Method for providing optimized process parameters relating to a production process for producing a sheet of building material

Abstract

The disclosure relates, inter alia, to a method that is carried out for example by at least one device or a system comprising at least two devices. The method comprises receiving information about at least one production factor relating to a production process for producing a sheet of building material. The method also comprises determining, based on the information about the at least one production factor and using an optimization function, at least one optimized first process parameter. The at least one optimized first process parameter is based on respective values for at least one first process parameter relating to the production process that optimize the optimization function, or corresponds to said values. Furthermore, each of the at least one first process parameter relating to the production process is related to at least one of the at least one production factor relating to the production process. The method also comprises determining, using a mathematical model, respective values for at least one second process parameter relating to the production process in such a way that, when the production process is carried out based on the at least one optimized first process parameter and on the values for the at least one second process parameter, at least one constraint related to the sheet of building material is satisfied. Furthermore, the method comprises providing the at least one optimized first process parameter and the values for the at least one second process parameter for use in the production process.

Description

[0001] Method for providing optimized process parameters of a production process for manufacturing a building material panel

[0002] Area

[0003] Exemplary embodiments of the invention relate to methods, devices, systems and computer programs, in particular for providing optimized process parameters of a production method for manufacturing a building material panel.

[0004] background

[0005] The continuous production of material and / or building material panels, such as wood-based panels, typically involves the use of complex production systems comprising a plurality of units or sections dedicated to specific production steps. For each such unit, a – usually large – number of process parameters can characterize the respective process conditions. For example, in the case of fiberboard production, the process parameters such as the amount of squeeze water, the amount of wood chips, the temperature of the digester, etc., can be characteristic of the process conditions of a fiberization process section of a production system for manufacturing wood-based panels.

[0006] Given the typically very large number of process parameters in production processes for manufacturing building panels – and the associated high complexity of controlling or regulating such processes – the use of methods for at least partially autonomous control or regulation of these production processes has proven advantageous compared to (exclusively) manual control or regulation. Such autonomous control / regulation methods can, for example, based on the current situation in a production plant for manufacturing building panels, automatically determine new setpoint specifications for process parameters of a corresponding production process and then adjust them automatically. This type of autonomous control or regulation can also be referred to as a higher-level closed-loop control.

[0007] Both with (exclusively) manual and at least partially autonomous control / regulation of the aforementioned production processes, certain requirements must usually be met. For example, in the production of building material panels, certain specified quality criteria must be met. Furthermore, achieving specified optimization goals, such as increasing production speed or reducing material and / or energy consumption, is often desirable. Furthermore, limitations of the control or regulation due to (machine) technology and / or user-specified limitations may need to be taken into account.

[0008] Particularly - but not only - in the case of at least partially autonomous control or regulation of production processes for the manufacture of building material panels (for example in the form of a higher-level closed control loop), the determination of the best possible process parameters with regard to several or all of the aforementioned requirements represents a challenge in view of the large number of process parameters.

[0009] Against this background, one object of the present invention is to provide methods, devices, systems, and computer programs, in particular for providing optimized process parameters of a production process for manufacturing a building material panel. A further object of the present invention is to provide methods, devices, systems, and computer programs that support the control and / or regulation of a production plant for manufacturing building material panels. Summary of some exemplary embodiments of the invention

[0010] According to an exemplary aspect of the invention, a method is disclosed which is carried out, for example, by at least one device or a system comprising at least two devices, the method comprising:

[0011] Obtaining information on at least one production factor of a production process for producing a building material panel;

[0012] Determining, based on the information about the at least one production factor and using an optimization function, at least one optimized first process parameter, wherein the at least one optimized first process parameter is based on or corresponds to respective values ​​for at least one first process parameter of the production process that optimize the optimization function, and wherein each of the at least one first process parameter of the production process is related to at least one of the at least one production factor of the production process;

[0013] Determining, using a mathematical model, respective values ​​for at least one second process parameter of the production process such that, when the production process is carried out based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter, at least one constraint associated with the building material panel is met; and

[0014] Providing the at least one optimized first process parameter and the values ​​for the at least one second process parameter for use in the production process.

[0015] According to this aspect of the invention, the following are further disclosed:

[0016] A computer program comprising program instructions that cause one or more processors to execute and / or control the method according to the stated aspect of the invention when the computer program is executed on the processor or the multiple processors. In this specification, a processor is understood to mean, among other things, control units, microprocessors, microcontrol units such as microcontrollers, digital signal processors (DSPs), application-specific integrated circuits (ASICs), or field-programmable gate arrays (FPGAs). Either all steps of the method can be controlled, or all steps of the method can be executed, or one or more steps can be controlled and one or more steps can be executed. The computer program can be at least partially software and / or firmware of a processor. It can equally be implemented at least partially as hardware.The computer program can, for example, be stored on a computer-readable storage medium, e.g., a magnetic, electrical, optical, and / or other storage medium. The storage medium can, for example, be part of the processor, such as a (non-volatile or volatile) program memory of the processor or a part thereof. The storage medium can, for example, be a tangible or physical storage medium.

[0017] A device or a system comprising at least two devices, configured to execute and / or control the method according to the stated aspect of the invention or comprising respective means for executing and / or controlling the steps of the method according to the stated aspect of the invention. In this case, either all steps of the method can be controlled, or all steps of the method can be executed, or one or more steps can be controlled and one or more steps can be executed. One or more of the means can also be executed and / or controlled by the same unit. For example, one or more of the means can be formed by one or more processors.A device according to the said aspect of the invention can, for example, be a control device which is connected to (at least to parts of) a production plant for producing building material panels, in particular for controlling at least parts of a production process for producing building material panels.

[0018] A device comprising at least one processor and at least one memory containing program code, wherein the memory and the program code are configured to cause a device with the at least one processor to execute and / or control at least the method according to the aforementioned aspect of the invention. In this case, either all steps of the method can be controlled, or all steps of the method can be executed, or one or more steps can be controlled and one or more steps can be executed.

[0019] A building material panel produced by a method comprising the method according to said aspect of the invention.

[0020] In the following, properties of the mentioned aspect are described - partly by way of example.

[0021] The method according to the mentioned aspect is carried out, for example, by at least one device or a system comprising at least two devices. In exemplary embodiments, the method is carried out by at least one control device that is connected (directly and / or indirectly) to a production plant for manufacturing building material panels. In an exemplary embodiment, the method can be carried out by a system that comprises, for example, multiple control devices, wherein each of the control devices executes (some or all) steps of the method.For example, a control device may comprise a processing plant such as one (or more) computers that are (or are) provided at the production plant (and can receive, for example, sensor data and / or data from one or more measuring devices of the production plant via wired and / or wireless communication connections) and / or a mobile device, such as a tablet computer, a smartphone, or the like, that is configured to carry out at least parts of the method and that is connected, for example, via a wired and / or wireless communication connection to the processing plant and / or the production plant. As further described in the present disclosure, the method according to the said aspect, in exemplary embodiments, is a method for determining and / or providing optimized process parameters of a production method for manufacturing a building material panel.

[0022] The method according to the said aspect comprises a step of obtaining information on at least one production factor of a production process for producing a building material panel.

[0023] The manufacture (or production) of building material panels – which are sometimes simply referred to as "material panels" in technical circles – takes place either in a cyclical or continuous manner. In cyclical production, the building material panels are produced as flat objects with finite dimensions in all three spatial directions, whereas the building material panels produced in a continuous process are cut to length from a web material with finite dimensions in only two spatial directions. The mode of operation of the joining and / or compaction unit determines whether the overall process is described as a cyclical or continuous process, since in the case of a so-called cyclical production method, the process stages upstream of compaction, such as scattering, are often also designed as continuous sub-processes.Since the compaction units, or rather the combined joining and compaction units, generally operate with significant pressures during the production of building material panels, these units are usually referred to by those skilled in the art as a "press section" with reference to the entire system. When producing building material panels within the meaning of the present disclosure, the working pressures here are usually in the range of approximately 50 N / cm, depending on the material and size of the material panel to be produced. 2 and approx. 500 N / cm 2 , and there advantageously between 100 N / cm 2 and 400 N / cm 2 , although in the area of ​​production of building material panels used for insulation, so-called insulation boards, at very low densities they can be less than 50 N / cm 2 may fail.

[0024] Building material boards that have at least one layer containing a natural fiber component occupy a special position among building material boards, both from an economic perspective and with regard to their technical usability. For the purposes of the present disclosure, natural fibers or fiber components are understood to mean fibers or fiber components that have a natural origin, i.e., originate from an annual or perennial plant, regardless of whether the fibers or fiber components are present as pure fibers, for example, for the production of MDF / HDF boards or their layer types, or form components of chips, long chips, or wafers, which are traditionally used for the production of particleboard or OSB boards or their layer types. The term "wood particles," also used below, therefore always includes at least natural fibers or fiber components.

[0025] Such building boards are often simply referred to by experts as "wood building boards," even if they contain one or more layers that are not based on a raw material obtained from a perennial plant. Even building boards that only comprise one or more layers that consist at least partially of fibers and / or fiber components obtained from annual plants are usually referred to as wood building boards and only very rarely are they correctly referred to as "bast building boards" or "grass building boards."

[0026] Such wood building boards are manufactured in a wide variety of designs for different applications. Particularly widespread are particle boards, OSB (oriented strand board), MDF (medium-density fiberboard), and HDF (high-density fiberboard), as well as hybrid boards constructed from individual layers of such composites. The name of the building boards depends on the shape and size of the fibers or particles used to construct the board or layer. Experts refer to a particle board when it is made from "fine" wood particles, while they refer to an OSB board when it is made from "coarse" wood particles. Experts generally understand "fine" wood particles to be particles whose maximum dimension in one spatial direction does not exceed 60 mm; these particles, described as chips, are usually even formed with a maximum dimension of 25 mm or even 20 mm.The expert generally understands “coarse” wood particles to be particles whose maximum extension in one spatial direction is at least 60 mm; these particles, described as long chips, are usually even formed with a maximum extension of 60 mm to 185 mm, in particular of 80 mm to 140 mm.

[0027] MDF and HDF boards, or their individual layers, are made of (medium-density or high-density pressed) fibers, which are usually obtained from the raw material via a chemical process, usually a type of cooking process.

[0028] Hybrid panels consist of several layers of different types and are often particularly suitable when the material panel has to meet different requirements for its intended use.

[0029] Such building boards are still referred to as wood-based building boards even if they contain individual layers that do not contain any natural fibers and / or fiber components. These are usually laminated building boards, i.e., wood-based building boards that are laminated on one or both sides. Plastics are typically used for the lamination. Coated particle boards are particularly well-known.

[0030] The types and types of wood building boards mentioned are therefore made from wood particles (chips, long chips or fibers) of different shapes and sizes, whereby the wood particles are bonded by stimulating their own adhesion mechanisms and adding adhesives (usually a glue) in the so-called press section of a building board production plant under the influence of pressure and temperature.

[0031] Recently, efforts have been made to use annual plants, especially grass-like plants, for the production of building boards, in addition to wood materials, which take many years to regrow. These annual plants have the great advantage of rapid growth. Thus, their use is particularly resource-efficient and fits better with the growing environmental awareness worldwide. Furthermore, the increasing prosperity in many countries, for example in Asia, requires meeting a large demand for building boards for residential construction, especially interior finishing and furniture construction.

