured to generate control and / or monitoring data for controlling and / or monitoring a coating material production. The coating material production may correspond to chemical production 704 illustrated in FIG. 7. The coating material production may correspond to chemical production 704 producing coating material 706 associated with formulation data which has been adjusted by coating material customizer 614. The coating material production may be configured to produce coating material(s) using one or more input material(s) as previously described in the context of FIG. 7. The monitoring and / or control data generated by control data generator 814 may be provided to control data provider 810. Control data provider 810 may be configured to provide the control and / or monitoring data generated by control data generator 814 to coating material production controller 820. Coating material production controller 820 may be configured to control the coating material production, such as chemical production 704 illustrated in FIG. 7. With reference to FIG. 7, the control and / or monitoring data generated by control data generator 814 may be used by coating material production controller 820 to control the coating material production to produce adjusted coating material. The adjusted coating material may be provided to a coating material consumer, such as the entity operating OEM production 724. The adjusted coating material may be provided to the entity having previously received coating material associated with the adjusted coating material (e.g. coating material associated with formulation data which was adjusted by coating material customizer 614 based on coated object data received from the entity).

[0158] By using the data structure providing relationships between use data of candidate input materials, composition data of such candidate input materials, composition component data signifying active ingredients present within the candidate input materials and property data of such active ingredients, target input material(s) suitable to achieve target property / ies of coating materials and / or coating layers produced from such coating materials and required by coating material consumers can be reliably determined. Hence, the data structure may be used identify target input material(s) suitable for adjustment of existing coating material formulations such that the resulting adjusted coating materials and / or coatings prepared from such adjusted coating materials fulfil the target coating property / ies more reliably and efficiently. Such adjustment may be achieved without requiring extensive preparation and testing of candidate coating material formulations, hence allowing to speed up the adjustment process and reducing the environmental impact associated with the coating material development process by avoiding generation of high amounts of waste coating materials and consumption of resources during the development process. Thus, the use of such a data structure may result in a more sustainable adjustment of existing coating materials while ensuring that the adjusted coating materials and coating layers prepared therefrom fulfil predefined requirements, such as customer requirements. The relationships encoded in the data structure allow to identify suitable target input material(s) based on a similarity of chemical structure(s) and / or functional group(s), hence allowing to identify suitable target input material(s) irrespective of known use data associated with the use of such candidate input materials within coating materials. This may enable identification of target input material(s) which are not associated with use data matching provided target property data, hence allowing to broaden the spectrum of suitable target input material(s) usable for adjustment of coating material formulation(s). This may allow more flexible adjustment of existing coating material formulations with respect to available target input material(s). In addition, environmental impact data associated with candidate input material(s) may be considered as a constraint during adjustment of the coating material formulation, hence allowing to ensure that determined target input material(s) fulfil given environmental impact criteria. This may allow to not only consider target property data, but also further required properties, such as the environmental impact associated with the coating materials and / or the coating produced therefrom, during determination of target input material(s), hence allowing development of more sustainable coating materials and coatings produced therefrom.

[0159] FIG. 9 illustrates a flow chart of an example method for adjusting coating material formulation(s), wherein at least one coating property of coating material(s) associated with such adjusted coating material formulation(s) and / or of coating(s) prepared from such coating material(s) match at least one target property in accordance with an embodiment of the present disclosure. The input material(s) may be input material(s) as described in the context of FIG. 2. The coating layer may be a coating layer as described in the context of FIG. 2. The method may be implemented by the systems illustrated in FIG. 6 and FIG. 7.

[0160] Data associated with a coated object including target property data and one or more identifier(s) may be received (see block 902). Target property data may include one or more target property / ies of the coating material and / or the coated object. Target property data may be defined by the entity producing the coated object. The identifier(s) may include coated object identifier(s) associated with the coated object and / or coating material identifier(s) associated with coating materials used to produce the coating on the coated object. With reference to FIG. 6 and FIG. 7, data associated with the coated object (e.g. coated object data) may be generated by the entity producing the coated object and may be provided to the system implementing the method illustrated in FIG. 9, such as coating material customizer 614 illustrated in FIG. 6 and FIG. 7.

