Device for determining the hygienic characteristics of sanitary products

Abstract

The present invention relates to a method for determining the hygienic properties of a sanitary product. The sanitary product includes a layer of superabsorbent material. In the first step, an injection model of the sanitary product is received, which includes a) one or more absorption properties of the superabsorbent material, and b) the time-dependent injection of a predetermined liquid into the superabsorbent material layer of the sanitary product. A sanitary product property determination model is used to determine the hygienic properties of the sanitary product based on the absorption properties and the injection model. Based on the determined hygienic properties of the sanitary product, control data is generated to control the production process of the sanitary product and / or the superabsorbent material.

Description

[Technical Field]

[0001] The present invention relates to an apparatus, method, and computer program product for determining the hygienic properties of sanitary products. Furthermore, the present invention relates to a system, method, and computer program product for controlling the production of sanitary products and / or superabsorbent materials. [Background technology]

[0002] Many modern sanitary products utilize superabsorbent materials, often in the form of superabsorbent particles, for fluid absorption. However, even for experts, predicting how each superabsorbent material will affect the performance parameters of sanitary products, particularly their hygienic properties, is often difficult. Therefore, current sanitary products are developed through trial and error and stepwise development techniques. Consequently, being able to quickly and accurately predict the hygienic properties of sanitary products would be advantageous in controlling the production process of sanitary products and / or the superabsorbent materials used in them. [Overview of the Initiative] [Problems that the invention aims to solve]

[0003] The object of the present invention is to provide apparatus, methods, and computer program products that enable improved control of the production process of sanitary products and / or superabsorbent materials, improved determination of the hygienic properties of sanitary products, and in particular, enable the continuous or batch production of sanitary products and / or superabsorbent materials while satisfying predetermined hygienic properties. [Means for solving the problem]

[0004] In a first aspect of the present invention, an apparatus for determining the sanitary properties of a sanitary product is presented, wherein the sanitary product comprises a layer of superabsorbent material provided in the form of superabsorbent particles, and the apparatus includes i) a) one or more absorption properties of the superabsorbent material, and b) an injection model of the sanitary product comprising the time-dependent injection of a predetermined liquid into the superabsorbent material layer of the sanitary product, ii) a sanitary product property determination model for determining the sanitary properties of the sanitary product based on the absorption properties and the injection model, and iii) one or more processors configured to generate control data for controlling the production process of the sanitary product and / or superabsorbent material based on the determined sanitary properties of the sanitary product.

[0005] The inventors have discovered that it is possible to predict the hygienic properties of sanitary products using a characterization model based on the absorption properties of the superabsorbent material for a given liquid within the sanitary product, and based on an injection model that shows the time-dependent injection of the given liquid into the superabsorbent material within the layers of the sanitary product. Since the model is based on only these two input parameters, the prediction of hygienic properties becomes efficient without the need to initially collect a vast amount of measurement data. This enables fast and computationally inexpensive predictions so that control data for controlling the production process of sanitary products, for example, for directly manipulating the production process of sanitary products and / or superabsorbent materials, can be generated based on the determined hygienic properties.

[0006] Generally, the device may refer to any general-purpose or dedicated computing device adapted to perform the functions of the device, for example, by running a specific computer program. In particular, the device may be implemented in any form of software and / or hardware that causes a general-purpose or dedicated computing device to perform the functions defined above. Furthermore, the device may be implemented in the form of a standalone device, for example in the form of dedicated hardware or by being installed in a user's computer system, but it may also be implemented in the form of a network of computers or processors, for example in a shared computing regime such as cloud computing or network computing, where two or more computers or processors can provide the functions of the device.

[0007] Generally, the device is adapted to determine the hygienic properties of a sanitary product. A sanitary product can be any product used for private hygienic reasons, for example, for the excretion of a human or pet. In particular, a sanitary product is configured to absorb bodily fluids. Preferably, a sanitary product refers to a diaper. However, a sanitary product can also refer to any other product configured to absorb bodily fluids, such as feminine hygiene products or medical sanitary products. Hygienic properties can refer to any properties of a sanitary product that affect its hygiene. In particular, since a sanitary product is a fluid absorbent product, hygienic properties refer to properties that indicate the fluid absorption of the sanitary product. Preferably, hygienic properties indicate the amount of free fluid in the sanitary product. More preferably, hygienic properties indicating the amount of free fluid in the sanitary product refer to the maximum amount of free fluid in the sanitary product after a certain amount of applied fluid and / or after an absorption time, i.e., the time required to absorb a certain amount of free fluid until a predetermined minimum amount of free fluid is reached. Preferably, the predetermined minimum amount of free fluid is zero, so that no free fluid is present in the sanitary product at the end of the absorption process. However, in some applications, a specific amount of free fluid may be acceptable over long periods, and consequently, in these cases, the minimum amount of free fluid may be greater than zero and set to the maximum amount of free fluid that is acceptable over long periods in this application. Another preferred hygienic property is the time it takes for the fluid to be absorbed into the sanitary product, which is the time it takes for the fluid to be completely collected in the sanitary product. In one embodiment, the hygienic properties may include or be derived from the free fluid and / or the time it takes for the fluid to be absorbed.

[0008] To absorb fluids, sanitary products include a layer of superabsorbent material provided in the form of superabsorbent particles. Superabsorbent material is a material capable of absorbing and retaining large amounts of aqueous liquid relative to its own mass. For example, in the case of deionized and distilled water, superabsorbent material can absorb up to 1000 times its own weight. For practical applications in hygiene, superabsorbent material absorbs a 0.9 wt% saline solution (NaCl) of at least 15 g / g, typically at least 20 g / g, preferably at least 25 g / g, most preferably at least 30 g / g, but no more than 120 g / g, preferably no more than 100 g / g, more preferably no more than 80 g / g, and most preferably no more than 60 g / g, in the absence of external pressure, for example, in the tea bag method CRC. Absorption by superabsorbent polymers is particularly useful compared to conventional absorbents such as cellulose fluff, because, even under the pressure of use in sanitary products, the absorbed liquid is not released and the wearer's skin remains dry. In most cases, superabsorbent materials contain superabsorbent polymers (SAPs), often provided in the form of multiple particles forming the superabsorbent material. Superabsorbent polymers typically consist of hydrophilic and ionic groups supporting high molecular weight polymer chains, which are interconnected to make the superabsorbent polymer water-insoluble. The ionic groups are typically -COOH, but can also be based on sulfur (-SO3H) or phosphorus as the source of acidity. These groups are partially neutralized to achieve a pH that is gentle on the wearer's skin, typically pH=4.0–7.5, preferably pH=5.0–6.5. Any alkali metal neutralizing agent (Li, Na, K, Rb, Cs) can be used as a means of neutralization, but Na is preferred for hygienic applications. Typically used neutralizing agents are alkali metal salts of hydroxides, carbonates, and bicarbonates, as well as mixtures thereof. Such neutralizing agents may be used in the form of a molten material, powder, liquid, or aqueous solution, or as a mixture of two or more of these physical forms in a sequential or simultaneous neutralization process.Examples of such superabsorbent polymers include crosslinked sodium poly(meth)acrylate, crosslinked sodium polyitaconate, polyacrylamide copolymers, ethylene maleic anhydride copolymers, crosslinked carboxymethylcellulose, crosslinked starch derivatives and carboxymethyl starch, polyvinyl alcohol graft or starch graft crosslinked partially neutralized polyacrylate, polyvinyl alcohol copolymer, and crosslinked polyethylene oxide. Copolymers of acrylic acid, maleic acid, and itaconic acid may also be used and may be combined with copolymerized nonionic hydrophilic or hydrophobic monomers. Partially neutralized crosslinked polyacrylic acid and polyitaconate and their copolymers are preferred. Partially neutralized crosslinked polyacrylic acid and polyitaconate and their copolymers derived from biological sources, such as plants, microorganisms, algae, and fungi, are more preferred. Most preferred is a superabsorbent production process for producing the superabsorbent polymers of the present invention having a partially neutralized crosslinked polyacrylic acid and polyitaconate and their copolymers and the lowest possible carbon footprint.

[0009] The apparatus, therefore, includes one or more processors capable of performing the functions of the method described below. For example, in a step performed by a receiving unit of the apparatus, which is realized by one or more processors, one or more absorption properties of superabsorbent materials used in sanitary products are received. In particular, the absorption properties of superabsorbent materials may be received, for example, by accessing a storage unit in which each absorption property is already stored. Such absorption properties of superabsorbent materials may be stored, for example, in a database or in a superabsorbent material library filled with multiple different superabsorbent materials and their associated absorption properties. Such a database or library may be generated by performing experiments and measurements of the absorption properties of multiple superabsorbent materials or by simulations of the absorption properties of each superabsorbent material. Receiving one or more absorption properties of superabsorbent materials may then include, for example, receiving superabsorbent materials via user input or automatic determination and accessing the respective database or library to receive the respective absorption properties stored in the database or library in relation to the received superabsorbent materials. However, one or more absorption properties may also be received, for example, via an input unit, from a user providing each absorption property. Furthermore, the absorption properties of each superabsorbent material can also be directly obtained from the respective measurement setups in which those absorption properties were measured for the superabsorbent material.