[0032] Since annual plants do not lose their bark, their harvested products initially form a homogeneous raw material from a production point of view, the fibers of which can be obtained for building board production through a splicing process.

[0033] However, the processing of annual plants is significantly more complicated than wood particle-based building boards. The high levels of silicate precipitation during the manufacturing process, which have an abrasive effect on plant construction, pose a major obstacle. This requires significantly increased effort, particularly with regard to plant construction, for example, due to additional process steps, the reinforcement of certain plant components, and an increased need for spare parts. There is also a risk of production downtime.

[0034] Last but not least, the mechanical properties of boards (layers) based on particles made from annual plants differ considerably from those of their wood-particle-based counterparts. The multitude of successive process steps, the variance in the requirements of the individual process steps depending on the type of building board to be produced and their desired properties, as well as the parameters within a process step that influence the quality of the building board to be produced, result in almost infinitely complex dependency structures.

[0035] In exemplary embodiments, a building material comprises a wood-based material, an insulating material, and / or one or more raw materials such as rice straw, bagasse, bamboo, hemp, or oil palm. Exemplary building material panels include particleboard, particleboard, or OSB, and / or MDF.

[0036] For the purposes of the present disclosure, the term "building material panels" refers to panels that, for example, contain at least a large proportion (for example, more than 25% by weight) of at least one of the aforementioned building materials; in the case of wood-based panels, for example, at least a large proportion (for example, more than 50% by weight, in particular more than 75% by weight, for example, at least 80% by weight) of cellulose-containing, for example, lignocellulose-containing, material, for example, wood chips. Such building material panels may comprise other materials such as plastic materials, which may, for example, be present at least partially in particle and / or fiber form.

[0037] A production plant for the manufacture of building material boards can thus, in particular, comprise or correspond to a production plant for the manufacture of wood-based panels (or wood-based substitute building material panels). Such production plants typically comprise several production units or sections, for example, a section (e.g., a bunker) for storage, debarking, and / or chipping, a section for chip washing, a section for defibration and / or chipping and gluing, a section for fiber and / or chip drying, a section for mat forming, and / or a section for hot pressing.

[0038] Production conditions, particularly in individual sections and / or in individual units of the production plant, can be characterized by corresponding process parameters. The number of process parameters in a production plant can typically be large (e.g., up to or even more than 2000, for example, 3500 process parameters, in a typical production plant). It is understood that values ​​for process parameters within the meaning of the present disclosure correspond in particular to actual values ​​and / or target values ​​for the process parameters. Thus, in exemplary embodiments, the production plant has at least one sensor and / or at least one measuring device. For example, the production plant can have one or more pressure sensors, temperature sensors, and / or humidity sensors.The production plant may further comprise, for example, one or more measuring devices for measuring properties of the building material panels, for example, for measuring properties of wood chips. However, it is understood that the present disclosure is not limited to such sensors and / or measuring devices. The production plant may, for example, have at least one production section that has at least one sensor. For example, a pressing section may have a pressure sensor, wherein corresponding pressure measured values ​​may correspond to the process parameter pressure. Alternatively or additionally, a set target value of the pressure at the corresponding pressing section may correspond to the process parameter pressure.

[0039] In other words, in an exemplary embodiment, the method is carried out by a control device of a production plant or by a system comprising such a control device, wherein the production plant has at least one sensor and / or at least one measuring device which is configured to output at least one sensor measured value and / or a measured value of the at least one measuring device as a target or actual value for a corresponding process parameter, and which characterizes a corresponding process condition during the production of the at least one building material panel by the production plant.Exemplary process parameters, which do not limit the present disclosure, particularly of the defibration and gluing section, may include a squeeze water quantity, a steam addition to a digester, a digester fill level, a digester temperature, a steam pressure of the digester, a cooking time with the digester, a wood chip quantity, a glue addition or paraffin addition, etc. Exemplary process parameters, which do not limit the present disclosure, particularly of the mat forming section, may include a fiber discharge quantity, a spreading height, a forming belt speed, a mat basis weight, a mat moisture content, a spreading width, a pre-press pressure, a pre-press distance, a trimming width, a mat density, a spray water quantity, etc.It is understood that for further units and / or sections of a production plant, there are separate process parameters that characterize the corresponding production conditions of these further units and / or sections.

[0040] The production conditions prevailing / set in a production facility during / for the manufacture of a building material board have at least a partial influence on the properties of the produced building material board. Such (quality) properties of a building material board can be characterized in particular by quality features or quality parameters. For the purposes of the present disclosure, quality features or quality parameters can include, in particular, a transverse tensile strength, one or more flexural moduli of elasticity, a bulk density, a flexural strength, a lift-off strength, and / or thickness swelling, whereby these examples are not to be understood as limiting. Thus, further quality features or quality parameters can be provided.

[0041] A production facility can have suitable sensors and / or measuring devices at various production stages, so that production conditions during the manufacture of a building material panel can be recorded at the various production stages and assigned to a produced building material panel. Thus, sensor data and / or measurement data from a measuring device can be stored as a data set with a corresponding timestamp assigned to a produced building material panel. Such time-associated data sets / data vectors contain the process conditions or process states under which the corresponding building material panel was produced.

[0042] The at least one production factor of the production process can be understood to mean, in particular, material and / or immaterial goods used in the production of the building material panel, the use of which may, for example, be necessary for the production of the building material panel. In exemplary embodiments, the at least one production factor comprises and / or corresponds to at least one material for producing the building material panel. The at least one material can, for example, comprise or correspond to at least one raw material (e.g., wood, rice straw, bagasse, bamboo, hemp, oil palm), at least one auxiliary material (e.g., an adhesive or glue), and / or at least one operating material (e.g., gas, oil, biomass, electrical current).

[0043] In exemplary embodiments, the information relating to the at least one production factor comprises price information relating to the at least one production factor. Price information relating to a production factor may, for example, comprise at least one value representing a price, in particular a purchase price, of a specific quantity of the production factor. The price (of a specific quantity) of a production factor may, for example, correspond to an average price (of the specific quantity) of the production factor (e.g., a time-average price) and / or a current price (of the specific quantity) of the production factor (e.g., a price that is at least temporarily valid or is quoted on the market during execution, control, and / or regulation of the production process).If the at least one production factor corresponds to wood, for example, the information on the at least one production factor comprises, for example, at least one value representing an average and / or current (purchase) price for (a specific quantity) of wood (e.g., the price for one kilogram of wood). Alternatively or additionally, the information on the at least one production factor, in exemplary embodiments, comprises emissions information on the at least one production factor. Emissions information on a production factor can, for example, comprise at least one value representing a quantity (e.g., in tonnes) and / or type (e.g., carbon dioxide, methane, etc.) of greenhouse gases that were / are emitted as a result of the provision and / or use (of a specific quantity) of the at least one production factor in the production process.The amount of greenhouse gases can, for example, correspond to an average amount (i.e., for example, a statistical mean of several historically known amounts) of greenhouse gases and / or an amount of greenhouse gases estimated using a model that were / are emitted as a result of the provision and / or use (of a specific amount) of the at least one production factor. If the at least one production factor corresponds, for example, to wood, glue and / or energy source (e.g., gas, oil, biomass, electricity), the information on the at least one production factor therefore includes, for example, at least one value that represents an average and / or model-estimated amount of greenhouse gases and / or their type that were / are emitted as a result of the provision and / or use (of a specific amount) of the wood, glue and / or energy source.

[0044] Alternatively or additionally, in exemplary embodiments, the information relating to the at least one production factor comprises sustainability information relating to the at least one production factor. Sustainability information relating to a production factor may, for example, comprise at least one value indicating a quantity of the production factor required and / or consumed in the production process for manufacturing a building material panel (such a quantity may, for example, be referred to as resource consumption). Alternatively or additionally, sustainability information relating to a production factor may, for example, comprise at least one value representing a proportion of a quantity of a production factor required and / or consumed in the production process that was (e.g., previously) obtained by recycling. Such a proportion may, for example, be referred to as the recycling proportion of the production factor.The recycling share can, for example, correspond to a share of a recyclate and / or regenerated material in a quantity of a production factor required and / or consumed in the production process (e.g. share of recycled wood in the required quantity of wood).

[0045] In exemplary embodiments, the information on the at least one production factor and / or values ​​comprised by this information are variable over time (for example, a market price of a wood, a typical amount of greenhouse gases as a result of making the wood available and / or a recycling share of the wood can change over time, e.g. due to a changed market situation and / or due to production conditions in wood production that have changed over time).

[0046] In exemplary embodiments, obtaining the information about the at least one production factor comprises receiving, retrieving, and / or reading the information, for example, from an external device and / or from a computer-readable storage medium. As a result of obtaining the information about the at least one production factor, a (control) device that executes the method according to the aforementioned aspect can, for example, access the information and / or values ​​encompassed by the information and / or use the information or values ​​in at least one further step of the method.

[0047] The method according to the mentioned aspect comprises a step of determining, based on the information on the at least one production factor and using an optimization function, at least one optimized first process parameter, wherein the at least one optimized first process parameter is based on or corresponds to respective values ​​for at least one first process parameter of the production method that optimize the optimization function. In other words, the at least one optimized first process parameter can, for example, correspond to the values ​​for the at least one first process parameter that optimize the optimization function. Alternatively, the at least one optimized first process parameter can, for example, correspond to values ​​that differ by less than a predetermined amount from the values ​​that optimize the optimization function.The at least one optimized first process parameter can therefore, for example, deviate slightly (e.g., by less than a predetermined amount) from the values ​​that optimize the optimization function. Such a deviation can, for example, be caused by a production facility for carrying out the production process (e.g., due to a production tolerance) and / or can be specified by a user of the production process. Values ​​that optimize a function can, for example, be understood as optimal values ​​of the function. Consequently, the at least one optimized first process parameter can, for example, correspond to optimal values ​​for the at least one first process parameter. It is understood, however, that optimization can alternatively also be understood as improvement as far as possible.Consequently, the at least one optimized first process parameter may alternatively correspond, for example, to values ​​that improve a function value of the optimization function as much as possible (these may, for example, be referred to as best possible values).

[0048] In other words, in exemplary embodiments, the optimization function depends on the at least one first process parameter and / or the at least one optimized first process parameter represents values ​​for the at least one first process parameter that optimize the optimization function.

[0049] In exemplary embodiments, the at least one optimized first process parameter comprises or corresponds to values ​​based on which the at least one first process parameter is set (e.g., in the future). Setting a process parameter based on a value can be understood, for example, to mean that the value for the process parameter is set (e.g., as a target or actual value). Alternatively, setting a process parameter based on a value can be understood, for example, to mean that a value is set for the process parameter (e.g., as a target and / or actual value) that deviates by less than a predetermined amount from the value on the basis of which the process parameter is set.

[0050] In exemplary embodiments, the at least one first process parameter corresponds to at least one of:

[0051] • Line speed of a production plant for manufacturing building material panels;

[0052] • Weight per unit area of ​​a building material panel to be produced;

[0053] • Density of a building material panel to be produced;

[0054] • Gluing factor;

[0055] • Use of energy sources;

[0056] • Flow temperature of a thermal oil.