[0161] Formulation data associated with coating material used to produce the coating based on received coated object identifier may be provided (see block 904). With reference to FIG. 6, the formulation data may be gathered from database 612 storing formulation data associated with coating materials, such as coating materials produced by chemical production 704. The formulation data may be gathered based on at least one identifier included in the data provided in block 902. With reference to FIG. 6, formulation data parser 602 of coating material customizer 614 may parse the received data to determine identifier(s) and may gather the formulation data from the database based on the determined identifier(s). The formulation data may include input material identifier(s) associated with input material(s) used to produce the respective coating material and amount data associated with amounts of such input material(s).

[0162] A data structure associated with candidate input materials may be provided (see block 906). The data structure 206 may provide relationship(s) relationships between use data of candidate input materials, composition data of such candidate input materials, composition component data signifying active ingredients present within the candidate input materials and property data of such active ingredients. The data structure may include one or more data model(s) defining candidate input material(s), associated use data, associated composition data, associated composition component data signifying active ingredients within the candidate input materials and associated property data of such active ingredients. The data structure may include a data structure as illustrated in FIG. 3 and FIG. 4 and as described in more detail in the context of FIG. 2 and FIG. 6.

[0163] Target input material data associated with target input material(s) may be determined based on the provided formulation data, target property data and the data structure (see block 908). The target input material data may be determined by determining active ingredient data associated with active ingredient(s) included in input material(s) based on the formulation data and the target property data and matching property data included in the determined active ingredient data with property data contained in further active ingredient data included in the data structure. The target input material data may be determined as described in the context of FIG. 6. The active ingredient data may be determined by matching use data associated with input material(s) related to the formulation data with the provided target property data, for example as described in the context of FIG. 6. The input material(s) related to the formulation data may be determined based on input material identifier(s) included in such formulation data. Such input material identifier(s) may be used to query the data structure to determine associated use data. The determined use data may then be compared to the provided target property data to identify candidate input materials associated with coating property data matching the target property data. Active ingredient data associated with such identified input material data and associated property data may be determined using the data structure via respective relationships, as illustrated in FIG. 3 and FIG. 4.

[0164] The determined property data may be matched to property data included in further active ingredient data (e.g. active ingredient data associated with active ingredients contained within candidate input materials not being related to the formulation data and / or active ingredient data associated with active ingredients contained within candidate input materials associated with use data not matching the target property data) to determine target input material data. Chemical structure and / or functional group data included in the property data may be matched. Physical property data included in the property data may be matched. Hence, target active ingredient data may show a similarity in chemical structure and / or functional group data and / or physical property data to the chemical structure and / or functional group data and / or physical property data included in the determined property data. Target input material data associated with determined target active ingredient(s) (e.g. active ingredient(s) associated with active ingredient data matching the active ingredient data of active ingredient(s) contained in input material(s) associated with the formulation data) may be determined using the relationships included in the data structure.

[0165] By matching property data of active ingredients, target active ingredient(s) may be determined based on matching chemical structure data and / or functional group data and / or physical property data, e.g. based on guiding structures as described in the context of FIG. 2. Identification of further input material(s) based on a similarity in chemical structure and / or functional group(s) and / or physical property / ies may allow to expand the choice of suitable target input material(s) without having to rely on a similarity in known coating property / ies associated with the use of candidate input material(s) within coating materials. This may allow to improve the flexibility upon developing new coating material(s), either by modifying existing coating materials or by generating new coating materials from scratch, since the number of target input material(s) available to achieve required properties is increased significantly by said approach.

[0166] Adjusted formulation data may be generated based on the determined target input material data (see block 910). Adjusted formulation data may be generated by modifying the formulation data gathered in block 904 based on the determined target input material data. The adjusted formulation data may be generated as described in the context of FIG. 6.