[0010] Preferably, the absorption characteristics refer to at least one of absorption capacity, swelling dynamics, and permeability. Absorption capacity can be determined as either centrifugal retention capacity (CRC), free swelling capacity (FSC), or pressure absorption capacity (AAP). Generally, CRC and FSC are determined without external pressure, i.e., at 0.0 psi, and in either case, the higher the respective CRC or FSC value, the more fluid can be absorbed by the particle. Swelling dynamics can refer to either VAUL, T20, or Vortex. For irregularly shaped, rough surface particles, these three quantities correlate. For particles with regular, smooth surfaces or circular shapes, Vortex may not correlate with the other quantities. Generally, the faster the particle swells, the smaller the value of any one of the quantities. Permeability (SFC) correlates nonlinearly with CRC capacity. Generally, the higher the permeability value, the better the fluid is distributed in the particle's rotational region. CRC may be interpreted as the mere absorption capacity of the superabsorbent material, SFC as the mere permeability of open pores in an expanded gel bed which is an expanded superabsorbent material, and FSC or AAP as the absorption capacity of the superabsorbent material under defined external pressure conditions, each including contributions from the expanded superabsorbent material and contributions from partially or completely liquid-filled pores in the resulting gel bed (interstitial fluid). T20, Vortex, and VAUL characteristic swelling times may be interpreted as dynamic swelling rate parameters describing the rate of swelling and may include additional effects other than the absorption rate (e.g., particle morphology and surface tackiness may affect these measurements). The rate at which liquid is absorbed by swellable superabsorbent material particles is defined as the absorption rate. These properties and the methods for determining each of them are further described below. Various other forms of properties or methods for determining each of these properties exist and may also be used as technical application properties according to the present invention. Other methods may vary, for example, by the dimensions of the device, such as whether the AAP cells or permeable cells are smaller or larger; the handling technique; the test solution, such as water or artificial urine instead of saline; and the swelling time, such as 1, 3, 5, or 10 minutes instead of 30 minutes. In general, the choice of absorption properties may depend on the intended use of the sanitary product, for example, as a diaper or medical product.Particularly useful methods for measuring absorption properties are described in International Publication No. 2021 / 001221, which enable the determination of the time-dependent swelling profile of superabsorbent polymers under various external pressures. Thus, characteristic fingerprint curves that can be used to define the absorption properties are obtained. In-line analytical methods, such as those disclosed in International Publication No. 2020 / 109601, which enable the determination of absorption properties by Raman spectral analysis within the production process, are particularly useful. The combination of such in-line techniques with in-line particle size determination enables highly efficient use cases in the present invention. In particularly preferred embodiments, one or more absorption properties of the superabsorbent material exhibit at least one of permeability, absorption capacity, and absorption rate. More preferably, the absorption property is the permeability of the superabsorbent material. Most preferably, the absorption property is a combination of permeability and absorption rate.

[0011] Superabsorbent materials are provided in the form of superabsorbent particles containing a superabsorbent polymer. For most applications, the size of the superabsorbent particles is preferably 100 μm to 850 μm. However, for some applications, larger or smaller superabsorbent particles may also be preferable. Recently, a narrower particle size distribution has been required for some physiological products that are far more difficult and expensive to produce and whose technical properties are difficult to optimize, such as having lower particle sizes of 100, 150, 200, or 250 μm and higher particle sizes of 700 μm, 600 μm, or 500 μm.

[0012] Preferably, each superabsorbent particle comprises a) an interconnected core and b) a surface-crosslinked shell having higher connectivity than the core. In this context, the terms “interconnected” and “connectivity” mean that the polymer chains of the core or shell portion of the superabsorbent polymer particle are physically entangled and crosslinked ionically or covalently, so that each portion of the superabsorbent particle is water-swellable but not water-soluble. Combinations of such methods of interconnecting polymer chains are possible and are typically found in superabsorbent particles. Crosslinking by ions can be achieved by polyvalent cations, a practical example being Mg 2+ Ca 2+ Sr 2+ Al 3+ Ti 4+ , Zr 4+This is the case. Crosslinking via covalent bonds can be achieved by adding a difunctional or polyfunctional ethylenically unsaturated crosslinking agent for polymerization to the monomer mixture. Alternatively, this functionality can also be provided by groups that can undergo esterification or transesterification. Mixed functionality in one molecule is also possible. For surface crosslinking, the same compounds as those described above can be used. Typically, ionic crosslinking agents and covalent crosslinking agents are used in combination. Examples of core and surface crosslinking are described in WO 2019 / 197194 pamphlet, which is incorporated herein by reference. In the present invention, it is understood that the shell and core of the superabsorbent particles are linked to each other by physical entanglement or crosslinking by ions or preferably covalent bonds. Such a core-shell structure can break the surface-shell of the superabsorbent particles upon swelling, but due to the connectivity of the shell to the core, even if the shell is completely broken, a physical force will continue to be applied to the swollen core. Preferably, the superabsorbent particles refer to post-crosslinked superabsorbent polymer particles. Such post-crosslinked superabsorbent polymer particles include a crosslinked and thus interconnected core, and are then brought about by a post-crosslinking process using a shell having a higher connectivity than the core, while this shell is covalently bonded to the underlying core. Optionally, the superabsorbent particles provided as such can be provided with an additional non-superabsorbent coating. Non-limiting examples of such coatings are polymers or polymer films for improving fluidity or damage stability, powder coatings (silica, alumina, clay or other inorganic powders in their dry or hydrated form) for preventing caking, additives for preventing aging or discoloration, additives for suppressing bad odors or functional coatings that react with the surface such as salts of Ca 2+ , Mg 2+ , Al 3+ and Zr 4+ or their soluble hydroxides.

[0013] Furthermore, an injection model of the sanitary product is received. In this case, the injection model may be received by accessing a storage unit in which one or more injection models are already stored, or by receiving input from the user, for example, via user input. The injection model includes at least information about the time-dependent injection of a given liquid into the superabsorbent material layer of the sanitary product. Thus, the injection model provides information about the time-dependent amount of fluid reaching the superabsorbent material layer of the sanitary product to enable the simulation of different application scenarios. For example, the injection model may include one or more amounts of fluid in the superabsorbent material layer for time curves corresponding to different application scenarios. Furthermore, the injection model, in particular the time-dependent injection of a given liquid into the superabsorbent material layer, may also implicitly include information about the respective compositions and structures of the sanitary product surrounding the superabsorbent material layer. For example, a particular layer used in the sanitary product may delay the arrival of the fluid introduced into the sanitary product into the superabsorbent material layer, while other compositions or structures of the sanitary product may result in rapid concentration of the fluid introduced into the sanitary product into the superabsorbent material layer. Therefore, these compositions and structures of sanitary products can affect the time-dependent infiltration of liquid into the superabsorbent material layer. Depending on the intended use of the sanitary product, such effects can be taken into account, and a time-dependent infiltration of a given liquid into the superabsorbent material layer can be provided accordingly. For example, measurements can be performed in the laboratory for each application case for different compositions and structures of sanitary products to determine the time-dependent infiltration of a given amount and composition of liquid into the superabsorbent material layer. The respective information, i.e., the infiltration model, can then be obtained, for example, by user input indicating each sanitary product and its respective application case, and then by accessing each database in which the corresponding infiltration models for one or more application cases are stored. However, if the composition and structure do not strongly affect the infiltration model, a standard infiltration model for one or more application cases may also be provided and accessible to obtain the infiltration model.

[0014] Furthermore, one or more absorption properties may influence the injection model. In particular, the permeability of the superabsorbent material can determine the amount of liquid reaching the superabsorbent layer over time. Therefore, in a preferred embodiment, the injection model depends on the permeability of the superabsorbent material. In this case, injection models with different permeability may be stored on their respective storage, and receiving may include selecting each injection model from storage based on the permeability of the superabsorbent material. However, receiving an injection model may also include modifying a standard injection model based on the received permeability, for example, by correcting the amount of liquid reaching the superabsorbent layer over time based on the permeability of the superabsorbent material as needed. Preferably, the injection model includes, for example, the permeability of the superabsorbent material and the permeability provided by the sanitary product, if it includes a liquid management element that can replace some or all of the permeability of the superabsorbent material. The liquid management element may be embedded in the superabsorbent material layer or placed above or below the superabsorbent material layer. Examples of embedded liquid management elements include synthetic resin fibers, cellulose fibers, crosslinked cellulose fibers, porous fabrics, channel structures, and profiled distributions of superabsorbent material inside a core. Examples of adjacent liquid management elements, typically positioned on top of, for example, the layer facing the wearer's body, are acquisition and distribution layers in the form of perforated films, nonwovens, cross-linked cellulose fibers, polymer resin top sheets, etc. Such liquid management elements provide porosity to the superabsorbent material layer containing the superabsorbent material, or provide porosity adjacent to the superabsorbent material layer. This allows for rapid liquid distribution across or within the superabsorbent material layer. As a result, the superabsorbent material may be provided with the required permeability at the expense of greater absorbency. Liquid management elements may be used in combination with the permeability of the superabsorbent material. One or more liquid management elements may be used in sanitary products, particularly diapers. Preferably, each injection model takes into account the product characteristics described above.

