Device for determining hygiene properties of hygiene products

Abstract

The invention relates to a method for determining hygiene properties of a hygiene product. A hygiene product includes a superabsorbent material layer. In one step, a) one or more absorption properties of the superabsorbent material and b) a quantitative model of the hygiene product comprising a predetermined quantification of liquid over time at a layer of superabsorbent material of the hygiene product are received. A hygiene product characteristic determination model is utilized for determining hygiene characteristics of the hygiene product based on the absorption characteristics and the quantitative model. Control data is generated for controlling the production process of the hygiene product and / or superabsorbent material based on the determined hygiene characteristics of the hygiene product.

Description

Technical Field

[0001] This invention relates to apparatus, methods, and computer program products for determining the hygienic properties of hygiene products. Furthermore, this invention relates to systems, methods, and computer program products for controlling the production of hygiene products and / or superabsorbent materials. Background Technology

[0002] In many modern hygiene products, superabsorbent materials in the form of superabsorbent particles are typically used for fluid absorption. However, even for experts, it is often difficult to predict how the corresponding superabsorbent material will affect the performance parameters of the hygiene product, especially its hygienic properties. Therefore, hygiene products are currently developed using a trial-and-error approach and incremental development techniques. Thus, it would be advantageous if the hygienic properties of hygiene products could be predicted quickly and accurately to control the production process of the hygiene product and / or the superabsorbent material used in it. Summary of the Invention

[0003] One object of the present invention is to provide an apparatus, method, and computer program product that allows for the determination of improved hygienic properties of hygienic products. This determination of improved properties allows for improved control of the production process of hygienic products and / or superabsorbent materials, particularly for continuous or batch production of hygienic products and / or superabsorbent materials, while meeting predetermined hygienic properties.

[0004] In a first aspect of the invention, an apparatus for determining the hygienic properties of a hygiene product is provided, wherein the hygiene product comprises a layer of superabsorbent material provided in the form of superabsorbent particles, wherein the apparatus comprises one or more processors configured to: i) receive a) one or more absorption properties of the superabsorbent material, and b) a quantitative model of the hygiene product, the quantitative model comprising a predetermined amount of liquid at the superabsorbent material layer of the hygiene product over time, ii) utilize a hygiene product property determination model to determine the hygienic properties of the hygiene product based on the absorption properties and the quantitative model, and iii) generate control data for controlling the production process of the hygiene product and / or the superabsorbent material based on the determined hygienic properties of the hygiene product.

[0005] The inventors have discovered that a characteristic determination model can be used to predict the hygienic properties of a hygiene product based on the absorption characteristics of a superabsorbent material in the product to a predetermined liquid and based on the predetermined amount of liquid at the superabsorbent material in a layer of hygiene product over time. Because the model is based on only these two input parameters, the prediction of hygienic properties becomes efficient without the need to collect large amounts of measurement data first. This allows for rapid and computationally inexpensive predictions, enabling the generation of control data for the production process of hygiene products, such as for directly manipulating the production process of hygiene products and / or superabsorbent materials, based on the separately determined hygienic properties.

[0006] Generally speaking, a device can refer to any general-purpose or special-purpose computing device suitable for performing its functions, for example, by executing a corresponding computer program. Specifically, a device can be implemented using any form of software and / or hardware that enables a general-purpose or special-purpose computing device to perform the functions defined above. Furthermore, a device can be implemented as a standalone device, for example, as dedicated hardware, or by being provided on a user's corresponding computer system, but it can also be implemented as a network of computers or processors, for example, in a shared computing system such as cloud computing or network computing, where more than one computer or processor can provide the device's functions.