[0167] By using the data structure providing relationships between use data of candidate input materials, composition data of such candidate input materials, composition component data signifying active ingredients present within the candidate input materials and property data of such active ingredients, target input material(s) suitable to achieve target property / ies of coating materials and / or coating layers produced from such coating materials and required by coating material consumers can be reliably determined. Hence, the data structure may be used identify target input material(s) suitable for adjustment of existing coating material formulations such that the resulting adjusted coating materials and / or coatings prepared from such adjusted coating materials fulfil the target coating property / ies more reliably and efficiently. Such adjustment may be achieved without requiring extensive preparation and testing of candidate coating material formulations, hence allowing to speed up the adjustment process and reducing the environmental impact associated with the coating material development process by avoiding generation of high amounts of waste coating materials and consumption of resources during the development process. Thus, the use of such a data structure may result in a more sustainable adjustment of existing coating materials while ensuring that the adjusted coating materials and coating layers prepared therefrom fulfil predefined requirements, such as customer requirements. The relationships encoded in the data structure allow to identify suitable target input material(s) based on a similarity of chemical structure(s) and / or functional group(s) and / or physical property / ies, hence allowing to identify suitable target input material(s) irrespective of known use data associated with the use of such candidate input materials within coating materials. This may enable identification of target input material(s) which are not associated with use data matching provided target property data, hence allowing to broaden the spectrum of suitable target input material(s) usable for adjustment of coating material formulation(s). This may allow more flexible adjustment of existing coating material formulations with respect to available target input material(s). In addition, environmental impact data associated with candidate input material(s) may be considered as a constraint during adjustment of the coating material formulation, hence allowing to ensure that determined target input material(s) fulfil given environmental impact criteria. This may allow to not only consider target property data, but also further required properties, such as the environmental impact associated with the coating materials and / or the coating produced therefrom, during determination of target input material(s), hence allowing development of more sustainable coating materials and coatings produced therefrom. FIG. 10 illustrates a block diagram of an example system for generating coating material formulation(s), wherein at least one property of coating material(s) produced from such generated coating material formulation(s) and / or of coating(s) prepared from such produced coating material(s) match at least one target property in accordance with an embodiment of the present disclosure. The input material(s) may be input material(s) as described in the context of FIG. 2. The coating layer may be a coating layer as described in the context of FIG. 2. The system may be used to implement the methods illustrated in FIG. 11.

[0168] As described in the context of FIG. 2, properties may be influenced by the coating material ingredients (e.g. input material(s) used to prepare the coating material) present within a coating material of a given coating material type. Properties may be influenced by the coating material ingredients present within a coating material, application and / or curing process used to prepare the coating from one or more coating material(s) and / or layer thickness of coating layer(s) and / or the coating. Hence, obtaining desired or target properties requires careful selection of input material(s) to ensure that such desired or target properties are achieved.

[0169] Coating material determinator 1012 illustrated in FIG. 10 may be configured to determine coating material formulations to achieve given target property / ies of coatings produced on surface(s) of an object using such coating materials. The coatings may include one or more coating layers as described in the context of FIG. 2. The coatings may be produced as described in the context of FIG. 1. The object may be an object as described in the context of FIG. 6.

[0170] With reference to FIG. 11 , target data associated with a target coating, a target coating process and target property data may be received. Target data may be received at coating material determinator 1012. Target data may include target coating property data, target coating process data, target coating data and target coating material type data. Target data may be provided by a user using coating material determinator 1012 to generate or create new coating material formulation(s) during the development phase (see FIG. 1).

[0171] Coating material determinator 1012 may include input material determinator 1004. With continued reference to FIG. 11 , input material determinator 1004 may be configured to determine target input material data associated with one or more target input material(s) selected from available candidate input materials. Input material determinator 1004 may be configured to determine target input material data using data structure 206 associated with candidate input material(s). The data structure 206 may provide providing relationship(s) between use data of candidate input materials, composition data of candidate input materials, composition component data signifying active ingredients within the candidate input materials and property data of such active ingredients. Data structure 206 may correspond to data structure 206 described in the context of FIG. 2 to FIG. 4. Input material determinator 1004 may be configured to determine target input material data associated with one or more target input material(s) selected from available candidate input materials based on the provided target data and the data structure. Input material determinator 1004 may be configured to match use data included in the provided data structure to target data to determine target input material(s). Input material determinator 1004 may be configured to determine property data associated with preliminary candidate active ingredient(s) included in the preliminary candidate input material(s). Input material determinator 1004 may be configured to match property data associated with preliminary candidate active ingredient(s) to property data of further candidate active ingredients included in the data structure to identify further target input material(s). This may allow to identify further target input material(s) based on a similarity in property data instead of a similarity in use data. Input material determinator 1004 may be configured to provide the target input material data (e.g. target input material data and further target input material data) to formulation generator 1006.