[0015] Furthermore, the device then utilizes a sanitary product characteristic determination model to determine the hygienic properties of sanitary products based on absorption and infusion models. The sanitary product characteristic determination model can be any model that enables the determination of the hygienic properties of sanitary products based on absorption and / or infusion models. In particular, the sanitary product characteristic determination model is a mathematical model. In one embodiment, the sanitary product characteristic determination model may be a data-driven model parameterized based on historical measurement data of hygienic properties dependent on absorption and infusion models, for example. Specifically, the term "data-driven" defines that the model is based primarily on its respective data inputs and not on, for example, intuition, personal experience, or knowledge. The characteristic determination model can be implemented as any machine learning-based model based on known machine learning algorithms, such as neural networks, regression models, and classification algorithms.

[0016] White-box models evaluated with nonlinear regression optimizers may also be used in the present invention. Such machine learning models may be used as part of a comprehensive process control model, optionally considering other formulation and process parameters using other machine learning and artificial intelligence algorithms. Generally, such machine learning-based characterization models include one or more model parameters that can be determined based on each training data. Thus, parameterization of a characterization model is the determination of the values ​​of each one or more model parameters based on the training data in the model training process. In particular, the characterization model is parameterized so that it can determine the hygienic properties of a sanitary product based on the injection model and absorption properties. Generally, known training methods for parameterizing a given model may be used to appropriately parameterize a characterization model. In particular, optimization methods may be used to find the best fit of the model parameters to each training data. For training a characterization model, preferably, historical data may be used as historical data including training data, for example, measurement data from each measurement of the hygienic properties of a plurality of sanitary products having each different superabsorbent material layer subjected to different injection scenarios.

[0017] However, in a preferred embodiment, the physiological product characteristic determination model is based on an ordinary differential equation or a partial differential equation that determines the influence of the injection model of the hygiene characteristics and the absorption characteristics of the superabsorbent material. Preferably, it is the device according to any one of the preceding claims, and the physiological product characteristic determination model includes solving the following differential equation.

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[0018] Furthermore, the device is configured to generate control data for controlling the production process of sanitary products and / or superabsorbent materials based on the determined hygienic properties of the sanitary products. The control data may refer to any data that may have some effect on the production process of sanitary products. For example, the control data may directly include information on the respective production process parameters of sanitary products and / or superabsorbent materials. However, the control data may also include more general information that enables correction of production process parameters only in combination with a production process control application. Therefore, the control data may be provided in any suitable format. For example, the control data may be provided in a format that allows for direct implementation of the control data in a production process control application. However, the control data may also be provided in a format that must first be translated into the respective format. In general, the control data may be provided directly for the control of the production process, or it may be provided to the user first, for example, for a security check, and the control data is implemented only if the user accepts the control data. Preferably, the method includes relaying the control data to a production control system for the production process.

[0019] In one embodiment, one or more received absorption properties are measured during the production process of superabsorbent materials and / or sanitary products containing superabsorbent materials, and the generated control data is configured to control and / or monitor the production process based on sanitary properties determined from one or more measured absorption properties. In particular, the determined sanitary properties may be evaluated against a predetermined target sanitary property, and the control data may be generated based on comparison. For example, if the determined sanitary property deviates outside a predetermined boundary from the target sanitary property, control and / or monitoring actions may be taken, such as notifying the operator, changing one or more production parameters, changing the formulation, changing the throughput in the polymerization reactor, modifying gel grinding or gel drying, stopping the chemical reaction, or modifying the milling or sieving procedure, or modifying the post-crosslinking or coating step. The measured absorption properties may include particle size distribution and / or particle crosslinking properties. Preferably, Raman spectroscopy is used to monitor the chemical reaction of the crosslinking process of superabsorbent particles during the production process and to determine the thickness of each crosslinking shell of the superabsorbent properties. Optical measurements may be used to determine the size distribution of each particle during the production process. One or more absorption properties may be measured continuously during the chemical production process for producing superabsorbent materials, meaning that measurements are taken continuously at predetermined time intervals much smaller than the production process itself. Direct measurement of the absorption properties of superabsorbent particles during the production process allows for monitoring of the resulting sanitary properties of the final product and enables modification of process parameters if the sanitary properties deviate from predetermined targets. In particular, in-situ measurement during the production process avoids delays in process control that might arise from laboratory measurements of absorption properties, thus leading to direct control and monitoring.In one embodiment, one or more processors are further configured to receive target hygiene characteristics of a sanitary product, compare the determined hygiene characteristics with the target hygiene characteristics, and i) determine the superabsorbent material as the target superabsorbent material of the sanitary product if the determined hygiene characteristics are within a predetermined range around the target hygiene characteristics, and ii) determine a new superabsorbent material if the determined hygiene characteristics are outside the predetermined range around the target hygiene characteristics, and to repeat the determination of the hygiene characteristics of the sanitary product using the new superabsorbent material, and the control of the production process is based on the determined target superabsorbent material. Preferably, determining a new superabsorbent material includes correcting the size distribution of the particles forming the superabsorbent material and / or the amount of superabsorbent material in the layer. Generally, the size distribution of the particles forming the superabsorbent material can greatly affect the absorption properties of the superabsorbent material, so by correcting the size distribution, it is also possible to change the absorption properties of the superabsorbent material and thus potentially satisfy the target hygiene characteristics. However, it is also possible to provide a completely different superabsorbent material as the new superabsorbent material, for example, a superabsorbent material having a different composition or formed from a different superabsorbent polymer. Furthermore, new superabsorbent materials can also be determined by determining different amounts of superabsorbent material in each superabsorbent layer. Generally, since at least some absorption properties of a superabsorbent material depend on the amount of superabsorbent material present in the layer, changing the amount of superabsorbent material can also change these superabsorbent properties, and thus potentially make it possible to satisfy each target sanitary property. Moreover, all of the above parameters can be changed in combination. Generally, the determination of a new superabsorbent material can be based on an iterative method of correcting each property additionally or alternatively, according to each predetermined rule, until the target sanitary property is met within a predetermined limit.For example, a given rule may determine during the first iteration, for instance, by using a gradient method to determine the new particle distribution at each iteration step, that the size distribution of the particles forming the superabsorbent material is corrected. After a number of predetermined steps, or after reaching a predetermined particle size distribution limit, e.g., an upper or lower limit on particle size, the rule may determine that for the next iteration, the amount of superabsorbent material in the superabsorbent layer is corrected by a predetermined increment at each iteration step. If the objective is still not met after reaching a predetermined limit on the amount of superabsorbent material in the layer, e.g., a predetermined upper limit on the amount of superabsorbent material in the layer, the rule may further define that for the next iteration, the superabsorbent material itself is changed to a different composition, and the iteration is then performed again for the particle size distribution of the superabsorbent material.

[0020] In a preferred embodiment, instructions are received regarding the amount of superabsorbent material in the sanitary product layer, and one or more absorption properties of the superabsorbent material are adapted based on the amount of superabsorbent material in the sanitary product.

[0021] In a preferred embodiment, the apparatus further includes one or more processors configured to determine one or more absorption properties of a superabsorbent material based on the received particle size distribution of the superabsorbent material using an absorption property determination model, wherein the property determination model is a data-driven model, parameterized to be adapted to determine the technical application properties of superabsorbent particles based on particle size, and the determined one or more absorption properties are then utilized in a hygiene property determination model. Preferably, the superabsorbent particles of the superabsorbent material include a superabsorbent polymer provided in the form of i) interconnected cores and ii) a surface crosslinked shell having higher connectivity than the cores, and the provided absorption property determination model is further parameterized based on the core size and shell size of the superabsorbent particles.

[0022] Next, one or more processors are further configured to utilize an absorption property determination model for determining the absorption properties of superabsorbent materials based on particle size. In particular, the absorption property determination model is implemented as a parameterized data-driven model, for example, based on historical measurement data, so as to be adapted to determine the absorption properties of superabsorbent particles based on particle size. Preferably, the absorption property determination model can be implemented as any machine learning-based model based on known machine learning algorithms such as neural networks, regression models, and classification algorithms. White-box models evaluated using a nonlinear regression optimizer are particularly useful in the present invention. Generally, the absorption property determination model includes one or more model parameters that can be determined based on each training data. Therefore, parameterization of the absorption property determination model is the determination of the values ​​of each of the one or more model parameters based on the training data in the model training process. In particular, the absorption property determination model is parameterized so as to be able to determine the absorption properties of superabsorbent particles based on particle size. Generally, known training methods for parameterizing a given model can be used to appropriately parameterize the absorption property determination model. In particular, optimization methods can be used to find the best fit of the model parameters to each training data. Preferably, historical data can be used as training data for training an absorption property determination model, for example, historical data including measurement data from each measurement of the absorption properties of superabsorbent particles or data derived from known physical relationships between the absorption properties of superabsorbent particles and each measurable property. In particular, historical data may include multiple different particle sizes of superabsorbent particles corresponding to one or more absorption properties.

[0023] Since the production process of superabsorbent particles can have a significant impact on the specific composition of the superabsorbent particles, for example, on the specific interconnectivity between the core and shell of the superabsorbent particles, it is preferable that the historical datasets for each specific production process for each superabsorbent material produced be used to parameterize the absorption property determination model. This allows the absorption property determination model to provide a highly accurate determination of the absorption properties of superabsorbent materials produced by a particular production process. However, in other embodiments, the absorption property determination model may also be trained using a more general historical dataset containing data on superabsorbent materials utilizing different production processes, in which case the absorption property determination model can then learn to distinguish between superabsorbent materials produced by different production processes, with each production process being provided as further input to the absorption property determination model. Furthermore, the absorption property determination model may be trained to determine one absorption property of a superabsorbent material, but it may also be trained to predict two or more absorption properties of a superabsorbent material.