[0057] In exemplary embodiments, determining the at least one optimized first process parameter comprises optimizing the optimization function. Optimizing a function within the meaning of this disclosure can be understood, for example, as determining variables such that the function is maximized or minimized. In the present case, optimizing the optimization function can therefore be understood, for example, as determining values ​​for the at least one first process parameter (which can be understood, for example, as at least one variable of the optimization function) such that the optimization function is optimized. The optimization (i.e., for example, maximizing or minimizing) of the optimization function can be carried out analytically and / or numerically, for example.In exemplary embodiments, determining the at least one optimized first process parameter therefore comprises an exact (e.g., analytical) and / or approximate (e.g., numerical) determination of the at least one optimized first process parameter. The fact that the at least one optimized first process parameter is determined using the optimization function can therefore be understood, for example, as the at least one optimized first process parameter being determined by determining which values ​​for the at least one first process parameter optimize the optimization function, as described above.

[0058] In exemplary embodiments, the method further comprises obtaining the optimization function. Obtaining the optimization function may, for example, comprise receiving, retrieving, and / or reading out information representing the optimization function, for example from an external device or from a computer-readable storage medium. The information representing the optimization function may, for example, comprise values ​​for at least one parameter of the optimization function. In other words, in exemplary embodiments, the information representing the optimization function is suitable for defining the optimization function. Alternatively or additionally, in exemplary embodiments, obtaining the optimization function comprises determining the optimization function, for example by a (control) device that executes the method according to the stated aspect.

[0059] In exemplary embodiments, the optimization function comprises a cost function and / or corresponds to a cost function. A function value of a cost function can, for example, represent costs for producing one or more building material panels as a function of respective values ​​for at least one first process parameter of the production method. In exemplary embodiments, the cost function is minimized by the at least one optimized first process parameter. In this way, the at least one optimized first process parameter can advantageously reduce, for example, the costs for producing the building material panel (nj).

[0060] Alternatively or additionally, in exemplary embodiments, the optimization function comprises a profit function and / or corresponds to a profit function. A function value of a profit function can, for example, represent a profit that is expected to be achieved by selling one or more building material panels, taking into account the costs for producing the building material panel(s) as a function of respective values ​​for at least one first process parameter of the production method. In exemplary embodiments, the profit function is maximized by the at least one optimized first process parameter. In this way, the at least one optimized first process parameter can advantageously, for example, maximize the (expected) achievable profit, taking into account the costs for producing the building material panel. The profit function can, for example, depend on price information about the building material panel.Thus, in exemplary embodiments, the profit function may depend on a price, in particular a selling price, of the building material panel.

[0061] In exemplary embodiments, the method according to the said aspect therefore further comprises:

[0062] Obtain price information about the building material board.

[0063] Price information relating to the building material panel may, for example, comprise at least one value representing a price, in particular a sales price, of the building material panel. The price of the building material panel may, for example, correspond to an average price (i.e., for example, a time-average price) and / or a current price (i.e., for example, a price that is at least temporarily valid during execution, control, and / or regulation of the production process, e.g., can be achieved on the market) of the building material panel. Properties (e.g., quality characteristics) of the manufactured building material panel may, for example, be taken into account here.For example, if the production method is a production method for manufacturing an OSB board with predetermined properties, the price information relating to the building material board may, for example, comprise at least one value representing the average and / or current price of an OSB board with these predetermined properties. The above explanations regarding the step of obtaining information relating to the at least one production factor apply accordingly to the step of obtaining price information. Thus, obtaining the price information may, for example, comprise receiving, retrieving, and / or reading the price information, for example from an external device or from a computer-readable storage medium.As a result of receiving the price information, a control device that carries out the method according to the said aspect can, for example, access the price information and / or use the price information in at least one further step of the method.

[0064] Alternatively or additionally, in exemplary embodiments, the optimization function comprises an emissions function and / or corresponds to an emissions function. A function value of an emissions function can, for example, represent an amount of greenhouse gases (e.g., in tons of CO2 equivalent) emitted as a result of the provision and / or use (of a specific amount) of at least one production factor in the production process for manufacturing a building material panel. In exemplary embodiments, the emissions function is minimized by the at least one optimized first process parameter. In this way, the optimized first process parameters can, for example, advantageously make it possible to reduce emissions (e.g., CO2 emissions) that arise during the production of the building material panel.

[0065] Alternatively or additionally, in exemplary embodiments, the optimization function comprises a sustainability function and / or corresponds to a sustainability function. A function value of a sustainability function can, for example, correspond to a value that represents a measure of sustainability in the production of the building material panels. The function value of the sustainability function can, for example, depend on an amount of resources (exemplary production factors) that are required and / or consumed in the production process for producing a building material panel (such an amount can, for example, be referred to as resource consumption of the production process). Alternatively or additionally, the function value of the sustainability function can, for example, depend on a value that represents a recycling share of the production process.The recycled content can, for example, correspond to a proportion of a quantity of a production factor required and / or consumed in the production process that was (e.g., previously) obtained through recycling. The recycled content can, for example, correspond to a proportion of a recyclate and / or regenerated material in the quantity of a production factor required and / or consumed in the production process (e.g., proportion of recycled wood in the required quantity of wood).

[0066] In exemplary embodiments, the sustainability function is minimized or maximized by the at least one optimized first process parameter. In this way, the at least one optimized first process parameter can, for example, advantageously enable the resource consumption of the production process to be reduced and / or the recycling rate to be increased, thus improving the sustainability of the production process.

[0067] In exemplary embodiments, the optimization function comprises at least one of:

[0068] • a cost function;

[0069] • a profit function;

[0070] • an emission function; and / or

[0071] • a sustainability function.

[0072] It is understood that an optimization function within the meaning of the present disclosure may correspond to a single one of the above-mentioned examples of optimization functions or may comprise several of the above-mentioned examples of optimization functions. For example, the optimization function may comprise both a cost function and an emissions function or both a cost function and a sustainability function. In exemplary embodiments, the cost function and / or the profit function is minimized (cost function) or maximized (profit function), wherein (e.g. simultaneously) a function value of the emissions function and / or the sustainability function does not exceed (emission function) or falls below (sustainability function) at least a predetermined threshold value. Alternatively, the emissions function and / or the sustainability function may be minimized (emission function) or maximized (profit function) in exemplary embodiments.maximized (sustainability function), whereby (e.g., simultaneously) a function value of the cost function and / or the profit function does not exceed (cost function) or falls below (profit function) a specified threshold. In other words, for example, one variable to be optimized (costs, profit, emissions, sustainability) can be optimized, while at the same time another variable to be optimized does not exceed or fall below at least a specified threshold (depending on whether minimization or maximization of the variable to be optimized is desired).

[0073] It is understood that the above examples of optimization functions are merely non-limiting examples. An optimization function within the meaning of the present disclosure may, in principle, include or correspond to any function whose function value represents a quantity to be optimized (e.g., maximized or minimized).

[0074] According to the stated aspect, each of the at least one first process parameters is related to at least one of the at least one production factor of the production process. In other words, in exemplary embodiments, each of the at least one first process parameter is related (e.g., directly) to one or more production factors of the production process. For example, the exemplary process parameter "area weight of wood" is related to the exemplary production factor "wood" (e.g., a higher desired / required area weight may require a greater wood requirement). Furthermore, the exemplary process parameter "gluing factor" is related to the exemplary production factor "glue" (e.g., a higher desired / required gluing factor may require a greater glue requirement).Furthermore, the exemplary process parameter "thermal oil flow temperature" is related to the exemplary production factors gas, oil, biomass, and / or electricity (e.g., a higher desired / required thermal oil flow temperature may result in a higher energy demand, which then has to be covered, for example, by a larger quantity of the aforementioned energy sources). In exemplary embodiments, a respective demand for a respective production factor of the production process thus depends (e.g., directly or indirectly) on a respective value of at least one of the at least one first process parameter.

[0075] In exemplary embodiments, the information on the at least one production factor comprises values ​​that are included in the optimization function as a factor, in particular as a weighting factor, for the process parameter associated with the respective production factor. For this purpose, the information on the at least one production factor can, for example, comprise values ​​that represent parameters of the optimization function (e.g., time-variable parameters). A parameter of the optimization function can, for example, correspond to a coefficient of a mathematical expression included in the optimization function. For example, the costs for a glue (in embodiments in which the optimization function is a cost function and a production factor is glue) can depend on the exemplary process parameter gluing factor and on a price for the glue. The exemplary process parameter gluing factor can, for example, be (e.g.,controllable and / or regulatable) variable of the cost function (e.g. since the gluing factor can be adjusted in the production process), while the price for the glue can be understood, for example, as a (e.g. non-controllable and / or regulatable, but time-variable) parameter of the cost function (e.g. since the price for the glue is time-variable, but cannot be adjusted). In other words, in exemplary embodiments, the at least one first process parameter represents a cost-relevant, regulatable process variable and / or the information on the at least one production factor comprises values ​​for a cost-relevant, non-regulatable process variable. For example, a price for a glue can serve as a coefficient (or weighting factor) for the exemplary process parameter gluing factor.For example, an expression encompassed by a cost function representing the cost of a glue can include the price of the glue as a coefficient and the exemplary process parameter gluing factor as a variable (the expression can, for example, include the product of the glue price and the gluing factor). It is understood that the cost function mentioned in the above example, as well as the process parameter gluing factor and the production factor glue, are merely examples.

[0076] In exemplary embodiments, the first process parameters thus represent variables of the optimization function and / or the information on the at least one production factor includes values ​​for (e.g., time-variable) parameters of the optimization function. The fact that the at least one optimized first process parameter is determined based on the (received) information on the at least one production factor can therefore be understood, for example, as values ​​included in the information on the at least one production factor being incorporated as parameters of the optimization function in an optimization of the optimization function.

[0077] The method according to the stated aspect further comprises a step of determining, using a mathematical model, respective values ​​for at least one second process parameter of the production method such that, when the production method is executed based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter, at least one constraint associated with the building material panel is met. In exemplary embodiments, the execution of the production method based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter corresponds to an execution of the production method using the stated parameters / values.The execution of the production process using the said parameters / values ​​can, for example, comprise at least temporarily setting the said parameters / values ​​in the production process (e.g. as target values).

[0078] In alternative exemplary embodiments, the execution of the production method based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter corresponds to an execution of the production method using respective values ​​for the at least one first and second process parameters that differ by less than a predetermined amount from the at least one optimized first process parameter and from the determined values ​​for the at least one second process parameter, respectively. In other words, in exemplary embodiments, values ​​for the at least one first and second process parameters are used to execute the production method that differ by less than a predetermined amount from the values ​​(previously) determined using the optimization function and the mathematical model.

[0079] In exemplary embodiments, compliance with the at least one secondary condition associated with the building material board corresponds to compliance with at least one predefined quality criterion for the building material board. Compliance with a predefined quality criterion can, for example, correspond to exceeding or falling below a quality threshold. A quality threshold can, for example, be understood as a threshold value to be achieved (e.g., to be exceeded or fallen below) for a quality parameter of the building material board. For example, a quality threshold can correspond to a minimum quality threshold (a threshold value that represents a quality of the building material board that must at least be achieved). A quality parameter of a building material board can, for example, be understood as a value that indicates at least one qualitative property of the building material board.Such a qualitative property of the building material board can, for example, be referred to as a quality property. In exemplary embodiments, compliance with the at least one predefined quality criterion therefore corresponds to the achievement of at least one quality threshold value by at least one quality parameter of the building material board.