[0172] With continued reference to FIG. 11 , formulation generator 1006 may be configured to generate formulation data associated with coating materials. Depending on the provided target input material(s), formulation generator 1006 may be configured to generate one or more formulation data set(s). Formulation generator 1006 may be configured to generate a formulation data set per coating material formulation. Generation of the formulation data may be based on knowledge sources graph neural networks as previously described. Generation of formulation data may include considering constraints, such as environmental attribute constraint(s), value constraints, production location constraints and / or storage amount(s) of input material(s). Value constraints may be associated with the total costs associated with production of the adjusted coating materials. Such constraints may be stored on within the graph structure of the knowledge source to allow consideration of such constrains during performing the formulation data adjustment. Considering such constraints allows to ensure that the generated coating material formulation can be produced and provided to the consumer. Considering environmental attribute(s) may allow to ensure that coating materials associated with generated coating material formulations fulfil given environmental attribute requirements.

[0173] Formulation generator 1006 may be configured to provide the generated formulation data. Providing the generated formulation data may include providing the generated formulation data for display. Providing the generated formulation data may include providing the generated formulation data to a control data generator unit configured to generate control and / or monitoring data for controlling production of coating material(s), for example as described in the context of FIG. 8.

[0174] By using the data structure, target input material(s) suitable to achieve target property data can be reliably determined, hence allowing to generate new coating material formulations such that coating materials and / or coatings prepared from such adjusted coating materials under target coating process conditions fulfil the target property / ies. Such generation may be achieved without requiring extensive preparation and testing of candidate coating material formulations, hence allowing to speed up the generation process and reducing the environmental impact associated with the coating material development process by avoiding generation of high amounts of waste coating materials and consumption of resources during the development process. Thus, the use of such a data structure may result in a more sustainable generation of new coating materials while ensuring that the coating materials and coating layers prepared therefrom fulfil predefined requirements, such as customer requirements. In addition, environmental impact data associated with candidate input material(s) may be considered as a constraint during generation of new coating material formulations, hence allowing to ensure that determined target input material(s) fulfil given environmental impact criteria. This may allow to not only consider target property data, but also further required properties, such as the environmental impact associated with the coating materials and / or the coating produced therefrom, during determination of target input material(s), hence allowing development of more sustainable coating materials and coatings produced therefrom.

[0175] FIG. 12 illustrates a system and associated methods for determining property data of coating layer(s) prepared from coating material(s) based on received coating process data associated with a coating process to prepare such coating layer(s) from the coating material(s) in accordance with an embodiment of the present disclosure. The coating layer may be a coating layer as described in the context of FIG. 2. The system may be used to implement the methods illustrated in FIG. 13.

[0176] As described in the context of FIG. 2, properties may be influenced by the coating material ingredients (e.g. input material(s) used to prepare the coating material) present within a coating material of a given coating material type. Properties may be influenced by the coating material ingredients (e.g. input material(s) used to prepare the coating material) present within a coating material, application and / or curing process used to prepare the coating from one or more coating material(s) and / or layer thickness of coating layer(s) and / or the coating. Hence, coating properties of coatings prepared from one or more coating material(s) may be determined based on the aforementioned data.

[0177] Coating property determinator 1202 illustrated in FIG. 12 may be configured to determine coating property / ies of coatings prepared by applying one or more coating material(s) to at least a part of the surface of an object. The coatings may include one or more coating layers as described in the context of FIG. 2. The coatings may be produced as described in the context of FIG. 1. The object may be an automotive or a part thereof.

[0178] Coating materials 706 may be produced from one or more input materials 702 by a chemical production 704, for example as described in the context of FIG. 7. Chemical production 704 may be a chemical production network as described in the context of FIG. 7. Chemical production 704 may be monitored and / or controlled by operating system 714 as described in the context of FIG. 7. The produced coating materials 706 may be provided to a consumer, such as an entity operating a production producing coated objects. The production may be OEM production 724. The provided coating material(s) may be applied within OEM production 724 by application equipment 1206. Application equipment may include application robot(s) configured to apply liquid or solid coating material to the surface of an object. The application equipment may include sensor(s) configured to gather application data prior to, during and / or after application of a coating material to an object. The gathered application data may include object identifier(s), shaping air value(s), flow rate, bell speed, high voltage, distance to object, distance to track, traction speed, equipment data, such as equipment type, equipment manufacturer, equipment identifier, etc..

[0179] The applied coating material(s) may be dried and / or cured to form the coating on the object. Drying and / or curing may be effected using curing equipment 1208. Drying and / or curing may be effected by heat and / or irradiation, such as IR and / or UV irradiation. The curing equipment 1208 may include sensor(s) configured to gather curing data prior to, during and / or after application of a coating material to an object. The curing data may include object identifier(s), curing time, curing temperature, humidity, energy, traction speed, light source data and / or equipment data.