[0007] Generally, this device is suitable for determining the hygienic characteristics of a hygiene product. A hygiene product can be any product used for personal hygiene reasons, such as for human or pet excrement. In particular, a hygiene product is configured to absorb bodily fluids. Preferably, a hygiene product refers to a diaper. However, a hygiene product can also refer to any other product configured to absorb bodily fluids, such as feminine hygiene products, medical hygiene products, etc. Hygienic characteristics can refer to any characteristic of a hygiene product that affects its hygiene. In particular, since a hygiene product is a fluid-absorbing product, a hygienic characteristic refers to a characteristic indicating the fluid absorption of the hygiene product. Preferably, the hygienic characteristic indicates the amount of free liquid in the hygiene product. More preferably, the hygienic characteristic indicating the amount of free liquid in the hygiene product refers to the maximum amount of free liquid in the hygiene product after a certain amount of fluid has been applied and / or the absorption time, i.e., the time required to absorb a certain amount of free fluid until a predetermined minimum amount of free liquid is reached. Preferably, the predetermined minimum amount of free liquid is zero, such that no free liquid remains in the hygiene product at the end of the absorption process. However, in some applications, a certain amount of free liquid is acceptable even over an extended period of time, such that in these cases, the corresponding minimum amount of free liquid can be higher than zero and set as the maximum amount of free liquid permissible over the extended period of time in such applications. Another preferred hygienic characteristic is the collection time of liquid in the hygienic product, where the collection time is the time until the liquid is completely collected in the hygienic product. In one embodiment, the hygienic characteristic includes free liquid and / or collection time, or can be derived from free liquid and / or collection time.

[0008] To absorb fluids, hygiene products include a layer of superabsorbent material provided in the form of superabsorbent particles. Superabsorbent material is a material that can absorb and retain a large amount of aqueous liquid relative to its own weight. For example, for deionized and distilled water, superabsorbent material can absorb up to 1000 times its own weight. For practical hygiene applications, superabsorbent material absorbs at least 15 g / g, typically at least 20 g / g, preferably at least 25 g / g, and most preferably at least 30 g / g, but not exceeding 120 g / g, preferably not exceeding 100 g / g, more preferably not exceeding 80 g / g, and most preferably not exceeding 60 g / g of a 0.9% by weight saline solution (NaCl), for example, in the tea bag method CRC, without external pressure. Absorption by superabsorbent polymers is particularly useful compared to conventional absorbents such as cellulose fibers because the absorbed liquid is not released even under the pressure of use in the hygiene product, and the wearer's skin remains dry. In most cases, superabsorbent material comprises superabsorbent polymers (SAPs), typically provided in the form of multiple particles forming the superabsorbent material. Superabsorbent polymers typically consist of hydrophilic, high-molecular-weight polymer chains with ionic groups, interconnected to render the superabsorbent polymer insoluble in water. The ionic groups are typically -COOH, but sulfur (-SO3H) or phosphorus can also be used as acid providers. These groups are partially neutralized to achieve a skin-friendly pH on the wearer's skin, typically pH 4.0-7.5, preferably pH 5.0-6.5. As a means of neutralization, any alkali metal-based neutralizing agent (Li, Na, K, Rb, Cs) can be used in hygienic applications, but Na is preferred. Commonly used neutralizing agents are alkali metal salts of hydroxides, carbonates, and bicarbonates, as well as mixtures thereof. Such neutralizing agents can be used in melt, powder, or liquid form, or as aqueous solutions, or as mixtures of two or more of these physical forms in a sequential or simultaneous neutralization process. Examples of such superabsorbent polymers are cross-linked sodium poly(meth)acrylate, cross-linked sodium itaconic acid, polyacrylamide copolymers, ethylene maleic anhydride copolymers, cross-linked carboxymethyl cellulose, cross-linked starch derivatives and carboxymethyl starch, polyvinyl alcohol grafted or starch grafted cross-linked partially neutralized polyacrylates, polyvinyl alcohol copolymers, cross-linked polyethylene oxide, etc. Furthermore, copolymers of acrylic acid, maleic acid, and itaconic acid can be used, and can be combined with copolymerized nonionic hydrophilic or hydrophobic monomers. Partially neutralized cross-linked polyacrylic acid and polyitaconic acid, and copolymers thereof are preferred. More preferably, partially neutralized cross-linked polyacrylic acid and polyitaconic acid, and copolymers thereof, whose raw materials are derived from biological sources, such as plants, microorganisms, algae, and fungi. Most preferably, partially neutralized cross-linked polyacrylic acid and polyitaconic acid, and copolymers thereof, and a superabsorbent production process with the lowest possible carbon footprint for producing the superabsorbent polymers of the present invention.