[0080] Alternatively or additionally, the at least one constraint associated with the building material panel may, for example, comprise or represent desired dimensions (e.g. width, length, height, volume, etc.) and / or a desired appearance (e.g. color, surface structure, etc.) of the building material panel.

[0081] In exemplary embodiments, the at least one predetermined quality criterion for the building material panel is measurable and / or predictable during the production process. In other words, the at least one predetermined quality criterion is measurable and / or predictable online in exemplary embodiments. The fact that a quality criterion is measurable and / or predictable during the production process (or online) can be understood, for example, to mean that at least one quality parameter of the building material panel can be measured and / or predicted during the production process (or online), so that, for example, the achievement of at least one quality threshold value by the at least one quality parameter of the building material panel can be checked (e.g., likewise) during the production process (or online), as explained above. The prediction of quality parameters (e.g.,of a building material panel) during a production process can, for example, be referred to as online quality prediction.

[0082] In exemplary embodiments, the period "during the production process" encompasses a period in which a specific building material panel to be produced is produced. This period can, for example, begin with a first production step of the production process and / or end with a final production step of the production process (see the above exemplary explanations in connection with the production plant).

[0083] In particular, the use of quality criteria that can be predicted during the production process advantageously enables even those quality criteria that cannot be measured during the production process (or online) to be taken into account when determining and providing optimized process parameters. This way, compliance with quality characteristics that cannot be measured online can also be advantageously ensured within the production process.

[0084] In exemplary embodiments, the mathematical model comprises a set of model coefficients for one or more mathematical equations which are configured to output respective values ​​for the at least one second process parameter based on an input comprising values ​​for the at least one first process parameter and further comprising at least one value representing the at least one constraint associated with the building material panel, wherein the values ​​for the at least one second process parameter are such that, when the production method is executed, the at least one constraint is met based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter.

[0085] In other words, in exemplary embodiments, the mathematical model is configured to output values ​​for second process parameters that match (e.g., previously) determined values ​​for first process parameters. Matching values ​​for second process parameters can be understood, for example, as values ​​such that, when used in the production process together with the values ​​for the first process parameters (e.g., by setting the values ​​for the first and second process parameters as target values), at least one constraint associated with the building material panel is met.In short, the mathematical model can be used to advantageously ensure, for example, that only those values ​​for the second process parameters are determined and / or set in the production process which, together with the optimized first process parameters, lead to the production of building material panels that fulfill at least one secondary condition (e.g., expected).

[0086] Thus, the values ​​for the second process parameters determined using the mathematical model enable the optimized first process parameters to be set in the production process, whereby a variable represented by the optimization function can be advantageously optimized while simultaneously complying with the constraints associated with the building material panel (e.g., one or more predetermined quality criteria).

[0087] In exemplary embodiments, the at least one second process parameter corresponds to at least one of:

[0088] • at least one pressing pressure;

[0089] • at least one pressing distance;

[0090] • at least one pressing temperature;

[0091] • at least one pre-press distance;

[0092] • at least one pre-press pressure;

[0093] • at least one mat temperature; and / or

[0094] • at least one chip moisture content.

[0095] In exemplary embodiments, the mathematical model comprises a statistical model or corresponds to a statistical model. In particular, in one exemplary embodiment, the mathematical model is based on a so-called model for interdependent simultaneous stochastic linear equations. It has been shown that, for example, regression models for interdependent systems of simultaneous (linear) stochastic equations can be suitable for modeling the production processes for building panels. In particular, the processes in the wood-based materials industry can be regarded as interdependent and simultaneous, since several product properties arise simultaneously and not independently of one another, and since the influencing variables or process parameters are interdependent. The model equations can be described as linear, since the model coefficients are linear.It should be understood, however, that the present disclosure is not limited to such linear systems. For example, process parameters may also be incorporated with a quadratic, cubic, or exponential (or other) weight.

[0096] Thus, in exemplary embodiments, the mathematical model comprises a simultaneous equation model, in particular a mathematical model based on the three-stage least squares method ("3SLS"). In exemplary embodiments, the mathematical model further comprises a mathematical model based on the two-stage least squares method ("2SLS"), a mathematical model based on partial least squares (PLS), and / or a linear regression model.

[0097] Alternatively or additionally, in exemplary embodiments, the mathematical model is based on machine learning (ML) methods and / or artificial intelligence (AI). For example, the mathematical model can be based on reinforcement learning, deep reinforcement learning, and / or at least one artificial neural network. It has been shown that mathematical models based on reinforcement learning, in particular, are particularly suitable for depicting or modeling the above-mentioned interdependent and / or simultaneous processes in the wood-based materials industry in a particularly accurate and / or robust manner.

[0098] The method according to the stated aspect further comprises a step of providing the at least one optimized first process parameter and the values ​​for the at least one second process parameter for use in the production process. In exemplary embodiments, providing values ​​for process parameters comprises transmitting (e.g., sending) the values, for example, to at least one production system for producing building material panels. Alternatively or additionally, in exemplary embodiments, providing the values ​​comprises setting the values ​​in a production process for producing a building material panel, for example, as a target value. The at least one optimized first process parameter and the values ​​for the at least one second process parameter can, for example, be transmitted and / or set simultaneously or sequentially.Alternatively or additionally, in exemplary embodiments, the provision comprises storing (for example temporarily or permanently) the at least one optimized first process parameter and / or the values ​​for the at least one second process parameter, for example for later transmission and / or adjustment to a production plant for producing building material panels.

[0099] Alternatively or additionally, in exemplary embodiments, the provision comprises outputting the at least one optimized first process parameter and / or the values ​​for the at least one second process parameter. In this case, outputting the said process parameters and / or values ​​can, for example, comprise internal output or forwarding of these parameters / values, for example within the at least one control device, for example for further use of the parameters / values ​​by the at least one control device. Outputting the said parameters and / or values ​​can further comprise, for example, outputting the said parameters and / or values ​​for further processing by a device external (for example from the at least one control device).For example, the output process parameters and / or values ​​can be converted in the control device or in another data processing device into display data that can be used by a display device (e.g., a screen connected to the control device) to display a representation or display.

[0100] In exemplary embodiments, the method further comprises:

[0101] Initiating a display of a representation of the at least one optimized first process parameter and / or the values ​​for the at least one second process parameter on a display device connected to the production plant; and / or

[0102] Generating at least one control signal based on the at least one optimized first process parameter and / or on the values ​​for the at least one second process parameter for controlling at least one component of the production plant

[0103] In other words, the at least one optimized first process parameter and / or the values ​​for the at least one second process parameter can be used in exemplary embodiments, on the one hand, for displaying a representation or representation of the said parameters / values. In this case, a representation can, for example, comprise a graphical representation of the said parameters / values ​​(for example, a real-time representation) in the form of a data value-time curve on a screen, wherein the screen, as a display device, can be directly or indirectly connected to the control device and / or the production plant. Such a display of the said parameters / values ​​can, for example, enable a user to control an autonomous control / regulation of the production plant (e.g., in real time) and / or during the production of a building material panel (e.g.,online) about which values ​​for the first and / or second process parameters have been determined as optimized and / or set by an autonomous control / regulation process.

[0104] Alternatively or additionally, the at least one control signal generated in exemplary embodiments based on the at least one optimized first process parameter and / or on the values ​​for the at least one second process parameter is used to directly control and / or regulate at least one component of the production plant, for example using control electronics operating based on a feedback loop.

[0105] In exemplary embodiments, the method therefore further comprises: controlling and / or regulating the production process for producing a building material panel based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter.

[0106] Controlling the production process based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter comprises, in exemplary embodiments, at least temporarily setting the optimized first process parameters and the values ​​for the at least one second process parameter in the production process, e.g. as target values.

[0107] Alternatively or additionally, controlling the production process based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter, in exemplary embodiments, comprises at least temporarily setting respective values ​​for the at least one first and second process parameters, respectively, which differ by less than a predetermined amount from the at least one optimized first process parameter and from the determined values ​​for the at least one second process parameter, respectively. In other words, in exemplary embodiments, values ​​for the at least one first and second process parameters are set that differ to a relatively small (e.g., predetermined) extent from the optimized process parameters.

[0108] In exemplary embodiments, controlling the production process based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter also comprises at least temporarily setting the optimized first process parameters and the values ​​for the at least one second process parameter in the production process, e.g., as target values. In exemplary embodiments, controlling the production process further comprises checking whether the at least one optimized first process parameter and the values ​​for the at least one second process parameter are (e.g., actually) set and / or measurable, e.g., as actual values, for the at least one first and the at least one second process parameter of the production process.In a case in which this check is unsuccessful (for example in a case in which the actual values ​​deviate from the target values), the control of the production process in exemplary embodiments further comprises at least temporarily setting respective adjusted values ​​for the at least one first and / or the at least one second process parameter of the production process (e.g. as target values). The adjusted values ​​can, for example, be such that as a result of the at least temporarily setting the adjusted values ​​for the at least one first and / or the at least one second process parameter of the production process (e.g. as target values), the at least one optimized first process parameter and the values ​​for the at least one second process parameter are (e.g. actually) set and / or measurable, e.g. as actual values.In other words, in exemplary embodiments, controlling the production process comprises at least temporarily controlling the at least one first process parameter and the at least one second process parameter such that the at least one optimized first process parameter and the (previously determined) values ​​for the at least one second process parameter are (actually) set for the at least one first and the at least one second process parameter in the production process, e.g., as actual values. The procedure described above can, for example, be referred to as a closed control loop. It is therefore understood that controlling a production process can be understood as controlling the production process in a specific way. In exemplary embodiments, controlling the production process therefore comprises controlling the production process.

[0109] Alternatively or additionally, the control of the production process based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter in exemplary embodiments comprises at least temporarily controlling and / or regulating the at least one first process parameter and the at least one second process parameter such that values ​​(e.g. actual values) set and / or measurable for the at least one first and the at least one second process parameter (e.g. actual values) differ by less than a predetermined amount from the optimized first process parameters or from the values ​​for the second process parameters.

[0110] The control and / or regulation of the production process based on the said parameters / values ​​(e.g. using the said parameters / values) can be carried out, for example, with the aid of at least one control and / or regulation signal which is generated (e.g. previously) based on the at least one optimized first process parameter and / or on the values ​​for the at least one second process parameter, e.g. as explained above.

[0111] In particular, the control and / or regulation of a production process based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter advantageously makes it possible to operate a production plant for producing building material panels in such a way that a predetermined optimization goal is achieved (e.g. costs are minimized) and at the same time a secondary condition associated with the building material panel (e.g. a predetermined quality) can be maintained.

[0112] The provision of the at least one optimized first process parameter and the values ​​for the at least one second process parameter is therefore carried out for the use of the said parameters / values ​​in the production process for manufacturing building material panels.

[0113] The determination and provision of the at least one optimized first process parameter and the values ​​for the at least one second process parameter by means of the method according to the first aspect advantageously make it possible to control / regulate a production process for manufacturing building material panels (for example by setting the said values ​​for the process parameters as target values) in such a way that, on the one hand, a target function to be optimized (the optimization function) is optimized in a desired manner (e.g., minimized or maximized), and that, on the other hand, at least one secondary condition associated with the building material panel (e.g., a predetermined quality criterion) is met.