[0180] The application and / or curing data gathered by the sensor(s) may be collected and stored in on or more databases associated with OEM production 724 (not shown). The operating system of OEM production 724 may be configured to generate coating process data associated with a coated object by gathering application and / or curing data from such database. The application and / or curing data may be gathered based on provided object identifier(s) associated with the coated object. The coating process data may include application and / or curing data and identifier(s). The identifier(s) may include object identifier(s) and / or coating material identifier(s). With reference to FIG. 13, the coating process data may be provided to coating property determinator 1202.

[0181] Coating property determinator 1202 may be configured to parse the received coating process data to determine the identifier(s). With continued reference to FIG. 13, coating property determinator 1202 may be configured to gather formulation data associated with coating material(s) used to prepare the coating on the coated object based on the determined identifier(s) from database 612, for example as described in the context of FIG. 6.

[0182] With continued reference to FIG. 13, coating property determinator 1202 may be configured to determine coating property data associated with the coating present on the coated object using data structure 206 associated with candidate input material(s). The data structure 206 may provide providing relationship(s) between use data of input materials, composition data of input materials, composition component data signifying active ingredients within the input materials and property data of such active ingredients. Data structure 206 may correspond to data structure 206 described in the context of FIG. 2 to FIG. 4.

[0183] Coating property determinator 1202 may be configured to determine input material(s) signified by the formulation data based on input material identifier(s) included in the formulation data. For instance, coating property determinator 1202 may match input material identifier(s) included in the formulation data to input material identifier(s) 430 included in the data structure. Coating property determinator 1202 may further be configured to generate coating property data associated with the determined input material(s) from the data structure based on the coating process data. For instance, coating property determinator 1202 may match coating process data to coating process data associated with determined input material(s) to determine associated coating property data.

[0184] With continued reference to FIG. 13, coating property determinator 1202 may be configured to provide the generated coating property data. Providing may include providing the determined coating property data for display. Providing may include providing the determined coating property data to a database for storage.

[0185] By using the data structure including property data of input materials and associated coating process data, coating property / ies of produced coatings may be determined based on coating process data. This allows to determine coating property / ies of produced coatings quickly and reliably on objects without having to determine such properties via sensor(s).

[0186] FIG. 14 shows a computing device 1400 that can be used to implement any aspect of the mechanisms set forth in the above-described figures. For instance, with reference to FIG. 2 and FIG. 5 to FIG. 13, the type of computing device 1400 shown in FIG. 14 can be used to implement any computing device associated with the input material determinator 208, coating material customizer 614, coating material determinator 1012, coating property determinator 1202 etc. In all cases, the computing device 1400 represents a physical and tangible processing mechanism.

[0187] The computing device 1400 can include one or more hardware processors 1402. The hardware processor(s) can include, without limitation, one or more Central Processing Units (CPUs), and / or one or more Graphics Processing Units (GPUs), and / or one or more Application Specific Integrated Circuits (ASICs), etc. More generally, any hardware processor can correspond to a general-purpose processing unit or an application-specific processor unit.

[0188] The computing device 1400 can also include computer-readable storage media 1416, corresponding to one or more computer-readable media hardware units. The computer-readable storage media 1416 retains any kind of information 1418, such as machine-readable instructions, settings, data, etc. Without limitation, for instance, the computer-readable storage media 1416 may include one or more solid-state devices, one or more magnetic hard disks, one or more optical disks, magnetic tape, and so on. Any instance of the computer-readable storage media 1416 can use any technology for storing and retrieving information. Further, any instance of the computer-readable storage media 1416 may represent a fixed or removable component of the computing device 1400. Further, any instance of the computer-readable storage media 1416 may provide volatile or non-volatile retention of information. The computing device 1400 can utilize any instance of the computer-readable storage media 1416 in different ways. For example, any instance of the computer-readable storage media 1416 may represent a hardware memory unit (such as Random Access Memory (RAM)) for storing transient information during execution of a program by the computing device 1400, and / or a hardware storage unit (such as a hard disk) for retaining / archiving information on a more permanent basis. In the latter case, the computing device 1400 also includes one or more drive mechanisms 1410 (such as a hard drive mechanism) for storing and retrieving information from an instance of the computer-readable storage media 1416.