[0009] The device then includes one or more processors capable of performing the functions described below. In a step performed by the receiving unit of the device, for example implemented by one or more processors, one or more absorption properties of a superabsorbent material to be used in a hygiene product are received. Specifically, for example, the absorption properties of the superabsorbent material can be received by accessing a storage unit that already stores the corresponding absorption properties. Such absorption properties of the superabsorbent material can be stored, for example, in a database or a superabsorbent material library, which is filled with various different superabsorbent materials and associated absorption properties. Such a database or library can be generated by performing corresponding experiments and measurements on the absorption properties of various superabsorbent materials or by performing corresponding simulations on the absorption properties of superabsorbent materials. Receiving one or more absorption properties of the superabsorbent material can then, for example, include receiving the superabsorbent material via user input or via automatic determination, and accessing the corresponding database or library to receive the corresponding absorption properties associated with the received superabsorbent material stored in the database or library. However, one or more absorption properties can also be received, for example, via an input unit from a user providing the corresponding absorption properties. Furthermore, the corresponding absorption characteristics of the superabsorbent material can also be directly received from the corresponding measuring equipment, in which the corresponding absorption characteristics of the superabsorbent material have been measured.

[0010] Preferably, absorption characteristics refer to at least one of absorption capacity, swelling kinetics, and permeability. Absorption capacity can be determined as any of centrifugal retention capacity (CRC), free swelling capacity (FSC), and absorbable pressure capacity (AAP). Generally, CRC and FSC are determined under conditions of no external pressure, i.e., 0.0 psi. In both cases, the higher the corresponding CRC or FSC value, the more fluid the particle can absorb. Swelling kinetics can refer to any of VAUL, T20, and Vortex. For irregularly shaped particles with rough surfaces, these three quantities are correlated. For particles with regular, smooth surfaces, or round shapes, Vortex may be uncorrelated with the other quantities. Generally, the faster the particle swells, the smaller the corresponding value of any of these quantities. Permeability (SFC) is non-linearly correlated with CRC capacity. Generally, the higher the permeability value, the better the fluid distribution within the particle's swirling surface. CRC can be interpreted as the simple absorption capacity of the superabsorbent material, SFC can be interpreted as the simple permeability of the open pores in the swollen gel bed of the swollen superabsorbent material, and FSC or AAP can be interpreted as the absorption capacity of the superabsorbent material under defined external pressure conditions. Each includes contributions from the swollen superabsorbent material and contributions from the partially or completely liquid-filled pores (interstitial liquid) in the resulting gel bed. T20, Vortex, and VAUL characteristic swelling times can be interpreted as kinetic swelling rate parameters describing the swelling rate and may include additional effects besides the absorption rate—for example, particle morphology and surface viscosity can affect these measurements. The rate at which liquid is absorbed into the swollen superabsorbent material particles is defined as the absorption rate. These properties and corresponding methods for determining them are further described below. Various other forms of properties or methods for determining corresponding properties exist and can also be used as technical application properties according to the invention. Other methods may differ, for example, in terms of equipment size, such as smaller or larger AAP pools or permeable pools; in terms of treatment technology; in terms of test liquid, such as water or artificial urine instead of saline; and in terms of swelling time, such as 1 minute, 3 minutes, 5 minutes, or 10 minutes instead of 30 minutes. Generally, the choice of absorbency characteristics can depend on the corresponding intended application of the hygiene product, such as as a diaper or a medical product. A particularly useful method for measuring absorbency characteristics is described in WO 2021 / 001221, which allows for the determination of the time-dependent swelling profile of the superabsorbent polymer under varying external pressure. In this way, a characteristic fingerprint profile is obtained, which can be used to define the absorbency characteristics. Particularly useful are online analytical methods, such as those disclosed in WO 2020 / 109601, which enable the determination of absorbency characteristics by Raman spectroscopy analysis within the production process. The combination of such online techniques with online particle size determination makes the present invention highly efficient.In a particularly preferred embodiment, one or more absorption properties of the superabsorbent material indicate at least one of permeability, absorption capacity, and absorption rate. Even 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 comprising superabsorbent polymers. For most applications, the size of the superabsorbent particles is preferably between 100 μm and 850 μm. However, for some applications, larger or smaller superabsorbent particles may also be suitable. Recently, for some hygiene products, a narrower particle size distribution is required, which makes production more difficult and costly, and poses a challenge to optimizing their technical properties, for example, with lower particle sizes of 100 μm, 150 μm, 200 μm, 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. Hereinafter, the terms "interconnected" and "connectivity" refer to the polymer chains of the core or shell portion of the superabsorbent polymer particle being physically entangled, ionicly crosslinked, or covalently crosslinked, such that the corresponding portion of the superabsorbent particle is water-swellable but not water-soluble. Combinations of such methods for interconnecting polymer chains are possible and are commonly found in superabsorbent particles. Ionic crosslinking can be achieved via multivalent cations, a practical example being Mg. 2+ Ca 2+ 、Sr 2+ Al 3+ Ti 4+ Zr 4+Covalent crosslinking can be achieved by adding polymerizable difunctional or polyfunctional olefinic unsaturated crosslinking agents to the monomer mixture. Alternatively, such functional groups can also be provided by groups capable of esterification or transesterification. Mixed functional groups in a single molecule are also possible. For surface crosslinking, the same compounds as described above can be used. Typically, ionic and covalent crosslinking agents are used in combination. Examples of core crosslinking and surface crosslinking are described in WO 2019 / 197194, which is incorporated herein by reference. In this invention, it should be understood that the shell and core of the superabsorbent particle are connected to each other by physical entanglement or ionic crosslinking or preferably by covalent crosslinking. Such a core-shell structure can destroy the surface-shell of the superabsorbent particle upon swelling, but due to the connectivity between the shell and the core, it will continue to exert physical forces on the swollen core even if the shell is completely ruptured. Preferably, the superabsorbent particle refers to a post-crosslinked superabsorbent polymer particle. Such a post-crosslinked superabsorbent polymer particle comprises a crosslinked and thus interconnected core, and then provides a shell with higher connectivity than the core during the post-crosslinking process, while the shell is covalently bonded to the core below it. Optionally, such superabsorbent particles may also have an additional non-superabsorbent coating. Non-limiting examples of such coatings include polymers or polymer films that improve flowability or degrade stability; powder coatings that prevent agglomeration (dry or hydrated forms of silica, alumina, clay, or other inorganic powders); additives that prevent aging or discoloration; additives that combat odors; or functional coatings that react with surfaces, such as Ca2+. 2+ -、Mg 2+ Al 3+ -and Zr 4+ - Salts or their soluble hydroxides, such as those disclosed, for example, in WO 2019 / 197194.