[0114] For example, the method according to the said aspect can enable the determination and provision of values ​​for (plant) technical process parameters by means of which a production plant for producing building material panels can be controlled / regulated in such a way that, for example, a predetermined quality of building material panels produced using the production process is achieved at minimal costs (in a case in which the optimization function is a cost function) and / or minimal emissions (in a case in which the optimization function is an emission function).

[0115] In short, the method according to the aforementioned aspect makes it possible to determine the best possible values ​​for (plant-related) process parameters of a production process for manufacturing building material panels with respect to the requirements mentioned above, in particular in order to advantageously control and / or regulate a corresponding production plant. Furthermore, determining suitable values ​​for the first and second process parameters using the method according to the aforementioned aspect is more efficient than (exclusively) manually determining these values.

[0116] The method according to the aforementioned aspect can further reduce manual control / regulation effort, for example if the provided parameters / values ​​are used for at least partially autonomous control / regulation of the production process. Thus, in exemplary embodiments, the control and / or regulation of the production process takes place autonomously and / or automatically. Autonomous or automated control and / or regulation of the production process can be understood, for example, to mean that the at least one optimized first process parameter and the values ​​for the at least one second process parameter in the production process are set autonomously and / or automatically, e.g. as target values, e.g. by at least one control device.Autonomous and / or automated setting of values ​​can be understood, for example, as meaning that the setting occurs automatically, for example, without a human user initiating the setting. This type of control / regulation of the production process can be referred to, for example, as a higher-level closed control loop. In exemplary embodiments, the method according to the aforementioned aspect is a method for at least partially autonomously controlling and / or regulating a production process for manufacturing a building material panel. Such autonomous and / or automated control / regulation of the production process advantageously makes it possible to reduce manual control / regulation effort.

[0117] In exemplary embodiments, values ​​for the at least one first process parameter and / or for the at least one second process parameter are continuously determined and / or provided (e.g., in real time) using the method according to the aforementioned aspect. The fact that the aforementioned values ​​are continuously determined and / or provided can be understood, for example, to mean that the aforementioned values ​​are repeatedly determined and / or provided, in particular with a frequency that is greater than or equal to a predetermined frequency. Such continuous determination / provision can, for example, be referred to as a dynamic process in the sense of a real-time control loop.

[0118] In exemplary embodiments, the optimization function is dependent on the at least one first process parameter and / or the optimization function is independent of the at least one second process parameter. In other words, in exemplary embodiments, the optimization function is a function of the at least one first process parameter and / or not a function of the at least one second process parameter. The fact that the optimization function is / is not a function of a process parameter can be understood, for example, to mean that a (function) value of the optimization function changes / does not change when a value of the process parameter changes. In exemplary embodiments, the at least one first process parameter is therefore a variable of the optimization function and / or the at least one second process parameter is not a variable of the optimization function.While the at least one first process parameter can thus be understood, for example, as at least one variable of the optimization function, the at least one optimized first process parameter can be understood as the respective (specific) value of this at least one variable (e.g., as a value that optimizes the optimization function). In particular, this division of process parameters into first and second process parameters advantageously makes it possible to optimize the optimization function in a desired manner depending on the at least one first process parameter and, furthermore, to select values ​​for the at least one second process parameter such that the at least one constraint associated with the building material panel is simultaneously met.

[0119] In exemplary embodiments, the method further comprises:

[0120] Checking whether the at least one optimized first process parameter and the values ​​for the at least one second process parameter are such that, when the production method is carried out, at least one restriction of a control and / or regulation of the production method is taken into account based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter; and o in a case where the check is successful, providing the at least one optimized first process parameter and the values ​​for the at least one second process parameter for use in the production method; o in a case where the check is unsuccessful, discarding the values ​​for the at least one second process parameter and / or determining further values ​​for the at least one second process parameter.

[0121] The fact that the test is successful can be understood, for example, to mean that it is determined that the at least one optimized first process parameter and the values ​​for the at least one second process parameter are such that when the production process is carried out based on the said parameters / values ​​(e.g. using them), the at least one restriction of a control and / or regulation of the production process is taken into account.

[0122] Thus, in exemplary embodiments, the method comprises:

[0123] Determining that the at least one optimized first process parameter and the values ​​for the at least one second process parameter are such that, when executing the production method based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter, at least one restriction of a control and / or regulation of the production method is taken into account; and

[0124] Providing the at least one optimized first process parameter and the values ​​for the at least one second process parameter for use in the production process.

[0125] The fact that the test is unsuccessful can be understood, for example, to mean that it is determined that the at least one optimized first process parameter and the values ​​for the at least one second process parameter are such that when the production process is carried out based on the said parameters / values ​​(e.g. using the said parameters / values), the at least one restriction of a control and / or regulation of the production process is not taken into account.

[0126] Thus, in exemplary embodiments, the method comprises: determining that the at least one optimized first process parameter and the values ​​for the at least one second process parameter are such that, when executing the production method based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter, at least one restriction of a control and / or regulation of the production method is not taken into account; and

[0127] Discarding the values ​​for the at least one second process parameter and / or determining further values ​​for the at least one second process parameter.

[0128] In exemplary embodiments, discarding the values ​​for the at least one second process parameter comprises deleting the values, e.g., from a computer-readable storage medium. Furthermore, discarding the values ​​for the at least one second process parameter can be understood, for example, to mean that the values ​​for the at least one second process parameter are not used in the production process, e.g., for controlling and / or regulating the production process. In exemplary embodiments, determining further values ​​for the at least one second process parameter comprises determining, using the mathematical model, a further (e.g., second, third, fourth, etc.) set of values ​​for the at least one second process parameter.In exemplary embodiments, the determination of the further set of values ​​for the at least one second process parameter is repeated until a set of values ​​for the at least one second process parameter is found, the use of which together with the at least one optimized first process parameter satisfies the at least one constraint associated with the production process.

[0129] In exemplary embodiments, the at least one restriction on the control and / or regulation of the production process is conditioned by a production plant for executing the production process and / or is specified by a user of the production process. In other words, the at least one restriction on the control and / or regulation of the production process in exemplary embodiments represents a (machine and / or plant) technical restriction on the control / regulation of the production process and / or a restriction on the control / regulation specified by a user of the production process. A restriction can be understood, for example, as a limitation (e.g. with regard to possible interventions and / or control objectives). A user can be understood, for example, as an operator of the production process and / or the production plant.

[0130] In exemplary embodiments, the at least one restriction of the control and / or regulation of the production process comprises at least one predetermined threshold value for the at least one first and / or for the at least one second process parameter of the production process. The check as to whether the at least one optimized first process parameter and the values ​​for the at least one second process parameter are such that the at least one restriction of the control and / or regulation of the production process is taken into account can, in the aforementioned exemplary embodiments, for example, comprise checking whether the at least one optimized first process parameter and the values ​​for the at least one second process parameter exceed the at least one threshold value (in the case of a lower threshold value) or fall below the at least one threshold value (in the case of an upper threshold value).

[0131] Alternatively or additionally, in exemplary embodiments, the at least one restriction of the control and / or regulation of the production process comprises at least one predetermined value range for the at least one first and / or for the at least one second process parameter. Checking whether the at least one optimized first process parameter and the values ​​for the at least one second process parameter are such that the at least one restriction of the control and / or regulation of the production process is taken into account can, for example, in the aforementioned exemplary embodiments, comprise checking whether the at least one optimized first process parameter and the values ​​for the at least one second process parameter lie within or outside the at least one value range.

[0132] Furthermore, alternatively or additionally, the at least one restriction of the control and / or regulation of the production process in exemplary embodiments corresponds to a predetermined state to be maintained for at least part of the production plant for manufacturing building material panels. The check as to whether the at least one optimized first process parameter and the values ​​for the at least one second process parameter are such that the at least one restriction of the control and / or regulation of the production process is taken into account can, for example, in the aforementioned exemplary embodiments, comprise checking whether the predetermined state to be maintained for at least part of the production plant is maintained when the at least one optimized first process parameter and the values ​​for the at least one second process parameter are used in the production process (e.g., set as target values).

[0133] By taking into account (machine) technical and / or user-related restrictions in the control / regulation of the production process, it is possible to advantageously ensure both less disruptive operation of a corresponding production plant and operation in a manner desired by the user.

[0134] In exemplary embodiments, the method further comprises:

[0135] Obtaining information on at least one environmental condition under which the production process is carried out, and / or

[0136] Obtaining respective values ​​for at least one previous process parameter of the production process; wherein determining the values ​​for the at least one second process parameter is based on the information about the at least one environmental condition and / or on the values ​​for the at least one previous process parameter.

[0137] The at least one environmental condition under which the production method is carried out comprises, in exemplary embodiments, at least one of:

[0138] • a temperature at which the production process is carried out;

[0139] • the humidity at which the production process is carried out;

[0140] • an air pressure at which the production process is carried out.

[0141] The at least one environmental condition can, for example, have an influence on the production process (e.g., an ambient temperature can influence a temperature in a unit or in a section of the production plant). Consequently, the relationships represented by the mathematical model (e.g., between process parameters of the production process and quality parameters of the building material panel) can, for example, depend on and / or be influenced by the at least one environmental condition (e.g., it may be necessary to increase a flow temperature of a thermal oil if an ambient temperature is comparatively low). Similarly, the at least one previous process parameter can, for example, have an influence on building material panels currently in production (e.g.,a previous process parameter set in a first production step can have an influence on properties of a building material panel that has passed through the first production step when the previous process parameter was set there). In exemplary embodiments, the at least one previous process parameter comprises at least one previous value of the at least one first process parameter and / or at least one previous value of the at least one second process parameter. It is understood that the "previous" refers in particular to the time of execution, control and / or regulation of the method according to the mentioned aspect. An earlier process parameter can therefore be understood, for example, as a value of the process parameter that was set or measured at a time prior to a time of execution, control and / or regulation of the method according to the mentioned aspect.

[0142] Because the determination of the values ​​for the at least one second process parameter is based on the information on the at least one environmental condition and / or on the values ​​for the at least one previous process parameter in exemplary embodiments, an influence of environmental conditions and / or previous process parameters on the production process is advantageously taken into account, whereby an accuracy and robustness of the determination of the values ​​for the at least one second process parameter are further improved.

[0143] Alternatively or additionally, in exemplary embodiments, the determination of the at least one optimized first process parameter using the optimization function is also based on the information about the at least one environmental condition and / or on the values ​​for the at least one previous process parameter. In this way, the influence of environmental conditions and / or previous process parameters on which values ​​are best / optimal for the first process parameters at the respective point in time can be advantageously taken into account, which in particular can further improve the accuracy of determining the optimized first process parameters.

[0144] In exemplary embodiments, obtaining information about the at least one production factor comprises at least one of:

[0145] Receiving the information from at least one external device; and / or

[0146] Reading the information from at least one internal or external computer-readable storage medium.

[0147] In exemplary embodiments, a (control) device that carries out the method according to the aforementioned aspect is connected to the external device and / or the external storage medium via a wired and / or wireless communication connection (e.g., a data interface). The external device and / or the external storage medium can, for example, be comprised of or comprised by an external system. In exemplary embodiments, the external system maintains the information relating to the at least one production factor and / or makes it available to the (control) device. The external system can, for example, be a commercial system that provides or maintains the information relating to the at least one production factor (e.g., information relating to the costs of at least one material used, information relating to energy costs, and / or information relating to expected sales revenues for the building material panel).The commercial system can, for example, correspond to or include an Enterprise Resource Planning (ERP) system.