[0189] The computing device 1400 may perform any of the functions described above when the hardware processor(s) 1402 carry out computer-readable instructions stored in any instance of the computer- readable storage media 1416. For instance, the computing device 1400 may carry out computer-readable instructions to perform each step of the methods outlined in the above figures.

[0190] Alternatively, or in addition, the computing device 1400 may rely on one or more other hardware logic components 1404 to perform operations using a task-specific collection of logic gates. For instance, the hardware logic component(s) 1404 may include a fixed configuration of hardware logic gates, e.g., that are created and set at the time of manufacture, and thereafter unalterable. Alternatively, or in addition, the other hardware logic component(s) 1404 may include a collection of programmable hardware logic gates that can be set to perform different application-specific tasks. The latter category of devices includes, but is not limited to Programmable Array Logic Devices (PALs), Generic Array Logic Devices (GALs), Complex Programmable Logic Devices (CPLDs), Field-Programmable Gate Arrays (FPGAs), etc. The term “logic” likewise encompasses various physical and tangible mechanisms for performing a task. For instance, each processing-related operation illustrated in the flowcharts corresponds to a logic component for performing that operation. A logic component can perform its operation using the hardware logic circuitry as described in relation to FIG. 14. When implemented by computing equipment, a logic component represents an electrical component that is a physical part of the computing system, in whatever manner implemented.

[0191] FIG. 14 generally indicates that hardware logic circuitry 1434 includes any combination of the hardware processor(s) 1402, the computer-readable storage media 1416, and / or the other hardware logic component(s) 1410. That is, the computing device 1400 can employ any combination of the hardware processor(s) 1402 that execute machine-readable instructions provided in the computer-readable storage media 1416, and / or one or more other hardware logic component(s) 1410 that perform operations using a fixed and / or programmable collection of hardware logic gates. More generally stated, the hardware logic circuitry 1434 corresponds to one or more hardware logic components of any type(s) that perform operations based on logic stored in and / or otherwise embodied in the hardware logic component(s).

[0192] In some cases, the computing device 1400 may also include an input / output interface 1422 for receiving various inputs (via input devices 1420), and for providing various outputs (via output devices 1412). Illustrative input devices include a keyboard device, a mouse input device, a touchscreen input device, a digitizing pad, one or more static image cameras, one or more video cameras, one or more depth camera systems, one or more microphones, a voice recognition mechanism, any movement detection mechanisms (e.g., accelerometers, gyroscopes, etc.), and so on. One particular output mechanism may include a display device 1412 and an associated graphical user interface presentation (GUI) 1414. The display device 1412 may correspond to a liquid crystal display device, a light-emitting diode display (LED) device, a cathode ray tube device, a projection mechanism, etc. Other output devices include a printer, one or more speakers, a haptic output mechanism, an archival mechanism (for storing output information), and so on. The computing device 1400 can also include one or more network interfaces 1408 for exchanging data with other devices via one or more communication conduits 1406. One or more communication buses 1432 communicatively couple the above-described components together.

[0193] The communication conduit(s) 1406 can be implemented in any manner, e.g., by a local area computer network, a wide area computer network (e.g., the Internet), point-to-point connections, etc., or any combination thereof. The communication conduit(s) 1026 can include any combination of hardwired links, wireless links, routers, gateway functionality, name servers, etc., governed by any protocol or combination of protocols.

[0194] FIG. 14 shows the computing device 1400 as being composed of a discrete collection of separate units. In some cases, the collection of units may correspond to discrete hardware units provided in a computing device chassis having any form factor. FIG. 14 shows illustrative form factors in its bottom portion. In other cases, the computing device 1400 can include a hardware logic component that integrates the functions of two or more of the units shown in FIG. 2, FIG. 6, FIG. 8, FIG. 10 and FIG. 12. For instance, the computing device 1400 can include a system on a chip (SoC or SOC), corresponding to an integrated circuit that combines the functions of two or more of the units shown in FIG. 14.

[0195] FIG. 15 illustrates a schematic drawing of a client server setup that may be used to implement any aspect of the mechanisms set forth in the above-described figures. The client device may be a computer or a program that, as part of its operation, relies on sending a request to another program or a computer hardware or software that accesses a service made available by a server. The server may or may not be located on another computer.