[0013] Furthermore, a quantitative model of the hygiene product is received. In this case, the quantitative model can be received by accessing a storage unit that already stores one or more quantitative models, or by receiving input from a user, for example. This quantitative model includes at least information about the predetermined quantity of liquid at the superabsorbent material layer of the hygiene product over time. Therefore, the quantitative model provides information about the amount of fluid reaching the superabsorbent material layer of the hygiene product over time, allowing for the simulation of different application scenarios. For example, the quantitative model may include curves of one or more fluid volumes versus time at the superabsorbent material layer corresponding to different application scenarios. Furthermore, the quantitative model, particularly the predetermined quantity of liquid at the superabsorbent material layer over time, may also implicitly include information about the corresponding composition and structure of the hygiene product surrounding the superabsorbent material layer. For example, a specific layer utilized in the hygiene product may delay the arrival of fluid introduced into the hygiene product at the superabsorbent material layer, while other components or structures of the hygiene product may cause the fluid introduced into the hygiene product to rapidly concentrate in the superabsorbent material layer. Therefore, these components and structures of the hygiene product can affect the quantity of liquid at the superabsorbent material layer over time. Depending on the intended application of the hygiene product, such corresponding effects can be considered, and a predetermined quantification of the liquid at the superabsorbent material layer over time can be provided accordingly. For example, for different compositions and structures of the hygiene product, measurements can be performed in the laboratory for the corresponding application to determine the predetermined amount and composition of the liquid at the superabsorbent material layer over time. The corresponding information, i.e., the quantification model, can then be received, for example, by user input indicating the corresponding hygiene product and the corresponding application, and then accessing a corresponding database storing the corresponding quantification models for one or more application scenarios. However, if the composition and structure do not strongly affect the quantification model, a standard quantification model for one or more application scenarios can also be provided and accessed to receive the quantification model.