[0148] In exemplary embodiments, the receiving and / or reading of the information relating to the at least one production factor takes place automatically, for example without a human user of the production method initiating the receiving and / or reading (e.g. directly). In exemplary embodiments, the receiving and / or reading of the said information is instead initiated by at least one signal, e.g. an update signal, which is sent, for example, from the at least one external device or the external system to the control device. An update signal can be understood, for example, as a signal which indicates that at least part of the information relating to the at least one production factor has changed (e.g. has been updated) within a predetermined time interval.

[0149] In exemplary embodiments, obtaining information about the at least one production factor therefore comprises:

[0150] Receiving, from at least one external device, an update signal indicating that at least part of the information relating to the at least one production factor has changed within a predetermined time interval; and receiving the information from the at least one external device and / or reading the information from at least one computer-readable storage medium comprised by the at least one external device.

[0151] In exemplary embodiments, the internal storage medium is part of a (control) device that executes the method according to the aforementioned aspect. In exemplary embodiments, the information relating to the at least one production factor is stored in and / or retained by the internal storage medium. Consequently, in exemplary embodiments, the (control) device can access the information stored in the internal storage medium, for example, read it from the internal storage medium.

[0152] Because the information on the at least one production factor can be obtained in various ways, it can advantageously be ensured that the information on the at least one production factor is as complete and / or up-to-date as possible. In this way, it can be ensured that, at a time when the optimized first process parameters are determined, the optimized first process parameters (actually) optimize the optimization function in light of the information on the at least one production factor on the basis of which the optimized first process parameters are determined.

[0153] In exemplary embodiments, the method further comprises obtaining the mathematical model, wherein obtaining the mathematical model comprises:

[0154] Obtaining at least one training data set comprising training input data and training output data; and

[0155] Generating the mathematical model based on the at least one training data set.

[0156] In exemplary embodiments, obtaining the at least one training data set comprises receiving, retrieving, and / or reading the at least one training data set, for example, from an external device or from a computer-readable storage medium. A training data set can be understood, for example, as a data set that is suitable and / or intended for training a mathematical model.

[0157] Training input data can be understood, for example, as data used as predefined input data during training of a mathematical model (e.g., in the form of supervised learning). In exemplary embodiments, the training input data includes values ​​for the at least one first process parameter and values ​​representing at least one constraint associated with the building material panel.

[0158] Training output data can be understood, for example, as data that is used as predetermined output data during training of a mathematical model (e.g., in the form of supervised learning). In exemplary embodiments, the training output data comprise values ​​for the at least one second process parameter, wherein the values ​​for the at least one second process parameter are such that, when the production method is executed, the at least one constraint associated with the building material panel is met based on the values ​​for the at least one second process parameter and on the values ​​for the at least one first process parameter included in the training input data.

[0159] For production processes for manufacturing building material panels, the at least one training data set can be obtained, for example, by removing building material panels produced by the production process or parts thereof after the production process at regular intervals and measuring one or more properties (e.g., a quality characteristic) of the removed building material panels, for example, in a laboratory or by a test robot. The measured properties can then be used, for example, to check whether one or more constraints associated with the building material panel (e.g., a quality criterion) are met or not.

[0160] In this way, the at least one training data set for a building material panel sample (entire panel or parts thereof) can comprise actual values ​​(e.g., measured values ​​measured for a corresponding building material panel sample in a laboratory) for at least one property (e.g., a quality characteristic) of a building material panel sample. Furthermore, the at least one training data set can comprise values ​​for process parameters of a production method for manufacturing the building material panel sample (e.g., target or actual values, obtained, for example, by a corresponding sensor, a corresponding measuring device, and / or by a corresponding setting device of the production plant) that were set during the production of the building material panel sample. In exemplary embodiments, the values ​​for the process parameters are chronologically assigned process parameter values ​​that include a corresponding timestamp.The timestamp corresponds to the point in time for which a process parameter value characterizes a process condition that existed during the production of a produced building material panel.

[0161] In exemplary embodiments, the one or more model parameters of the mathematical model are then adapted such that the mathematical model learns, based on values ​​for the first process parameters (first input data) and values ​​that represent at least one constraint associated with the building material panel (second input data), to output values ​​for second process parameters (output data) that are such that when the production method is carried out based on the values ​​for the first and second process parameters (e.g. using the said values), the at least one constraint associated with the building material panel is met.

[0162] Accordingly, generating the mathematical model based on the at least one training data set can be understood as, for example, training the mathematical model based on the at least one training data set. Because the at least one training data set, as explained above, includes, for example, actual values ​​for both process parameters and resulting properties (e.g., quality characteristics) of a building material panel sample, the at least one training data set advantageously enables the training of the mathematical model. This can be done successively for additional training data sets (e.g., whenever new training data sets are received during the production process), so that the mathematical model learns with additional training data sets and can thus be trained, which advantageously results in improved accuracy of the mathematical model.

[0163] In alternative exemplary embodiments, obtaining the mathematical model comprises receiving, retrieving, and / or reading information representing the mathematical model, for example, from an external device or from a computer-readable storage medium. Information representing a mathematical model may, for example, include values ​​representing some or all of the model parameters of the mathematical model. In other words, obtaining the mathematical model in alternative exemplary embodiments comprises obtaining a previously trained mathematical model.

[0164] Obtaining the mathematical model in at least one of the aforementioned ways advantageously makes it possible to determine, using the mathematical model, values ​​(as explained above) for second process parameters that match the optimized first process parameters. In this way, the best possible (plant-related) process parameters of a production process for manufacturing building material panels can be advantageously determined.

[0165] Furthermore, obtaining the mathematical model in at least one of the aforementioned ways enables, in particular, the at least one second process parameter to be determined (e.g., locally), for example, by a control device that executes the method according to the aforementioned aspect. This eliminates the otherwise necessary transmission of the at least one second process parameter, e.g., from an external device, to the control device, e.g., via a data interface. This advantageously reduces network usage.

[0166] In exemplary embodiments, the training input data further includes values ​​representing at least one environmental condition under which the production process is carried out and / or values ​​for at least one previous process parameter of the production process. Thus, in exemplary embodiments, the mathematical model is trained based on the stated values. In this way, an influence of environmental conditions and / or previous process parameters on the production process is taken into account in the parameters or coefficients of the mathematical model, thereby advantageously further improving the accuracy and robustness of the mathematical model.

[0167] In exemplary embodiments, generating the mathematical model based on the at least one training data set comprises determining at least one model parameter of the mathematical model such that, when using the training input data as input data, the mathematical model outputs output data that differs from the training output data by less than a predetermined amount.

[0168] Whether the output data differs from the training output data by less than a predetermined amount can be determined, for example, using a distance function and / or a distance metric. Thus, in exemplary embodiments, determining the at least one model parameter of the mathematical model includes determining that a value of a distance function and / or distance metric that represents a difference between the training output data and output data determined using the at least one model parameter is less than or equal to a distance threshold.In other words, in exemplary embodiments, one or more model parameters of the mathematical model are adjusted based on the at least one training data set such that the mathematical model learns, based on input data that substantially correspond to the training input data, to output data that substantially correspond to the training output data. "Substantially correspond" can be understood, for example, as a deviation of less than a predetermined amount (e.g., by less than 20% or 10%). Whether a deviation is less than a predetermined amount can be determined, for example, using a distance function and / or distance metric.

[0169] Determining the at least one model parameter based on the at least one training data set (e.g. in the form of training the mathematical model based on the training data set) advantageously makes it possible to map complex non-linear relationships between variables that are represented by values ​​contained in the training data set.

[0170] In exemplary embodiments, the optimization function is part of the mathematical model. In other words, in exemplary embodiments, the mathematical model includes the optimization function. In this way, a desired optimization of a variable to be optimized can advantageously be taken into account in the mathematical model, and a less complex algorithmic architecture also advantageously results.

[0171] It is understood that the phrases “value of a parameter” and “value for a parameter” are used interchangeably in the present disclosure.

[0172] It is further understood that data within the meaning of the present disclosure, for example the sensor data, the measurement data, the (training) input data, the (training) output data and / or data disclosed hereinafter, comprise any type of information that can be read and / or processed by a processing device, such as the at least one control device, a processor, a system of one or more processors, and / or one or more computers, and which can be stored, in particular for this purpose, on a storage medium that is suitably connected directly and / or indirectly (e.g. directly, wired or wirelessly) to the at least one control device, the processor, the system of one or more processors, and / or to the one or more computers.

[0173] It is understood that information within the meaning of the present disclosure, for example the information on the at least one production factor and / or the information disclosed below, includes any type of computer-readable and / or electronically readable information that can be read and / or processed by a processing device, such as the at least one control device, a processor, a system of one or more processors, and / or one or more computers.

[0174] Further advantageous exemplary embodiments of the invention can be found in the following detailed description of some exemplary embodiments of the present invention, particularly in conjunction with the figures. However, the figures appended to the application are intended only for the purpose of illustration and not to limit the scope of the invention. The accompanying drawings are not necessarily to scale and are intended merely to reflect the general concept of the present invention by way of example. In particular, features contained in the figures should in no way be considered a necessary part of the present invention.

[0175] They show:

[0176] Fig. 1 is a schematic representation of an exemplary production plant for producing a building material panel and a control device; Fig. 2 is an exemplary flowchart illustrating a method according to an exemplary embodiment of the aforementioned aspect of the invention;

[0177] Fig. 3 is a schematic representation of exemplary aspects of an exemplary embodiment of a method according to said aspect of the invention;

[0178] Fig. 4 is a schematic representation of an exemplary embodiment of a device according to the said aspect of the invention, for example a mobile device.

[0179] Fig. 1 shows a schematic representation of an exemplary production plant 1 for producing a material board from particle material as an illustrative example of a building material board in accordance with the present disclosure. Fig. 1 further shows a schematic representation of a control device 200 connected to the production plant 1 for controlling and / or regulating the production plant 1, for example, via the schematically illustrated connection 400. For this purpose, the control device 200 can be configured to carry out the steps of the method according to the aforementioned aspect of the invention.For this purpose, the control device 200 can, for example, comprise a processing system such as a computer and / or a computer system connected to sensors and / or measuring devices (not shown) of the production plant 1, for example, to obtain target and / or actual values ​​of process parameters of sections or units of the production plant 1 from such sensors and / or measuring devices. Alternatively or additionally, the control device 200 can, in exemplary embodiments, comprise one or more mobile devices, for example one or more smartphones, one or more tablet computers, and / or one or more laptops.In exemplary embodiments, the control device 200 comprises one or more display devices, such as one or more screens, and / or is connected to one or more display devices in order to display, for example, values ​​for process parameters or values ​​for quality parameters, for example of a building material panel in production.

[0180] In exemplary embodiments, the control device 200 can comprise a plurality of control devices, of which a single control device can execute one or more steps of the method according to the aforementioned aspect of the present invention. For example, it may be possible for the control device 200, which is only schematically illustrated in Fig. 1, to comprise a processing unit, such as one or more computers, which are connected to sensors and / or measuring devices of the production plant 1 (wirelessly, wired, and / or via an internet connection), and, for example, a mobile device which is connected at least to the processing unit (wirelessly, wired, and / or via an internet connection).For example, it may be possible that, in particular, steps comprising a display and / or an input of data may, in exemplary embodiments, comprise a display and / or input of data using (for example a touchscreen) of a mobile device such as a smartphone.