[0024] In preferred embodiments, the absorption property determination model used is further parameterized based on the core size and shell size of the superabsorbent particles. Surprisingly, the inventors have found that further parameterizing the absorption property determination model based on the core size and shell size of the superabsorbent particles enables particularly accurate determination of the absorption properties. Furthermore, by further parameterizing the absorption property determination model based on the core size and shell size of the superabsorbent particles, it becomes possible to isolate the respective influence of each of these parameters on the absorption properties. In general, the core size and shell size of superabsorbent particles depend on the particle size, i.e., the depth of penetration of the material used in the post-crosslinking process is substantially the same for all particle sizes, just as the shell and core sizes, i.e., volume, depend mainly on the particle size. However, the overall depth of penetration of the post-crosslinking material, and therefore the thickness of the shell relative to the core, depends on the crosslinking procedure used, e.g., the material used, pressure conditions, additives used, temperature, etc. Therefore, by further separating the effects of core and shell size on absorption properties, it becomes possible not only to utilize the size of superabsorbent particles to control absorption properties, but also to determine the effects of shell and core size on absorption properties, and thus to optimize the post-crosslinking procedure of superabsorbent particles with respect to technical application characteristics.

[0025] Preferably, parameterizing the absorption property determination model used includes determining performance parameters that quantify the respective contributions of the core size and shell size of the superabsorbent particle to the absorption property. By using separate training datasets for multiple superabsorbent particle sizes, each containing the corresponding core size, shell size, and absorption property, the absorption property determination model can be parameterized so that the influence of core size and shell size on the absorption property can be accurately quantified by determining the performance parameters. Preferably, the absorption property determination model used is based on the following relationship between the absorption property and the size of the superabsorbent particle.

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[0026] In one embodiment, the received particle size is the particle size distribution of superabsorbent particles in the superabsorbent material. In this case, based on the particle size distribution, one or more particle size classes from a given particle size class can be determined, each containing particles of a specific size. The absorption properties can then be determined for the determined particle size classes, and the overall applicability properties of the superabsorbent material can be determined based on the absorption properties determined for each determined particle size class, and also based on the particle size distribution. Generally, the particle size distribution of superabsorbent particles can be received in the form of any data information indicating the particle sizes present in a statistically relevant sample of the superabsorbent material. For example, the particle size distribution can be provided in the form of a list of all sampled superabsorbent particles and their corresponding sizes. However, the particle size distribution can also be directly provided in the form of a class distribution indicating the amount of particles present in each class of a statistically relevant sample for multiple particle size classes. Generally, a particle size class refers to a range of particle sizes and is defined by a minimum and maximum particle size that define the range of particle sizes. When the particle size distribution is provided in the form of a class distribution, each predetermined particle size class may refer to a particle size class that has already been used. In this case, determining whether a particle exists within a predetermined particle size class is equivalent to determining whether the amount of particles greater than zero is indicated by the particle size class distribution within each particle size class. However, a predetermined particle size class may be independent of any particle size class previously used to provide the particle size class distribution. In this case, each statistical method can be used to determine which of the predetermined particle size classes is present in the superabsorbent material. Furthermore, when a list of particle sizes is provided as a particle size distribution, the particle sizes can be sorted appropriately using the predetermined particle size classes to determine whether at least one particle exists for each predetermined particle size class.Preferably, for example, the particle size distribution of superabsorbent polymer particles can be determined by the test method recommended by EDANA, number WSP220.3(11) "Particle Size Distribution". Optical methods, such as laser diffraction, photoanalysis, beam alignment, and spatial filter kinetics (Parsum® probe), can also be advantageously utilized and preferably calibrated against EDANA or corresponding ISO test methods based on screening analysis. Such calibration may depend on other particle properties besides particle size and is therefore performed specifically for each production grade. In the present invention, such calibrated methods are particularly useful because they can be used inline in the production process at one or more locations and can provide the necessary particle size information in real time.

[0027] Next, the absorption characteristics for the determined particle size class are determined by using an absorption characteristic determination model for each particle size that falls within a given particle size class. Generally, the absorption characteristics can be determined by providing the absorption characteristic determination model with at least one particle size that falls within a given particle size class, and by using the determined absorption characteristics as a technically applicable characteristic for all sizes that fall within the determined particle size class. However, the minimum and maximum particle sizes that fall within each determined particle size class may also be used as input to the absorption characteristic determination model, and the determined absorption characteristics can be statistically combined, for example, by averaging them to determine the absorption characteristics that represent each determined particle size class. However, other statistical methods may also be used as appropriate. Next, the overall absorption characteristics can be determined based on the determined absorption characteristics for each determined particle size class and based on the particle distribution. In particular, the amount of particles that fall within each determined particle size class is taken into consideration when determining the overall absorption characteristics. For example, a weighted average may be used to determine the overall absorption characteristics based on the determined absorption characteristics, and the weights of the weighted average are determined based on the amount of particles in the particle distribution that fall within each particle size class. For example, if more particles fall within a particle size class, each absorption characteristic may be weighted more highly than the absorption characteristics corresponding to particle size classes with fewer particles. Furthermore, other known or learned relationships may also be considered in the weighting for determining the overall absorption characteristics. For example, larger particles may generally be determined to have a greater influence on the overall absorption characteristics than smaller particles. In this case, the weight for particle size classes with larger particles may be given a higher weight than the weight for particle size classes with smaller particles. However, for some absorption characteristics, smaller particles may generally be determined to have a greater influence than larger particles. In this case, the weight for particle size classes with smaller particles may be given a higher weight than the weight for particle size classes with larger particles.Typically, arithmetic mean can be used to predict overall product properties from individual particle size classes for absorption capacity with and without external pressure. This is not true for performance-critical properties such as swelling dynamics and liquid permeability, where fairly complex mixing properties are found for blends of superabsorbent particles with different properties (as described, for example, in International Publication No. 2019 / 137833). This is due to the fact that for such blends, not only are size-class specific properties relevant, but complex mixing phenomena based on the amount of particles present in different size classes also have a significant impact on overall performance. While finer particles may be beneficial for achieving faster liquid absorption, they can also act to counteract liquid distribution by rapidly blocking fluid conduction pores. To predict such properties, a size-class weighted average that depends on the number of particles in each class, without treating all particle sizes equally, may be used. In this invention, the weights are preferably determined experimentally after first measuring the overall performance properties of the superabsorbent polymer and then classifying them into their respective discrete size classes by determining the properties of each class. By mixing each classification in varying quantities, it becomes possible to draw conclusions toward the required weight. Experimental designs can be used for such mixing. The determined overall absorption properties are then used as the absorption properties for each particle size distribution in all further processing, particularly to determine the hygienic properties.

[0028] In a further aspect of the present invention, a system is presented for controlling the production of sanitary products and / or superabsorbent materials, wherein the sanitary products comprise a layer of superabsorbent material provided in the form of superabsorbent particles, and the system comprises: i) one or more production parameters used to produce the sanitary products; and b) an interface unit configured to receive target sanitary properties of the sanitary products and determine one or more absorption properties of the superabsorbent material and / or an injection model of the sanitary products based on the received production parameters; and ii) the apparatus according to any one of the preceding claims, configured to receive the absorption properties and / or an injection model of the superabsorbent material from the interface unit, determine the sanitary properties, further compare the determined sanitary properties with target properties, and generate a control signal to correct one or more of the one or more production parameters used to produce the sanitary products and / or superabsorbent materials if the determined sanitary properties are outside a predetermined range around the target sanitary properties. Generally, the correction of one or more production parameters used to produce the sanitary products and / or superabsorbent materials may be generated according to predetermined rules based on process knowledge. For example, if a given hygienic characteristic exceeds a predetermined range around a target hygienic characteristic, the rule may indicate that a particular production parameter should be reduced by a predetermined increment until the hygienic characteristic returns to a predetermined range around the target hygienic characteristic. Such rules may generally be based on prior experience associated with experiments or production processes.

[0029] In another aspect of the present invention, a computer-aided method for determining the hygienic properties of a sanitary product is provided, wherein the sanitary product comprises a layer of superabsorbent material provided in the form of superabsorbent particles, and the method comprises the steps of: i) receiving an injection model of the sanitary product, which includes a) one or more absorption properties of the superabsorbent material and b) the time-dependent injection of a predetermined liquid into the superabsorbent material layer of the sanitary product; ii) utilizing a sanitary product property determination model for determining the hygienic properties of the sanitary product based on the absorption properties and the injection model; and iii) generating control data for controlling the production process of the sanitary product and / or superabsorbent material based on the determined hygienic properties of the sanitary product.