[0014] Furthermore, one or more absorption properties can influence the quantification model. Specifically, the permeability of the superabsorbent material can determine the amount of liquid reaching the superabsorbent layer over time. Therefore, in a preferred embodiment, the quantification model depends on the permeability of the superabsorbent material. In this case, quantification models for different permeabilities can be stored in corresponding memories, and receiving can include selecting the appropriate quantification model from the memory based on the permeability of the superabsorbent material. However, receiving the quantification model can also include modifying the standard quantification model based on the received permeability, for example, correcting the amount of liquid reaching the superabsorbent layer over time based on the permeability of the superabsorbent material, if necessary. Preferably, for example, if the hygiene product includes a liquid management element capable of replacing some or all of the permeability of the superabsorbent material, then the quantification model does indeed include the permeability of the superabsorbent material and the permeability provided by the hygiene product. The liquid management element can be embedded in or positioned above or below the superabsorbent material layer. Examples of embedded liquid management elements are synthetic resin fibers, cellulose fibers, cross-linked cellulose fibers, porous nonwovens, channel structures, and irregularly shaped superabsorbent materials distributed within a core. Examples of adjacent liquid management elements, typically placed above the superabsorbent material layer (e.g., facing the wearer's body), are collection and dispensing layers in the form of porous membranes, nonwovens, cross-linked cellulose fibers, polymer resin top sheets, etc. Such liquid management elements provide pores to or adjacent to the superabsorbent material layer, including the superabsorbent material. This allows for rapid liquid distribution on or within the superabsorbent material layer. Therefore, the superabsorbent material can be provided with the desired permeability in exchange for greater absorbency. Liquid management elements can be used in conjunction with the permeability of the superabsorbent material. One or more liquid management elements can be used in hygiene products, particularly diapers. Preferably, the corresponding quantitative model takes into account the characteristics of such products as described above.

[0015] Furthermore, the device then utilizes a hygiene product characteristic determination model to determine the hygiene characteristics of the hygiene product based on absorption characteristics and a quantitative model. The hygiene product characteristic determination model can be any model that allows for the determination of the hygiene characteristics of the hygiene product based on absorption characteristics and / or a quantitative model. Specifically, the hygiene product characteristic determination model is a mathematical model. In one embodiment, the hygiene product characteristic determination model can be a data-driven model that has been parameterized, for example, based on historical measurement data of hygiene characteristics according to absorption characteristics and a quantitative model. Specifically, the term "data-driven" defines a model that is primarily based on relevant data inputs, rather than, for example, on intuition, personal experience, or knowledge. Specifically, the characteristic determination model can be implemented as any machine learning-based model that is based on known machine learning algorithms, such as neural networks, regression models, classification algorithms, etc.

[0016] Similarly, white-box models evaluated using nonlinear regression optimizers can be used in this invention. Such machine learning models can 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 characteristic determination models include one or more model parameters that can be determined based on corresponding training data. The parameterization of the characteristic determination model is therefore based on training data during the model training process to determine the values ​​of the corresponding one or more model parameters. In particular, the determination model is parameterized so that it can determine the hygienic properties of a hygiene product based on a quantitative model and absorption characteristics. Generally, to parameterize the characteristic determination model accordingly, training methods known for parameterizing a given model can be utilized. In particular, optimization methods can be used to find the best fit of the model parameters to the corresponding training data. For training the characteristic determination model, historical data can preferably be used as training data, for example, historical data including measurement data from various hygiene products with corresponding measurements of hygienic properties of different superabsorbent material layers subjected to different quantitative scenarios.

[0017] However, in a preferred embodiment, the hygiene product characteristic determination model is based on a quantitative model determining the superabsorbent material and ordinary differential equations or partial differential equations relating the absorption characteristics to the hygiene properties. Preferably, in the device according to any one of the preceding claims, the hygiene product characteristic determination model includes solving the following differential equations.