[0196] The system may comprise a server 1502 which may be accessed via a network 1504, such as the Internet, by one or more clients 1506.1 to 15O6.n. The server may be an HTTP server and may be accessed via conventional Internet web-based technology. The server 1502 may be configured to perform the methods described in FIG. 5, FIG. 9, FIG. 11 or FIG. 13. The clients 1506 may be computer terminals accessible by a user and may be customized devices, such as data entry kiosks, or general-purpose devices, such as a personal computer. The clients 1506 may be configured to provide input necessary to perform the methods described in the context of FIG. 5, FIG. 9, FIG. 11 or FIG. 13. The clients 1506 may comprise a screen and may be used to display the determined permittivity of the pigmented coating layer. The clients 1506 may comprise a screen and may be used to display the determined input material data, adjusted coating formulation data, generated coating formulation data and / or generated coating property data. A printer 1508 may be connected to a client 1506. The internet-based system may be useful, if a service is provided to customers or in a larger company setup.

[0197] The present disclosure has been described in conjunction with preferred embodiments and examples as well. However, other variations can be understood and effected by those persons skilled in the art and practicing the claimed invention, from the studies of the drawings, this disclosure and the claims.

[0198] Any steps presented herein can be performed in any order. The methods disclosed herein are not limited to a specific order of these steps. It is also not required that the different steps are performed at a certain place or in a certain computing node of a distributed system, i.e. each of the steps may be performed at different computing nodes using different equipment / data processing.

[0199] As used herein ..determining" also includes ..initiating or causing to determine", “generating" also includes ..initiating and / or causing to generate" and “providing” also includes “initiating or causing to determine, generate, select, send and / or receive”. “Initiating or causing to perform an action” includes any processing signal that triggers a computing node or device to perform the respective action.

[0200] In the claims as well as in the description the word “comprising” does not exclude other elements or steps and the indefinite article “a” or “an” does not exclude a plurality. A single element or other unit may fulfill the functions of several entities or items recited in the claims. The mere fact that certain measures are recited in the mutual different dependent claims does not indicate that a combination of these measures cannot be used in an advantageous implementation.

Claims

CLAIMS1. A computer-implemented method for determining input material(s) used to prepare coating materials, wherein at least one property of the coating materials and / or of coating layer(s) prepared from such coating materials match at least one target property, the method comprising:• providing target coating property data associated with the at least one target property,• providing a data structure associated with candidate input materials, wherein the data structure provides relationship(s) between- use data associated with a use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s),- active ingredients included in the candidate input materials and- property data associated with at least one property of such active ingredients,• determining target input material data associated with target input material(s) by determining from the data structure candidate active ingredient(s) based on the target property data and matching property data of the determined candidate active ingredient(s) with property data of further active ingredient(s) included in the provided data structure,• providing the determined target input material data associated with the target input material(s).

2. The method of claim 1 , wherein the input material consists of a single chemical compound or includes at least two different chemical compounds.

3. The method of claim 1 or 2, wherein the active ingredient is associated with or related to the use data associated with the respective candidate input material including the active ingredient.

4. The method of any one of claims 1 to 3, wherein the target property data includes at least one target property associated with input material(s) to be included in the coating material, the coating material and / or coating layer(s) produced from the coating material.

5. The method of any one of claims 1 to 4, wherein the target coating property is selected from at least one chemical and / or physical property associated with the input material(s), environmental attribute(s) associated with input material(s), the coating material and / or the coating layer(s), viscosity associated with the coating material, sagging resistance associated with the coating material, leveling properties associated with the coating material, stability associated with the coating material, stirring stability associated with the coating material, settling stability associated with the coating material, popping resistance associated with the coating material, pinhole resistance associated with the coating material, crater resistance associated with the coating material, mottling resistance associated with the coating material, travel resistance associatedwith the coating material, color stability associated with the coating material, slumping resistance associated with the coating material, seeding resistance associated with the coating material, hardness associated with the coating layer(s), flexibility associated with the coating layer(s), compatibility of the coating layer(s) with respect to environmental influences, corrosion resistance associated with the coating layer(s), adhesion associated with the coating layer(s), chemical resistance associated with the coating layer(s), roughness associated with the coating layer(s), smoothness associated with the coating layer(s), haptics associated with the coating layer(s), gloss associated with the coating layer(s), color associated with the coating layer(s)and / or texture associated with the coating layer(s).