[0030] In another aspect of the present invention, a computer implementation method for controlling the production of sanitary products and / or superabsorbent materials is provided, wherein the sanitary products comprise a layer of superabsorbent material provided in the form of superabsorbent particles, and the method comprises: i) receiving one or more production parameters to be used to produce the sanitary products, and b) a target sanitary product; ii) determining one or more absorption properties of the superabsorbent material and / or an injection model of the sanitary product based on the received one or more production parameters; iii) implementing the method of claim 11 based on the received absorption properties and / or injection model of the superabsorbent material to determine the sanitary properties; and iv) comparing the determined sanitary properties with a target property, and if the determined sanitary properties are outside a predetermined range around the target sanitary properties, generating a control signal to correct one or more of the one or more production parameters to be used to produce the sanitary products and / or superabsorbent materials.

[0031] In another aspect of the present invention, a computer program product for determining the hygienic properties of sanitary products is presented, the computer program product including program code means for causing the above-described apparatus to perform the above-described method.

[0032] In another aspect of the present invention, a computer program product for controlling the production of sanitary products and / or superabsorbent materials is presented, the computer program product including program code means for causing the apparatus described above to perform the method described above.

[0033] It should be understood that the above-described methods, apparatus, and computer program products have several preferred embodiments similar to and / or identical to those defined in particular in the dependent claims.

[0034] It should be understood that preferred embodiments of the present invention may also be dependent claims or any combination of the above embodiments and their respective independent claims.

[0035] These and other aspects of the present invention will become apparent with reference to the embodiments described below.

[0036] The drawings are as follows: [Brief explanation of the drawing]

[0037] [Figure 1] A schematic and illustrative system for controlling the production of sanitary products and / or superabsorbent materials used in sanitary products is provided. [Figure 2] A schematic and illustrative flowchart of a method for controlling the production of sanitary products and / or superabsorbent materials used in sanitary products is provided. [Figure 3a] Schematic and illustrative diagrams of one-dimensional, two-dimensional, and three-dimensional models for determining the hygienic characteristics of sanitary products are shown. [Figure 3b] Schematic and illustrative diagrams of one-dimensional, two-dimensional, and three-dimensional models for determining the hygienic characteristics of sanitary products are shown. [Figure 3c] Schematic and illustrative diagrams of one-dimensional, two-dimensional, and three-dimensional models for determining the hygienic characteristics of sanitary products are shown. [Figure 4a] The application of the present invention to control processes for producing sanitary products and / or superabsorbent materials is shown schematically and illustratively. [Figure 4b] The application of the present invention to control processes for producing sanitary products and / or superabsorbent materials is shown schematically and illustratively. [Figure 4c] The application of the present invention to control processes for producing sanitary products and / or superabsorbent materials is shown schematically and illustratively. [Figure 4d] The application of the present invention to control processes for producing sanitary products and / or superabsorbent materials is shown schematically and illustratively. [Figure 5] This section provides a schematic and illustrative example of how Torricelli's Law can be applied to injection models. [Modes for carrying out the invention]

[0038] Figure 1 schematically and illustratively shows a system 100 for controlling the production of sanitary products and / or superabsorbent materials used in sanitary products. System 100 includes a device 110 for determining the sanitary properties of sanitary products. Furthermore, the system includes an interface unit 120 for interface with a production system 130 for producing sanitary products and / or superabsorbent materials for sanitary products. The device 110 can be implemented as any dedicated or general-purpose computing hardware including one or more processors. In particular, the device 110 can be implemented in distributed computing, where different functions of the device are executed by different processors in the same or different locations. The device 110 is then implemented by performing functions determined by the method described with respect to Figure 2. Generally, the functions performed by the device 110 may be performed by, for example, a receiving unit 111, a sanitary properties determination unit 112, and a control data generation unit 113.

[0039] The device 110 is configured to determine the hygienic properties of sanitary products. The receiving unit 111 of the device 110 is configured to receive one or more absorbent properties of superabsorbent materials. For example, the receiving unit 111 may be configured to utilize a user interface, to which the user can input each superabsorbent material to be used in the sanitary product. Based on the input superabsorbent materials, the receiving unit 111 may then be configured to access a storage unit or library in which the absorbent properties of multiple superabsorbent materials are already stored. Furthermore, the receiving unit 111 may also directly receive the absorbent properties of superabsorbent materials from the user via the input interface. Alternatively, each superabsorbent material having one or more relevant absorbent properties may be pre-determined to be used in all cases without further notification. However, in a preferred embodiment, the system 100 may further include or be communicably coupled to a device 140 for determining the absorbent properties of each superabsorbent material.

[0040] The apparatus 140 includes, for example, a receiving interface 141, one or more processors 142, and an output interface 143. Generally, the apparatus is configured to determine the absorption properties of a superabsorbent material. The superabsorbent material is preferably available in the form of a superabsorbent polymer provided in the form of an interconnected core and superabsorbent particles including a surface crosslinked shell having higher connectivity than the interconnected core. Generally, the apparatus 140 may be provided as a standalone device, for example, as a dedicated computing device, but may also be provided as part of a more general-purpose computing device that provides additional functionality. In particular, the apparatus may be provided as part of a quality control system or, for example, as part of a production control system.

[0041] The receiving interface 141, in this example, is configured to receive the particle size of superabsorbent particles of the superabsorbent material. Generally, the receiving interface can be implemented as any interface that enables the reception of each data indicating particle size. In particular, the receiving interface may be configured to provide an interface to a storage unit in which the particle size is already stored. However, the apparatus 110 may also provide the particle size, or the control system of the production system 130 may provide sensor measurements indicating particle size. Particle size can refer to any quantity that enables the quantification of the volume of particles in the superabsorbent particles of the superabsorbent material. Preferably, particle size refers to the volume of the particles, or the radius or diameter of the particles if the particles can be approximated as spherical particles. The particle size of the superabsorbent particles is generally provided when the superabsorbent particles are dry, i.e., before they absorb fluid and enter the superabsorbent particles, resulting in an increase in the superabsorbent particle size. The received particle size of the superabsorbent particles is then provided to one or more processors 142.

[0042] One or more processors 142 are then configured to utilize an absorption property determination model for determining the absorption properties of a superabsorbent material based on particle size. For example, one or more processors may be configured to access a storage unit in which absorption property determination models are already stored. Generally, two or more absorption property determination models may be stored in the storage unit, for example, characterization models for different superabsorbent materials produced according to manufacturing specifications using different superabsorbent polymers, different crosslinking methods and / or production parameters. In this case, one or more processors may then be configured to select each absorption property determination model for a superabsorbent material using the respective information about the superabsorbent material, for example, the ID of the superabsorbent material or the manufacturing specifications provided for the superabsorbent material. Furthermore, different absorption property determination models may be stored in the storage unit for different absorption properties. In this case, one or more processors may be configured to select all available absorption property determination models for each superabsorbent material and then apply each of the absorption property determination models to determine all available absorption properties for each superabsorbent material, or one or more processors may be configured to select each absorption property determination model to be used based on further information about the desired absorption properties provided, for example, via a user interface.

[0043] Generally, absorption characterization models are parameterized to be adapted to determine the absorption characteristics of superabsorbent particles based on particle size. In particular, data-driven characterization models can be any machine learning-based model that allows learning based on historical data to determine the absorption characteristics of superabsorbent particles based on particle size. For example, absorption characterization models may refer to regression model-based algorithms such as neural network algorithms, Lasso algorithms, Ridge regression algorithms, regression methods based on principal component analysis, robust multiple linear regression analysis, MASS algorithms, or random forest algorithms. However, absorption characterization models may also refer to classifier-based model algorithms such as random forest algorithms or SVM algorithms. Useful algorithms are disclosed in "Introduction to multivariate Statistical analysis in Chemometrics," K. Varmuzza, P. Filzmoser, CRC Press, New York 2009, which are expressly incorporated herein. In particular, the absorption characterization model used is preferably further parameterized based on the core size and shell size of each superabsorbent particle in order to enable the quantification and determination of the respective contributions of core size and shell size to each absorption characteristic. This makes it possible to store absorption characteristic determination models by storing each performance parameter that quantifies the contribution. Subsequently, the selection of an absorption characteristic determination model can be achieved by selecting performance parameters corresponding to each core size and each shell size, and using these performance parameters in the absorption characteristic determination model.

[0044] In general, an absorption property determination model can be trained using any known method. In particular, hierarchical training data is used to train an absorption property determination model. Hierarchical training data includes at least two, preferably multiple, particle sizes of superabsorbent materials and one or more corresponding measured absorption properties of the superabsorbent materials. Such training data can be generated, for example, by measurements of each superabsorbent material using a known measurement method for determining the absorption property and also measuring the respective particle size of the superabsorbent material. In general, such hierarchical training data is often generated during quality control of the superabsorbent material or during the design process of the superabsorbent material in which the respective measurements are performed. The hierarchical training data can then be used to parameterize the absorption property determination model so that the parameterized absorption property determination model is adapted to determine the absorption property of the superabsorbent material based on particle size. For example, known machine learning methods, i.e., parameterization methods, can be used. Based on such a trained property determination model, one or more processors 142 of the apparatus 140 are then configured to determine the absorption property of the superabsorbent material based on the provided particle size. The determined absorption property and optionally used particle size can then also be provided to the apparatus 110. Therefore, the apparatus for determining the absorption properties of superabsorbent materials makes it possible to determine the absorption properties even for superabsorbent materials that are not directly stored in a database or library. In particular, the effect of particle size can be determined more accurately in most cases when using the apparatus 140.