[0018]

[0019] in Describes the free fluid in hygiene products over time. Describe the fluid absorption of superabsorbent materials over time based on their absorption characteristics, and This describes the quantification of fluid entering the hygiene product over time. Preferably, in cases where the penetration is faster than the subsequent liquid absorption by the superabsorbent polymer, the hygiene product provides sufficient void space to capture and distribute the permeated fluid. The inventors have discovered, in particular, that the aforementioned differential equation accurately describes the free fluid in the hygiene product over time as a hygiene characteristic, and that it can be easily solved using known and conventional methods for solving differential equations numerically. Non-limiting examples of useful algorithms are the Euler and Runge-Kutta methods. In particular, these methods are computationally less expensive and faster to implement compared to machine learning methods that directly solve the corresponding differential equations.

[0020] Furthermore, the equipment is configured to generate control data for controlling the production process of hygiene products and / or superabsorbent materials based on the determined hygiene characteristics of the hygiene products. This control data can refer to any data that can affect the production process of the hygiene products in some way. For example, the control data can directly include relevant information about the production process parameters of the hygiene products and / or superabsorbent materials. However, the control data can also include more general information that only allows for the modification of the production process parameters when combined with, for example, a production process control application. Therefore, the control data can be provided in any suitable format. For example, the control data can be provided in a format that allows the control data to be directly implemented in the production process control application. However, the control data can also be provided in a format that must first be converted to the appropriate format. Generally, the control data can be provided directly for controlling the production process, or it can be provided first, for example, to a user for a safety check, wherein the control data is only implemented when the user accepts the control data. Preferably, the method includes relaying the control data to the production control system of the production process.

[0021] In one embodiment, the received one or more absorption properties are measured during the production process of the superabsorbent material and / or a hygiene product including the superabsorbent material, and the generated control data is configured to control and / or monitor the production process based on hygiene properties determined from the measured one or more absorption properties. Specifically, the determined hygiene properties can be evaluated against predetermined target hygiene properties, and control data can be generated based on this comparison. For example, if the determined hygiene properties deviate from the target hygiene properties beyond a predetermined boundary, control and / or monitoring actions can 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 pulverization or gel drying, stopping the chemical reaction, or changing the grinding or sieving procedure, modifying the post-crosslinking step, or the coating step. The measured absorption properties may include the particle size distribution and / or crosslinking characteristics. Preferably, Raman spectroscopy is used to monitor the chemical reactions of the crosslinking process of the superabsorbent particles during the production process and to determine the thickness of the corresponding crosslinked shell having superabsorbent properties. Optical measurements can be used to determine the corresponding particle size distribution during the production process. One or more absorption properties can be continuously measured during the chemical production process for producing superabsorbent materials, where continuous means measuring at predetermined time intervals much smaller than the production process. Directly measuring the absorption properties of the superabsorbent particles during the production process allows monitoring of the resulting hygiene properties of the final product and modification of process parameters if the hygiene properties deviate from predetermined targets. In particular, in-situ measurement during the production process allows avoiding delays in process control that would otherwise be caused by laboratory measurements of absorption properties, and thus leads to direct control and monitoring. In one embodiment, one or more processors are further configured to receive the target hygiene properties of the hygiene product and compare the determined hygiene properties with those target hygiene properties, and i) if the determined hygiene properties are within a predetermined range around the target hygiene properties, then the superabsorbent material is identified as the target superabsorbent material for the hygiene product, and ii) if the determined hygiene properties are outside the predetermined range around the target hygiene properties, then a new superabsorbent material is identified and the hygiene properties of the hygiene product are repeatedly determined using the new superabsorbent material, and wherein control of the production process is based on the identified target superabsorbent material. Preferably, the determination of the new superabsorbent material includes correcting the size distribution of the particles forming the superabsorbent material and / or the amount of superabsorbent material in the layers. Generally speaking, since the size distribution of particles forming superabsorbent materials can have a significant impact on the absorption properties of superabsorbent materials, modifying the size distribution can also allow for changes in the absorption properties of superabsorbent materials, and thus potentially allow for meeting target hygiene characteristics. However, completely different superabsorbent materials can also be provided, such as superabsorbent materials with different compositions or formed from different superabsorbent polymers, as new superabsorbent materials.Furthermore, new superabsorbent materials can also be determined by determining different amounts of superabsorbent material in the corresponding 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 specifically alter these superabsorbent properties and thus potentially allow for the satisfaction of corresponding target hygiene characteristics. Furthermore, all of the aforementioned parameters can be changed in combination. Generally, the determination of new superabsorbent materials can be based on corresponding predetermined rules and, additionally or alternatively, on an iterative method for modifying the corresponding properties until the target hygiene characteristics are satisfied within predetermined limits. For example, the predetermined rules can determine, during the first iteration, to modify the size distribution of the particles forming the superabsorbent material, for example, using a corresponding gradient method for determining the new particle distribution in each iteration step, wherein if, after multiple predetermined steps or if, a predetermined particle size distribution limit (e.g., an upper or lower limit of particle size) is reached, the predetermined rules can determine that for the next iteration, the amount of superabsorbent material in the superabsorbent layer is modified with each iteration step in predetermined increments. 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 can be further restricted for the next iteration by changing the superabsorbent material itself to a different composition, wherein the iteration is then performed again with respect to the particle size distribution of the superabsorbent material.