[0181] Fig. 1 further shows a storage device (for example one or more hard disks and / or one or more cloud storage units), which can be provided, for example, for storing training data sets and is connected to the control device 200 via the schematically illustrated connection 500.

[0182] In exemplary embodiments, connections in accordance with the present disclosure, in particular the schematically illustrated connections 400 between the control device 200 and the production plant 1 (for example between the control device 200 and one or more sensors, measuring devices and / or control controllers of the production plant 1) and 500, in particular include direct or indirect wired communication connections (for example LAN connections), and / or direct or indirect wireless communication connections comprising radio connections such as Bluetooth, NFC, WLAN, 4G or 5G and / or communication connections via the Internet.

[0183] Fig. 1 shows a diagram of units, sections, or aggregates of the production plant 1 that can be used to manufacture the building material panels. In particular, the following sections of the production plant 1 are shown, which can be used for individual production steps in the manufacture of a building material panel: a chipper 2, a dryer for chips 3, a screening device 4, a device for providing the chips with a binding agent with mixers 5a, 5b, which also represent other devices with which binding agent is applied to the chips, further spreading devices 6, which spread the glued chips, optionally in several layers of different chip sizes, from several spreading heads 6a, 6b onto a forming conveyor belt 7 to form a mat, a continuous press 8, and a cutting or milling device 9 for dimensioning the finished building material panels.

[0184] The chippers 2 also symbolically represent the general reduction of wood into chips. The figure shows five knife-ring chippers, which are fed from a bunker above via screw conveyors. These can produce different chip sizes depending on the knife setting. The resulting chips, which vary in size and moisture content, are then passed on to dryer 3.

[0185] The screening device 4 shown in the figure can be used in various designs at different production points. This device can be used to separate fine particles (e.g., dust) or coarse particles (e.g., unwanted minerals or glue lumps) from the flow of chips. Screening devices 4 can also be used, for example, to achieve fractionation according to chip size during scattering, so that different layers of the final building board can be produced from chips of different sizes.

[0186] In the embodiment shown in Fig. 1, for example, two different chip size ranges are produced, which are fed from bunkers to a mixer 5a and a mixer 5b, respectively. In these mixers, the chips are at least partially wetted with binding agent.

[0187] Thus, it is possible to supply different chip sizes to the spreading heads 6a for the outer layers of the mat to be spread and pressed than to the spreading heads 6b for the middle layer.

[0188] The double-belt press 8, as used for the production of building material panels, particularly building material panels made of wood-based materials, has a basic design consisting of an upper press section with a heated upper pressure plate and a lower press section with a heated lower pressure plate. Frames, which also support pressure transducers for pressure application, connect the upper and lower press sections. In both the upper and lower press sections, endlessly circulating steel belts are guided around belt deflection pulleys, forming a press nip for applying pressure and temperature to the mat.

[0189] Furthermore, Fig. 1 also shows a chip size measuring device 10 (an example of a measuring device) downstream of the mixer 5. Optionally, a chip size measuring device 11 can also be provided upstream of the mixer. A representative selection of chips, for example, a very small amount of chips discharged from the transport process at a sampling point 20, can be measured in this chip size measuring device 10, 11.Exemplary process parameters that may be related to such chips measured by the chip size measuring device are, for example, a feed quantity of binding agent via glue nozzles (an example of a first process parameter), a feed quantity of chips (another example of a first process parameter), and / or a feed rate of chips through the mixer 5a, 5b (an example of a second process parameter), a rotational speed of a shaft of a mixer 5a, 5b (another example of a second process parameter), etc.

[0190] A method according to the said aspect of the present disclosure can be carried out in connection with a production plant according to Fig. 1, although it is understood that the present invention is not limited to the production plant according to Fig. 1.

[0191] According to exemplary embodiments, process parameters can in particular be process parameters of wood-based material production, for example process parameters of a defibration and gluing section of a production plant for the production of wood-based panels, in particular comprising one or more process parameters which are selected at least from:

[0192] • Amount of squeezed water;

[0193] • Steam addition cooker;

[0194] • Cooker fill level;

[0195] • Temperature cooker;

[0196] • Steam pressure cooker;

[0197] • Cooking time;

[0198] • Quantity of wood chips;

[0199] • Addition of paraffin;

[0200] • Energy absorption refiner;

[0201] • Temperature refiner;

[0202] • Steam pressure refiner;

[0203] • Grinding gap refiner;

[0204] • Grinding disc age;

[0205] • Blow valve opening;

[0206] • pH value of the fibers; amount of glue.

[0207] In exemplary embodiments, process parameters of a mat forming section of a production plant for producing wood-based panels may in particular comprise one or more process parameters selected at least from:

[0208] • Fiber output quantity;

[0209] • Spreading height;

[0210] • Forming belt speed;

[0211] • Basis weight of mat;

[0212] • Mat moisture;

[0213] • Spread;

[0214] • Pre-press pressures;

[0215] • Pre-press distances;

[0216] • Trimming width;

[0217] • Mat density;

[0218] • Quantity of spray water;

[0219] • Mat height forming belt end;

[0220] • Mat temperature;

[0221] • Spray height;

[0222] • Incorrect filling.

[0223] For such process parameters, corresponding sensors and / or measuring devices can be provided in a production plant, so that setpoint values ​​or actual values ​​corresponding to these process parameters can be made available to the at least one control device via corresponding communication connections.

[0224] In particular, it is possible that, for example, measured and / or set target or actual values ​​during the production of a building material board are saved together with corresponding timestamps, so that the corresponding values ​​for process parameters are available for a produced building material board at the respective points in time. As described, for building material board samples that are, for example, rejected for measurement in the laboratory, additional measured values ​​for certain properties (e.g. quality characteristics) can be obtained, which can be saved together with the values ​​for the process parameters in a training data set for the corresponding building material board sample. Furthermore, as also described, additional (measured) values ​​for ambient conditions and / or previous process parameters can be saved in a training data set for a corresponding building material board sample.

[0225] According to exemplary embodiments, quality features that can characterize a building material panel are in particular one or more quality features that are selected at least from:

[0226] • Transverse tensile strength;

[0227] • Flexural modulus of elasticity;

[0228] • Bulk density;

[0229] • Flexural strength;

[0230] • Lift-off strength

[0231] • Thickness swelling.

[0232] Thus, in exemplary embodiments, a training data set for a building material panel sample comprises values ​​(e.g., target and / or actual values) for at least one first and / or second process parameter, each with an associated time stamp, and values ​​(e.g., measured values ​​and / or laboratory measured values) for at least one property (e.g., a quality characteristic) of a building material panel sample.

[0233] Fig. 2 shows an exemplary flow chart representing an exemplary embodiment of the method 100 according to the aforementioned aspect of the present invention. The flow chart 100 can be understood as an illustration of an exemplary method for providing optimized process parameters of a production method for manufacturing a building material panel, for example using the production plant 1 according to Fig. 1. Without limiting the invention thereto, it is assumed below that method 100 is carried out by the control device 200 according to Fig. 1. However, in other exemplary embodiments, method 100 can be carried out by one or more processors of the control device 200 and / or by a plurality of control devices, wherein, for example, one or more processors and / or one or more of the control devices can carry out one or more steps of the method 100.

[0234] Fig. 3 shows a schematic representation of exemplary aspects of an exemplary embodiment of a method according to the aforementioned aspect of the invention. The devices, method steps, and (information) elements schematically illustrated in Fig. 3 serve to illustrate exemplary aspects of an exemplary embodiment of a method according to the aforementioned aspect of the present invention.

[0235] The steps 110 to 140 of the method 100 shown in Fig. 2 are therefore explained in more detail below with reference to Fig. 3, among other things.

[0236] As shown in Fig. 2, the method 100 comprises a step 110 of obtaining information on at least one production factor of a production process for manufacturing a building material panel. As shown in Fig. 3, the said information can be received or retrieved by the control device 200, for example, from a server 301 (an example of an external device) or retrieved or read from a database 302 (an example of a computer-readable storage medium) (steps 110a and 110b). In exemplary embodiments, the said information is obtained from an ERP system and / or from another source. The said information can, for example, correspond to time-dependent cost parameters such as material and energy prices, market revenues, etc. In exemplary embodiments, the automatic or automated adaptation of the optimization function (e.g.a cost function) and thus the dynamization by coupling a device or a system for autonomous process management with a commercial system.

[0237] The method 100 shown in Fig. 2 further comprises a step 120 of determining, based on the information on the at least one production factor and using an optimization function, at least one optimized first process parameter. The at least one optimized first process parameter is based on or corresponds to respective values ​​for at least one first process parameter of the production process that optimize the optimization function. Furthermore, each of the at least one first process parameter of the production process is related to at least one of the at least one production factor of the production process. The determination 120 can be carried out, for example, using the optimization function 20 shown in Fig. 3. As shown in Fig.3, the determination 120 of the optimized first process parameters can further take into account, for example, environmental conditions 41 under which the production method is carried out. As further illustrated in Fig. 3, the determination 120 of the optimized first process parameters can further take into account, for example, previous process parameters 42. As further illustrated in Fig. 3, the previous process parameters 42 can, for example, correspond to or be based on values ​​for first and / or second process parameters that were determined and provided at an earlier or previous point in time using the method 100 (cf. steps 140 and 151 in Fig. 3). The previous process parameters 42 can, for example, characterize a previous plant situation. As schematically illustrated in Fig. 3, the optimization function 20 can, for example, be stored at least temporarily on the control device 200.

[0238] In exemplary embodiments, the optimization function 20 is a cost function (or cost calculation function) C(t, P), which depends both on time t and on cost-relevant, controllable process variables P (an example of the at least one first process parameter), and into which the current material and energy prices and the achievable market prices for a building material panel to be produced are incorporated, which may, for example, be variable over time. For example, the achievable market price for a building material panel to be produced can be included as a (weighting factor) for the controllable system speed, the wood price can be included as a (weighting factor) for the controllable basis weight and thus a density of a building material panel to be produced at a given thickness, the glue price can be included as a (weighting factor) for the so-called gluing factor, and / or the energy price for gas, oil, biomass, etc.as a weighting factor for a controllable energy source consumption of a combined heat and power plant and / or a controllable flow temperature of thermal oil, to name a few non-limiting examples. In this way, when using a cost function as an optimization function, it can then be determined, for example, whether it is advantageous to increase the gluing factor (and thus dose more glue) but to be able to produce building boards at a higher speed, for example because the current market revenue (an example of a sales price) for the building board to be produced is high, or whether, conversely, it is more advantageous to reduce the plant speed in order to save glue, for example because the market sales price is low but the glue price is high. It is understood that the above explanations are merely examples and are not to be understood as limiting.