[0045] Furthermore, the receiving unit 111 receives an injection model of a sanitary product, which includes injecting a predetermined liquid over time into the superabsorbent material layer of the sanitary product. Generally, the injection model makes it possible to specify the respective applications for which the hygienic properties of the sanitary product should be determined. Moreover, the injection model can implicitly take into account different compositions and structures of sanitary products, particularly those that have an effect on the fluid applied to the sanitary product that reaches the superabsorbent material within the superabsorbent layer.

[0046] The hygiene characteristics determination unit 112 is then configured to utilize a sanitary product characteristics determination model for determining the hygiene characteristics of sanitary products based on absorption characteristics and injection models. A preferred example of such a product characteristics determination model is described below with reference to Figure 3a.

[0047] Figure 3a shows a schematic and illustrative diagram of a one-dimensional (1D) model for determining the hygienic properties of sanitary products. However, the model can also refer to more dimensions and may further be a 2D or 3D model, as shown in Figures 3b and 3c. In the case of a 1D model, an ordinary differential equation involving only a function of time may be used, while in 2D and 3D models, differential subequations involving a function of time t and spatial liquid distribution may be used. In a 2D model, the sanitary product may be mathematically segmented with stripes to describe the liquid distribution in only one direction, while in a 3D model, the liquid may be described as being distributed in two spatial orientations, e.g., x and y directions. Such 2D and 3D models are illustrated in Figures 3b and 3c. For the purpose of optimizing the absorption properties of superabsorbent polymers in sanitary products, a simple 1D model is usually sufficient, while a 2D or 3D model is preferred for optimizing the sanitary product itself.

[0048] The model shown in Figure 3a is a 1D model in this example that shows layers containing a superabsorbent material and optionally a fluff material. Furthermore, the model shows a fluid source in the injection model, in this case a funnel reservoir. Furthermore, in some cases, the model further includes the effect of the pressure supplied to the superabsorbent material layer, as indicated by the weight. Arrows indicate possible flow directions of the fluid from the reservoir in the layer. In this model, the free fluid in the layer can be described based on a differential equation that includes, for example, three terms, particularly a term indicating injection, a term indicating liquid absorption, and a term indicating free fluid that has not yet been absorbed. Preferably, the model is based on the following differential equation:

number

number

number

number

number

number

number

number

number

[0049] Alternatively, the injection term may be any encoded fluid injection profile simulating a pump or natural discharge, and may include the effects or inefficiencies of fluid management elements observed in the sanitary product. In this invention, one or more subsequent fluid injections may be simulated in the sanitary product to define one or more target sanitary properties. An example of a target sanitary property is the amount of free fluid still present in the sanitary product at a specific time in the simulation and after a specific amount of fluid has been injected. Two or more time points may be defined to calculate the amount of free fluid and define the target sanitary property. Another example of a target sanitary property is the acquisition time required to absorb all the fluid in the sanitary product up to a preset threshold for one or more subsequent discharges. Another example of a target sanitary property is the maximum amount of free fluid available in the sanitary product after each discharge. Yet another example of a target sanitary property is the integral over time of the available free fluid in the simulated sanitary product and the integral over one or more subsequent discharges.

[0050] The absorption of the fluid is preferably described by the following equation, which includes the absorption characteristics.

number

[0051] In the 1D model, it is preferably assumed that the liquid is instantaneously and equally distributed to all accessible superabsorbent material, and that all superabsorbent material within the layer has the same degree of swelling. However, in this model, it is not necessary for all superabsorbent material to be accessible. In this model, the absorbent layer is not spatially discretized. Figure 3b shows a schematic and illustrative 2D model of a sanitary product. In this case, the absorbent layer is spatially discretized in one direction. Preferably, since most sanitary products have a given layer thickness and an absorbent layer that is longer in one direction than in the other, the discretization is performed in the longitudinal direction of the layer. However, the direction of discretization may also be the direction in which the greatest change in the superabsorbent layer is expected. In this 2D model, it is preferably assumed that the liquid diffuses isotropically to all accessible superabsorbent material, and that the superabsorbent material swells when the liquid reaches the superabsorbent material layer. Figure 3c shows a schematic and illustrative 3D model of a sanitary product. In this case, the absorbent layer is spatially discretized in two directions. Preferably, the two directions are those in which the superabsorbent layer extends over the surface of the sanitary product, i.e., the layer thickness is not discretized. In this case, the liquid is assumed to diffuse isotropically into all accessible superabsorbent material, and the superabsorbent material is assumed to swell when the liquid reaches it.

[0052] In the model, only superabsorbent properties are considered, preferably the absorption capacity under use-case pressure, the absorption rate under use-case pressure, or the permeability under use-case pressure. An injection model, and therefore the injection of fluid over time, can be provided, for example, through the design of an experiment based on experimental determination using a synthesized sanitary material, such as in the case of an SAP-Fluff mixture. Preferably, the injection model further takes into account the permeability of the superabsorbent material or the combined permeability of the mixture. This can be achieved, for example, again by experimental measurement of the injection volume, but can also be achieved by utilizing a known physical relationship between the permeability of the material and the possible fluid flow through the material, such as Torricelli's law. However, the injection model can also be a theoretical injection model that does not take into account the permeability of the sanitary material or a particular arrangement. Such a theoretical injection model can be particularly useful for comparing the effects of different superabsorbent materials, especially different superabsorbent properties in a theoretical setup. The model can then calculate the time-dependent amount of liquid that has not yet been absorbed, i.e., free, as a function of absorption capacity, the amount of superabsorbent agent, and the time elapsed after acquisition is complete. Free liquid is a desirable hygienic characteristic because it allows for determining how much unabsorbed liquid remains at time t after the spraying of a sanitary item, and also for determining how dry the item is after a predetermined time after each liquid has been sprayed.

[0053] The experimental determination of unabsorbed liquid (re-wetting) is cumbersome because it is performed experimentally after a predetermined time t (t=1-20 minutes) following each ejection, by squeezing out the unabsorbed liquid through blotting paper placed on top of the sanitary item and applying a predetermined pressure. The amount of liquid injected, the injection sequence, and the time t for re-wetting measurement are variable, and all of them differ for different applications. Since the experimental method can only deliver such re-wetting data at one fixed time per sanitary item, often only at the end of the test after the last ejection, two complete test series are required, for example, to check two different t values ​​for one superabsorbent grade used at the same concentration and in the same sanitary item design. Therefore, variations in superabsorbent grade, superabsorbent concentration, liquid injection sequence, and re-wetting test time (t) result in a considerable amount of manual work, delaying the development and commercialization of optimized superabsorbents. For example, a model like the one described above would allow for a much faster and less manual workload and time consumption through, for example, a grid search across a matrix of these properties. In contrast to manual re-wetting methods, this model can generate time-dependent drying curves that allow for the deriving of the optimal balance between absorption capacity, absorption rate, and liquid permeability for different re-wetting time requirements T. To achieve this, the model uses experimental information on absorption properties such as absorption capacity, absorption rate, and liquid permeability as a function of pressure from external use cases, which can be determined experimentally for pure superabsorbent agents and stored in a database.

[0054] Alternatively, at least the absorption capacity and absorption rate under pressure in external use cases can be estimated via the theory described in FLBuchholz, A.T. Graham, Modern Superabsorbent Polymer Technology, Wiley-VCH, Weinheim, 1998. Furthermore, as mentioned above, each data-driven model can also be used. In particular, since absorption rate and permeability are typically nonlinear functions of the particle size mixture, and it is important in the production process to approximate a constant particle size distribution as close as possible to an optimized performance balance of these parameters, the influence of the particle size distribution on absorption capacity, absorption rate, and permeability can be accurately modeled using the data-driven models already described above. In preferred embodiments, the model is based only on permeability and absorption rate.

[0055] Next, the control data generation unit 113 may generate control data to control the production process of sanitary products and / or superabsorbent materials based on the determined hygienic properties of the sanitary products. The control data is indicated by arrow 114 in Figure 1. In a preferred embodiment, the control data is generated to directly control the production process performed by the production unit 130. In this case, production parameters used to produce sanitary products, indicated by arrows 115 and 116, are provided to the apparatus 110 via the interface unit 120. In this case, the interface unit 120 is further configured to determine one or more absorption properties of superabsorbent materials and / or injection models of sanitary products based on one or more received production parameters. For example, the production parameters may indicate which superabsorbent materials are used in the production of sanitary products, and then the interface unit 120 may utilize the same database or library as the receiving unit 111. However, the interface unit 120 may also utilize the apparatus 140 for determining absorption properties using respective absorption property determination models, for example, based on the particle size of the superabsorbent materials. However, other knowledge, such as other databases and libraries, may also be used to associate one or more production characteristics of superabsorbent materials with their respective absorption characteristics, or to associate one or more production characteristics of sanitary products with their respective injection models. However, the absorption characteristics and / or injection models of superabsorbent materials may also be provided to the interface unit, for example, via an input unit from the user. Furthermore, the interface unit 120 may receive target hygiene characteristics of the sanitary products. The received and / or determined parameters are then provided to the device 110, as indicated by the arrow 116, and the device 110 may then predict the hygiene characteristics of the produced sanitary products based on the provided parameters, as described above. This makes it possible to avoid multiple measurements of the hygiene characteristics of the sanitary products during production. Based on the determined hygiene characteristics of the sanitary products, the device 110, for example, the control data generation unit 113, may then be configured to further compare the determined hygiene characteristics with target hygiene characteristics.If the determined sanitary properties fall outside a predetermined range around the target sanitary properties, a control signal may be generated so that the production parameters for producing sanitary products and / or superabsorbent materials are directly corrected. Generally, the correction of production parameters may be based on known rules determined by experiment or experience, for example, that deviations from a particular sanitary property can be corrected by incrementally correcting the respective production parameters.