6. The method of any one of claims 1 to 4, wherein the data structure defines a plurality of data models per candidate input material and defines relationships between the plurality of data models.

7. The method of claim 6, wherein the data models include a data model defining use data associated with the candidate input materials, a data model defining composition data associated with the candidate input materials, a data model defining active ingredient(s) within the candidate input materials and / or a data model defining property data associated with such active ingredients.

8. The method of any one of claims 1 to 7, wherein the candidate active ingredients are determined based on the provided target property data by matching use data associated with candidate input materials with the provided target property data and determining active ingredients associated with matching use data.

9. The method of any one of claims 1 to 8, wherein the target input material data associated with target input material(s) is determined by matching chemical property data and / or physical property data included in data model(s) defining property data of determined candidate active ingredient(s) with chemical property data and / or physical property data included in data model(s) defining property data associated with further active ingredients.

10. The method of claim 9, wherein the chemical property data defines chemical structure data and / or functional group data.11 . The method of any one of claims 1 to 10, further including a step of updating use data associated with the target input material(s) with at least a part of the target property data, wherein updating the use data includes updating the use data included in the data structure and being associated with the candidate input material(s) corresponding to the target input material(s).

12. An apparatus for determining input material(s) used to prepare coating materials, wherein at least one coating property of the coating materials and / or of coating layer(s) prepared from such coating materials have at least one target property, the apparatus comprising:• a data providing interface configured to provide target property data associated with the at least one target property and configured to provide a data structure associated with candidate input materials, wherein the data structure provides relationship(s) between use data associated with a use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), active ingredients included in the candidate input materials and property data associated with at least one property of such active ingredients,• a target input material determination unit configured to determine target input material data associated with target input material(s) by determining from the data structure candidate active ingredient(s) based on the target property data and matching property data of the determined candidate active ingredient(s) with property data of further active ingredient(s) included in the provided data structure,• a data providing interface configured to provide the determined target input material data associated with the target input material(s).

13. Use of a data structure as updated according to the method claimed in claim 11 for adjusting coating material formulation(s) and / or for generating new coating material formulation(s), wherein at least one property of coating material(s) associated with such coating material formulation(s) and / or coating layer(s) prepared from such coating material(s) match at least one target property.

14. A method for adjusting coating material formulation(s), wherein at least one coating property of coating material(s) associated with such adjusted coating material formulation(s) and / or of coating(s) prepared from such coating material(s) match at least one target property, the method comprising:• receiving data associated with a coated object including target property data associated with the at least one target property and identifier(s) associated with the coated object and / or coating material(s) used to produce a coating on the coated object,• providing formulation data associated with the coating material(s) used to produce the coating on the coated object based on at least one received identifier,• providing a data structure associated with candidate input materials, wherein the data structure provides relationship(s) between use data associated with a use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), active ingredients included in the candidate input materials and property data associated with at least one property of such active ingredients,• determining target input material data associated with target input material(s) by determining from the data structure candidate active ingredient(s) based on the formulation data and target property data, and matching property data associated with the determined candidate active ingredient(s) to property data of further active ingredient(s) included in the provided data structure,• generating adjusted formulation data based on determined target input material data and the provided formulation data,• providing the adjusted formulation data.

15. An apparatus for adjusting coating material formulation(s) associated with coating material(s), wherein the adjusted coating material(s) and / or coating(s) prepared from such adjusted coating materials match at least one given target coating property, the apparatus comprising:• a data receiving interface configured to receive data associated with a coated object including target property data associated with the at least one target property and identifier(s) associated with the coated object and / or coating material(s) used to prepare a coating on the coated object,• a data providing interface configured to provide formulation data associated with the coating material(s) used to produce the coating on the coated object based on at least one received identifier and configured to provide a data structure associated with candidate input materials, wherein the data structure provides relationship(s) between use data associated with a use of candidate input materials in coating materials and resulting influence(s) of such use on at least one property of the coating materials and / or the coating layer(s), active ingredients included in the candidate input materials and property data associated with at least one property of such active ingredients,• a target input material determination unit configured to determine target input material data associated with target input material(s) by determining from the data structure candidate active ingredient(s) based on the formulation data and the target property data, and matching property data associated with the determined candidate active ingredient(s) to property data of further active ingredient(s) included in the provided data structure,• a formulation generator configured to generate adjusted formulation data based on determined target input material data and the provided formulation data,• a data providing interface configured to provide the adjusted formulation data.

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