[0239] The method 100 shown in Fig. 2 further comprises a step 130 of determining, using a mathematical model, respective values ​​for at least one second process parameter of the production method. The respective values ​​for the at least one second process parameter are determined such that, when the production method is executed, at least one constraint associated with the building material panel is met based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter. As shown in Fig. 3, for example, both the optimization function 20 and the mathematical model 30 can be stored locally on the control device 200. As further shown in Fig.3, values ​​representing ambient conditions 41 under which the production process is carried out, as well as previous process parameters 42, can also be transferred as input data to the control device 200 and thus in particular to the mathematical model 30, and taken into account by the latter when determining the values ​​for the second process parameters. As further shown in Fig. 3, values ​​representing the constraints 43 associated with the building material panel are also transferred as input data to the control device 200 and thus in particular to the mathematical model 30. In exemplary embodiments, the constraints associated with the building material panel include a quality of the building material panel to be maintained, e.g., a quality that can be measured online and / or a quality that can be predicted online.As indicated by the arrow from the previous process parameters 42 to the constraints 43, in particular values ​​for online measurable quality properties (on which the constraints 43 can be based, for example) can be based on previous (and, for example, currently still measurable) process parameters 42.

[0240] In exemplary embodiments, the mathematical model is a machine learning unit, in particular for autonomous process control. The machine learning unit can be based, in particular, on reinforcement learning methods.

[0241] The method 100 illustrated in Fig. 2 finally comprises a step 140 of providing the at least one optimized first process parameter and the values ​​for the at least one second process parameter for use in the production process. As illustrated in Fig. 3, the optimized first process parameters and the values ​​for the second process parameters can, for example, be provided together and / or simultaneously by the control device 200. The at least one optimized first process parameter and the values ​​for the at least one second process parameter can, for example, be referred to as optimized process settings. As shown in Fig.3, the method according to the aforementioned aspect, in exemplary embodiments, further comprises a step 150 of checking whether the at least one optimized first process parameter and the values ​​for the at least one second process parameter are such that, when the production method is executed based on the at least one optimized first process parameter and the values ​​for the at least one second process parameter, at least one restriction of a control and / or regulation of the production method is taken into account (e.g., the dry chip bunker fill level must not fall below 20%). In exemplary embodiments, step 150 therefore corresponds to a technical and / or mechanical check of the process settings (e.g., the optimized first process parameters and / or the values ​​for the second process parameters).

[0242] As shown in Fig. 3, if the check is successful (branch "yes"), the optimized first process parameters and the values ​​for the at least one second process parameter can be provided, for example, for use in the production process. For example, if the check is successful, the specified parameters / values ​​can be adjusted in the production process. Consequently, the specified parameters / values ​​can then represent previous process parameters at a later point in time (see step 151).

[0243] If the test is not successful (branch “no”), as also shown in Fig. 3, the optimized first process parameters and the values ​​for the second process parameters can, for example, be discarded and / or further values ​​for the at least one second process parameter can be determined by reusing the mathematical model 30 (see step 152).

[0244] In exemplary embodiments, the method according to the aforementioned aspect can, for example, as described above, be used for autonomous process control of the production process for manufacturing a building material panel. In exemplary embodiments, the method according to the aforementioned aspect therefore evaluates, for example, based on a current process situation, which, within the range of technically possible / permitted values ​​for the various process parameters, taking into account the current and time-variable market and cost situation, lead to optimized costs or emissions, and then adjusts these, for example, autonomously in the production process. This can be understood, for example, as a dynamic process in the sense of a real-time control loop.In other words, in exemplary embodiments of the method according to the aforementioned aspect, the actual optimization goal is made dynamic by making the determination of the optimized process settings dependent on a situation prevailing during the production process (e.g., a cost and market situation) and adapting them automatically and / or independently to this. It is understood that the above explanations are merely exemplary and should not be understood as limiting.

[0245] It is further understood that the optimization function 20 and the mathematical model 30 are shown in Fig. 3 as separate units for illustrative purposes only and purely by way of example. As already explained above, the optimization function can, for example, be part of the mathematical model.

[0246] Fig. 4 is a schematic representation of an exemplary embodiment of a control device 200 configured to carry out the method according to the aforementioned aspect of the invention. The control device 200 may, for example, be comprised of a control device of a production plant.

[0247] The control device 200 comprises a processor 50, a program memory 51, a working memory 52, a user data memory 53, one or more communication interfaces 54, a recording unit 55, for example for recording actual or setpoint values ​​for one or more process parameters, and a user interface 56. In exemplary embodiments, the user interface 56 comprises:

[0248] • at least one keyboard and at least one screen,

[0249] • one or more means of speech input,

[0250] • one or more touchscreens, and / or

[0251] • a mobile device connected to the production facility, such as a smartphone, a tablet computer, a laptop.

[0252] In exemplary embodiments, the user interface is connected directly - wired and / or wirelessly - to the production plant and / or to the at least one control device and / or, for example, via an internet connection. In exemplary embodiments, a user interface comprises a display device such as one or more screens and an input device such as one or more keyboards, a computer mouse and / or an input / output device such as one or more touchscreens and / or means for voice input. In exemplary embodiments, the at least one control device comprises a mobile device such as one or more smartphones, one or more tablet computers and / or one or more laptops, wherein a user interface, in particular in these embodiments, comprises one or more touchscreens of a mobile device.A connection of the at least one control device via the Internet can advantageously enable remote control and / or regulation by a user, which can be particularly advantageous if a user is responsible for several production plants.

[0253] Processor 50 executes, for example, a program for implementing the aforementioned method according to the aforementioned aspect of the invention, which program is stored in program memory 51. Working memory 52 serves, in particular, to store temporary data during the execution of this program. Payload data memory 53 serves to store data required for program execution and can correspond to storage medium 250 in Figure 1.

[0254] The communication interface(s) 54 comprise one or more interfaces for communication of the device, in particular with the production plant 1 and / or at least with parts (for example one or more sensors and / or one or more measuring devices) of the production plant 1. The interface can be based on a wired and / or wireless (for example on cellular mobile radio (e.g. GSM, E-GSM, UMTS, LTE, 5G) or on WLAN (Wireless Local Area Network)).

[0255] The user interface 56 can be configured as a screen and keyboard or as a touch-sensitive display (touchscreen). The user interface 56 can be connected directly (e.g., wired) to the processor 50 and / or the control device 200, and / or (multiple user interfaces 56 can be provided) via a wired and / or wireless (e.g., based on GSM, E-GSM, UMTS, LTE, 5G, and / or WLAN (Wireless Local Area Network) technology) communication connection, for example, a communication connection including an internet connection, to the processor 50 and / or the control device 200. In the latter case, a remote connection to the control device 200 can be enabled, which, for example, allows a user to remotely access the control device 200 and thus, if necessary, operate multiple control devices 200.

[0256] The exemplary embodiments of the present invention described in this specification should also be understood as disclosed in all combinations with one another. In particular, the description of a feature encompassed by an embodiment should not be understood in this case - unless explicitly stated otherwise - to mean that the feature is indispensable or essential for the function of the exemplary embodiment. The sequence of the method steps described in this specification is not mandatory; alternative sequences of the method steps are conceivable - unless stated otherwise. The method steps can be implemented in various ways; for example, an implementation in software (by program instructions), hardware or a combination of both is conceivable for implementing the method steps.

[0257] Terms used in the claims such as "comprise," "have," "include," "contain," and the like do not exclude further elements or steps. The phrase "at least partially" encompasses both "partially" and "fully." The phrase "and / or" is intended to indicate that both the alternative and the combination are disclosed, thus "A and / or B" means "(A) or (B) or (A and B)." A plurality of units or the like, in the context of this specification, means multiple units or the like. The use of the indefinite article does not exclude a plurality. A single device may perform the functions of several units or devices recited in the claims. Reference numerals indicated in the claims are not to be construed as limitations on the means and steps employed.

Claims

Patent claims 1. A method, for example carried out by at least one device or a system comprising at least two devices, the method comprising: obtaining information on at least one production factor of a production process for producing a building material panel; Determining, based on the information about the at least one production factor and using an optimization function, at least one optimized first process parameter, wherein the at least one optimized first process parameter is based on or corresponds to respective values ​​for at least one first process parameter of the production process that optimize the optimization function, and wherein each of the at least one first process parameter of the production process is related to at least one of the at least one production factor of the production process; Determining, using a mathematical model, respective values ​​for at least one second process parameter of the production process such that, when the production process is executed based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter, at least one constraint associated with the building material panel is met; and providing the at least one optimized first process parameter and the values ​​for the at least one second process parameter for use in the production process.

2. The method according to claim 1, wherein the optimization function is dependent on the at least one first process parameter and / or wherein the optimization function is independent of the at least one second process parameter.

3. The method according to any one of claims 1 or 2, wherein the method further comprises: Controlling and / or regulating the production process for producing a building material panel based on the at least one optimised first process parameter and on the values ​​for the at least one second process parameter.

4. The method according to any one of claims 1 to 3, wherein the method further comprises: Checking whether the at least one optimized first process parameter and the values ​​for the at least one second process parameter are such that, when the production method is carried out, at least one restriction of a control and / or regulation of the production method is taken into account based on the at least one optimized first process parameter and on the values ​​for the at least one second process parameter; and o in a case where the check is successful, providing the at least one optimized first process parameter and the values ​​for the at least one second process parameter for use in the production method; o in a case where the check is unsuccessful, discarding the values ​​for the at least one second process parameter and / or determining further values ​​for the at least one second process parameter.

5. The method according to claim 4, wherein the at least one restriction of the control and / or regulation of the production process is conditioned by a production plant for carrying out the production process and / or is predetermined by a user of the production process.

6. The method according to one of claims 1 to 5, wherein compliance with the at least one secondary condition associated with the building material board corresponds to compliance with at least one predetermined quality criterion for the building material board.

7. The method according to claim 6, wherein the at least one predetermined quality criterion for the building material panel is measurable and / or predictable during the production process.

8. The method according to any one of claims 1 to 7, wherein the method further comprises: Obtaining information on at least one environmental condition under which the production process is carried out, and / or Obtaining respective values ​​for at least one previous process parameter of the production process; wherein determining the values ​​for the at least one second process parameter is based on the information about the at least one environmental condition and / or on the values ​​for the at least one previous process parameter.

9. The method according to any one of claims 1 to 8, wherein obtaining information on the at least one production factor comprises at least one of: Receiving the information from at least one external device; and / or Reading the information from at least one internal or external computer-readable storage medium.

10. The method according to any one of claims 1 to 9, wherein the method further comprises obtaining the mathematical model, and wherein obtaining the mathematical model comprises: Obtaining at least one training data set comprising training input data and training output data; and Generating the mathematical model based on the at least one training data set.

11. The method of claim 10, wherein generating the mathematical model based on the at least one training data set comprises determining at least one model parameter of the mathematical model such that, when using the training input data as input data, the mathematical model outputs output data that differs from the training output data by less than a predetermined amount.

12. The method according to any one of claims 1 to 11, wherein the optimization function is part of the mathematical model.

13. The method according to any one of claims 1 to 12, wherein the optimization function comprises at least one of: • a cost function; • a profit function; • an emission function; and / or • a sustainability function.

14. Device or system comprising at least two devices, arranged to carry out and / or control the method according to one of claims 1-13 or comprising respective means for carrying out and / or controlling the steps of the method according to one of claims 1-13.

15. A computer program comprising program instructions that cause one or more processors to execute and / or control the method according to any one of claims 1-13 when the computer program is executed on the processor or the multiple processors.

16. Building material panel produced by a process comprising the process according to any one of claims 1-13.

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