[0056] Additionally or alternatively, the apparatus 110 may also provide control data for optimizing sanitary products, particularly by utilizing target sanitary properties before production, and then for producing optimized sanitary products. In this case, the apparatus 110, for example, the control data generation unit 113 or the property determination unit 112, may be further configured to compare the determined sanitary properties with target sanitary properties. Based on the comparison, if the determined sanitary properties meet the target sanitary properties within a predetermined limit, the respective superabsorbent material used, particularly the particle size distribution of the superabsorbent material, the composition of the superabsorbent material, and the amount of the superabsorbent material, may be set as the target superabsorbent material. However, if the comparison results in the determined sanitary properties not meeting the target sanitary properties within a predetermined limit, a new superabsorbent material may be determined, and the determination of the sanitary properties of the sanitary product may be repeated using the new superabsorbent material. This optimization may then be performed iteratively until any interruption criterion, for example, a predetermined number of iteration steps, is met or until a superabsorbent material that can be set as the target superabsorbent material is found. A new superabsorbent material can be determined, for example, by correcting for the size distribution of the particles forming the superabsorbent material, the composition of the superabsorbent material itself, and / or the amount of superabsorbent material within the superabsorbent layer. Each of these variables for sanitary products can have its own influence on the absorbent properties of the superabsorbent material, thus making it possible to find a superabsorbent material that satisfies the target sanitary properties during iteration.

[0057] Figure 2 schematically and illustratively illustrates a method for controlling the production process of superabsorbent materials and / or sanitary products containing superabsorbent materials. Generally, the method includes the steps of receiving the absorption properties of the superabsorbent material and receiving an injection model that shows the application and / or compositional structure of the sanitary product. Optionally, receiving the absorption properties is based on received production parameters of the sanitary product, for example, as described above with respect to Figure 1. In a further step, each received absorption property and the received injection model are then used to determine the sanitary properties of the sanitary product. The model used may refer to a differential equation model, as described in more detail above with respect to Figures 1 and 3. In an optional step, the method may also include receiving a target sanitary property and further comparing the determined sanitary property with the target sanitary property. Based on the comparison, it may then be determined to provide a new sanitary property, in particular, if a deviation exceeding a predetermined limit is determined, the model may be used again to determine the sanitary properties of the new superabsorbent material, or if the deviation falls below a predetermined limit, each superabsorbent material may be determined as the target superabsorbent material. Subsequently, control data may be generated, for example, based directly on the determined hygienic properties to directly control the production process of the superabsorbent material or sanitary product to satisfy the respective target hygienic properties of the final product, or it may be generated based on the target superabsorbent material by indicating the production process to utilize the respective determined target superabsorbent material.

[0058] Figure 4a schematically and illustratively illustrates a more detailed example of applying the present invention described above to the production of specific sanitary products. In particular, first process parameters such as polymerization, drying, and sizing, as well as compounding parameters, are provided for each superabsorbent material, enabling the determination of each base polymer that can be used to produce superabsorbent particles. The base polymers used to produce superabsorbent particles are characterized by volume, swelling time, particle size distribution, and particle morphology. Based on these properties, compounding and production processes using each parameter, called SXL parameters, can be further determined. This complete production process then results in the production of finished superabsorbent particles, which include their respective absorption properties, particularly volume, swelling time, and permeability. These superabsorbent particle parameters, along with diaper target performance parameters that indicate the target sanitary properties of the diaper, such as free liquid after a predetermined amount of time, can then be provided to a sanitary property determination model based on differential equations, for example, as described above with respect to Figure 3. The model then makes it possible to calculate diaper performance, particularly sanitary properties, from the superabsorbent particle parameters and compare the calculated diaper performance with the target performance. Based on this comparison, process and formulation parameters may then be adjusted to optimize the sanitary product, in this case a diaper, to meet target performance, for example, by using machine learning, white-box models, or a combination thereof.

[0059] Figures 4b to 4d show in more detail which steps in the production and generation of superabsorbent particles can have parameters optimized based on the target performance. In Figure 4b, the optimization process is configured to optimize superabsorbent material production across all production steps of the superabsorbent material. The arrows in each step indicate whether process parameters or formulation parameters can be corrected for the optimization of the superabsorbent material in that step. In general, optimization can be performed as described in relation to Figure 4a, using a hygiene property determination model based on differential equations, for example, as described above with respect to Figure 3, to determine each hygiene property and compare the hygiene property to each target performance, i.e., the target hygiene property. Figure 4c shows an optimization process in which only the step of producing the superabsorbent material is optimized, without surface adaptation, for example, without a surface crosslinking step and / or coating step. Furthermore, in this example, the hygiene property determination model has already determined the optimal target absorption properties of the superabsorbent material that enable the provision of each target performance of the sanitary product. Therefore, in this case, optimization can be performed directly, for example, by comparing the absorption properties of the superabsorbent material, determined using the respective absorption property determination models described above, with the target absorption properties. Figure 4d illustrates a further optimization process, showing only the final step in superabsorbent material production, which refers to surface adaptation, such as crosslinking. In this case, it is also illustrated that optimization can be performed directly based on the target absorption properties of the absorbent material previously determined with respect to the target performance of the sanitary product.

[0060] In the embodiments described above, the present invention was explained using a model based on differential equations, but other models, particularly data-driven models implemented as machine learning models trained on historical training data, can also be used.

[0061] To improve diaper performance and develop / supply appropriate superabsorbency, it is necessary to understand how many different performance parameters affect good diaper performance. Historically, this has been done through trial and error and incremental development activities. With increasing market complexity, evolution of diaper design, and the progress of commoditization, there is now a need to develop ways to drive innovation more effectively and efficiently. Therefore, a calculation method is needed that enables the definition of performance-critical SAP parameters in superabsorbency and the selection of an optimized parameter set, in order to enable the rapid development of superabsorbency that will result in improved diaper performance.

[0062] The present invention, in particular, makes it possible to improve the balance between absorption capacity, absorption rate, and acquisition rate, which need to be optimized to suit specific application tests and / or consumer preferences. The present invention enables more effective decisions in the development of new sanitary products.

[0063] The above description outlines several absorption properties defined by the respective measurement or test methods used to determine absorption properties in most cases. Sources for details on these measurement and test methods are provided below. Generally, various methods for determining superabsorbent absorption properties are available as industry standards in publications, specified by user applications, or widely used in the market through experience. For example, methods for determining FSC, CRC, and AAP properties are available from EDANA (European disposables and non-wovens association) as the EDANA method. Specifically, for FSC properties, the measurement method is described in standard NWSP 240.0.R2(15), for CRC properties, in standard NWSP 241.0.R2(15), and for AAP properties, in standard NWSP 242.0.R2(15). Furthermore, country-specific test methods for China are available from Chinese standardization bodies. Furthermore, methods for measuring saline flow conductivity (SFC) are disclosed, for example, in the published European Patent No. 0752892B1. Methods for measuring volume absorbability under load (VAUL) are disclosed, for example, in the published European Patent No. 2922882B1. Methods for measuring T20 absorption dynamics are disclosed, for example, in the published European Patent Application Publication No. 2535698A1. Furthermore, a vortex absorption dynamics method is exemplarily disclosed in "Modern Superabsorbent Polymer Technology" by Buchholz FL and Graham AT, 1st ed. Weinheim: Wiley-VCH, 1998, p. 155. Furthermore, an automated AAP method is disclosed in the patent application brochure International Publication No. 2021 / 001221A1.

[0064] In the claims, the word “including” does not exclude other elements or steps, and the indefinite articles “a” or “an” do not exclude plurals.

[0065] A single unit or device may perform the functions of multiple items described in the claims. The mere fact that certain means are mentioned in different dependent claims does not indicate that combinations of these means cannot be used advantageously.

[0066] Procedures such as receiving absorption characteristics, determining absorption characteristics, and generating control data, which are performed by one or more units or devices, may be performed by any number of other units or devices. These procedures may be implemented as program code means in a computer program and / or as dedicated hardware.

[0067] Computer program products may be distributed in storage / medium on suitable media such as optical storage media or solid-state media, supplied together with or as part of other hardware, but may also be distributed in other forms, for example, via the Internet or other wired or wireless telecommunication systems.

[0068] Any unit described herein may be a processing unit that is part of a classic computing system. A processing unit may include a general-purpose processor, a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or any other dedicated circuit. Any memory may be physical system memory and may be volatile, non-volatile, or a combination of both. The term “memory” may include any computer-readable storage medium, such as a non-volatile mass storage device. If the computing system is distributed, the processing power and / or storage power may also be distributed. A computing system may include multiple structures as “executable components.” The term “executable component” is a structure that is well understood in the computing field as a structure that may be software, hardware, or a combination thereof. For example, if implemented in software, a person skilled in the art will understand that the structure of an executable component may include software objects, routines, methods, etc., that can be executed on the computing system. This may include both executable components in the computing system’s heap or executable components on computer-readable storage medium. The structure of an executable component may exist on a computer-readable medium such that, when interpreted by one or more processors of a computing system, such as processor threads, it causes the computing system to perform a function. Such a structure may be directly computer-readable by the processor, for example, if the executable component is a binary, or it may be structured to be interpretable and / or compiled to produce such a binary that is directly interpretable by the processor, whether, for example, in a single or multiple stage. In other examples, the structure may be, for example, a hardcoded logic gate or hardwired logic gate that is implemented exclusively or nearly exclusively in hardware within a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or other dedicated circuitry.Accordingly, the term “executable component” is a term for a structure that is well understood by those skilled in the art of computing, whether implemented in software, hardware, or a combination thereof. Any embodiment of this specification is described with reference to an operation performed by one or more processing units of a computing system. Where such an operation is implemented in software, one or more processors direct the operation of the computing system in response to the execution of computer executable instructions constituting the executable component. The computing system may also include, for example, communication channels that enable the computing system to communicate with other computing systems via a network. “Network” is defined as one or more data links that enable the transmission of electronic data between computing systems and / or modules and / or other electronic devices. When information is transferred to or supplied to the computing system via a network or another communication connection, such as hardwired, wireless, or a combination of hardwired and wireless, the computing system appropriately considers the connection to be a medium of transport. The medium of transport may include networks and / or data links that can be used to transport desired program code means in the form of computer executable instructions or data structures, and that can be accessed by general-purpose computing systems or dedicated computing systems or a combination thereof. Not all computing systems require a user interface, but in some embodiments, the computing system includes a user interface system used to interface with a user. The user interface functions, for example, as an input or output mechanism to the user via a display.

[0069] Those skilled in the art will understand that at least part of the present invention can be implemented in network computing environments having many types of computing system configurations, including personal computers, desktop computers, laptop computers, message processors, handheld devices, multiprocessor systems, microprocessor-based or programmable home appliances, network PCs, minicomputers, mainframe computers, mobile phones, PDAs, pagers, routers, switches, data centers, and wearable devices such as eyeglasses. The present invention can also be implemented in a distributed system environment in which local and remote computing systems linked over a network by either hardwired data links, wireless data links, or a combination of hardwired and wireless data links work together to perform tasks. In a distributed system environment, program modules can be located on both local and remote memory storage devices.

[0070] Those skilled in the art will also understand that at least part of the present invention may be implemented in a cloud computing environment. A cloud computing environment may, but is not required, be distributed. If distributed, a cloud computing environment may have components that are internationally distributed within an organization and / or held across multiple organizations. In this specification and the following claims, “cloud computing” is defined as a model that enables on-demand network access to a shared pool of configurable computing resources, such as networks, servers, storage devices, applications, and services. The definition of “cloud computing” is not limited to any of the many other benefits that may be obtained when such a model is deployed. The computing system in the drawings includes various components or functional blocks that can implement the various embodiments disclosed herein, as described. These various components or functional blocks may be implemented on a local computing system, or on a distributed computing system that includes elements residing in the cloud or implements a form of cloud computing. These various components or functional blocks may be implemented as software, hardware, or a combination of software and hardware. The computing system shown in the drawings may include more or fewer components than those shown, and some of the components may be combined where circumstances permit.

[0071] None of the reference numerals in the claims should be construed as limiting the scope.

Claims

1. An apparatus for determining the hygienic properties of a sanitary product, wherein the sanitary product includes a layer of superabsorbent material provided in the form of superabsorbent particles, and the apparatus (110) a) receiving one or more absorption properties of the superabsorbent material, and b) receiving an injection model of the sanitary product, which includes the time-dependent injection of a predetermined liquid into the superabsorbent material layer of the sanitary product. A model for determining the sanitary product characteristics is used to determine the hygienic characteristics of the sanitary product based on the absorption characteristics and the injection model. Based on the determined hygienic properties of the sanitary products, control data is generated to control the production process of the sanitary products and / or the superabsorbent material. A device including one or more processors configured to perform the following actions.

2. The apparatus according to claim 1, wherein one or more processors are configured to receive the target hygiene characteristics of the sanitary product, compare the determined hygiene characteristics with the target hygiene characteristics, and i) determine the superabsorbent material as the target superabsorbent material of the sanitary product if the determined hygiene characteristics are within a predetermined range around the target hygiene characteristics, and ii) determine a new superabsorbent material if the determined hygiene characteristics are outside a predetermined range around the target hygiene characteristics, and to repeat the determination of the hygiene characteristics of the sanitary product using the new superabsorbent material, and the control of the production process is based on the determined target superabsorbent material.

3. The apparatus according to claim 2, wherein determining a new superabsorbent material includes correcting the size distribution of the particles forming the superabsorbent material and / or the amount of superabsorbent material in the layer.

4. The apparatus according to any one of claims 1 to 3, wherein the hygienic characteristic indicates the amount of free liquid in the sanitary product.

5. The apparatus according to any one of claims 1 to 4, wherein one or more absorption properties of the superabsorbent material exhibit at least one of permeability, absorption capacity, and absorption rate.

6. The aforementioned model for determining the characteristics of sanitary products is based on the following differential equation [Math 1] This includes solving the following, where, [Math 2] This describes the free liquid in the sanitary product over time, [Math 3] This describes the absorption of fluid by the superabsorbent material according to the absorption characteristics over time, and [Math 4] The apparatus according to any one of claims 1 to 5, which describes the injection of the fluid into the sanitary product over time.

7. Furthermore, the apparatus according to any one of claims 1 to 6, wherein instructions regarding the amount of superabsorbent material in the sanitary product layer are received, and the one or more absorption properties of the superabsorbent material are adapted based on the amount of superabsorbent material in the sanitary product.

8. The apparatus according to any one of claims 1 to 7, further comprising one or more processors configured to determine one or more absorption properties of the superabsorbent material based on the received particle size distribution of the superabsorbent material using an absorption property determination model, wherein the property determination model is a data-driven model, parameterized to be adapted to determine the technical application properties of superabsorbent particles based on the size of the particles, and the determined one or more absorption properties are subsequently used in the sanitary property determination model.

9. The apparatus according to claim 8, wherein the superabsorbent material comprises a superabsorbent polymer provided in the form of i) interconnected cores and ii) surface crosslinked shells having higher connectivity than the cores, and the provided absorption property determination model is further parameterized based on the core size and shell size of the superabsorbent particles.

10. The apparatus according to any one of claims 1 to 9, wherein the one or more received absorption characteristics are measured during the production process of the superabsorbent material and / or the sanitary product containing the superabsorbent material, and the generated control data is configured to control and / or monitor the production process based on the sanitary characteristics determined from the one or more measured absorption characteristics.

11. A system for controlling the production of sanitary products and / or superabsorbent materials, wherein the sanitary products include a layer of the superabsorbent material provided in the form of superabsorbent particles, and the system (100) is a) one or more production parameters used to produce the sanitary product, and b) an interface unit (120) configured to receive target hygiene characteristics of the sanitary product and to determine one or more absorption characteristics of the superabsorbent material and / or an injection model of the sanitary product based on the received one or more production parameters. An apparatus (110) according to any one of claims 1 to 10, comprising: receiving the absorption properties and / or injection model of the superabsorbent material from the interface unit; determining the sanitary properties; further comparing the determined sanitary properties with the target properties; and, if the determined sanitary properties are outside a predetermined range around the target sanitary properties, generating a control signal for correcting one or more of the one or more production parameters used to produce the sanitary product and / or the superabsorbent material. A system that includes this.

12. A computer-based method for determining the hygienic properties of a sanitary product, wherein the sanitary product comprises a layer of superabsorbent material provided in the form of superabsorbent particles, and the method is: a) receiving one or more absorption properties of the superabsorbent material, and b) receiving an injection model of the sanitary product, which includes the time-dependent injection of a predetermined liquid into the superabsorbent material layer of the sanitary product, A step of using a sanitary product characteristics determination model to determine the hygienic characteristics of the sanitary product based on the absorption characteristics and the injection model, A step of generating control data for controlling the production process of the sanitary product and / or the superabsorbent material based on the determined hygienic properties of the sanitary product. A computer implementation method, including

13. A computer-aided method for controlling the production of sanitary products and / or superabsorbent materials, wherein the sanitary products include a layer of the superabsorbent material provided in the form of superabsorbent particles, and the method is a) one or more production parameters used to produce the sanitary products, and b) receiving the target hygiene characteristics of the sanitary products. Based on the received production parameters, one or more absorption properties of the superabsorbent material and / or the injection model of the sanitary product are determined. In order to determine the hygienic properties, the method of claim 12 is carried out based on the received absorption properties and / or injection model of the superabsorbent material, The determined sanitary properties are compared with the target properties, and if the determined sanitary properties are outside a predetermined range around the target sanitary properties, a control signal is generated to correct one or more of the one or more production parameters used to produce the sanitary products and / or the superabsorbent material. A computer implementation method, including

14. A computer program product for determining the hygienic characteristics of sanitary products, comprising a program code means for causing the apparatus described in any one of claims 1 to 10 to execute the method described in claim 12.

15. A computer program product for controlling the production of sanitary products and / or superabsorbent materials, comprising program code means for causing the apparatus according to claim 11 to perform the method according to claim 13.

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