[0022] In a preferred embodiment, an indication of the amount of superabsorbent material in the hygiene product layer is also received, and one or more absorption properties of the superabsorbent material are adjusted based on the amount of superabsorbent material in the hygiene product.

[0023] In a preferred embodiment, the device further includes one or more processors configured to determine one or more absorption properties of the superabsorbent material based on the particle size distribution of the received superabsorbent material using an absorption property determination model. The property determination model is a data-driven model that has been parameterized to suit determining the technical application properties of the superabsorbent particles based on particle size. The determined one or more absorption properties are then used in a hygiene property determination model. Preferably, the superabsorbent particles of the superabsorbent material comprise a superabsorbent polymer provided in the form of: i) an interconnected core and ii) a surface-crosslinked shell having higher connectivity than the core. The provided absorption property determination model is further parameterized based on the core size and shell size of the superabsorbent particles.

[0024] One or more processors are then further configured to determine the absorption properties of the superabsorbent material based on particle size using an absorption property determination model. Specifically, the absorption property determination model is implemented as a data-driven model, which has been parameterized, for example, based on historical measurement data, making it suitable for determining 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, which is based on known machine learning algorithms such as neural networks, regression models, classification algorithms, etc. White-box models evaluated using nonlinear regression optimizers are particularly useful in this invention. Generally, the absorption property determination model includes one or more model parameters that can be determined based on corresponding training data. The parameterization of the absorption property determination model is therefore based on training data during the model training process to determine the values ​​of the corresponding one or more model parameters. In particular, the absorption property determination model is parameterized so that it can determine the absorption properties of superabsorbent particles based on particle size. Generally, to parameterize the absorption property determination model accordingly, known training methods for parameterizing a given model can be utilized. In particular, optimization methods can be used to find the best fit of the model parameters to the corresponding training data. For training the absorption property determination model, historical data can preferably be used as training data. This includes, for example, measurement data comprising corresponding measurements of the absorption properties of superabsorbent particles, or historical data derived from known physical relationships between the absorption properties of superabsorbent particles and their corresponding measurable characteristics. Specifically, the historical data includes superabsorbent particles of various particle sizes corresponding to one or more absorption properties.

[0025] Since the production process of superabsorbent particles can significantly influence their specific composition, such as the specific interconnectivity of the core and shell, it is preferable to parameterize the absorption property determination model using corresponding historical datasets for specific production processes of the superabsorbent materials being produced. This allows the absorption property determination model to provide a very accurate determination of the absorption properties of superabsorbent materials produced in a specific production process. However, in other embodiments, the absorption property determination model can also be trained using a more general historical dataset that includes data on superabsorbent materials using different production processes. In this case, the absorption property determination model can then learn to distinguish between superabsorbent materials produced in different processes, and the corresponding production process can be provided as further input to the absorption property determination model. Furthermore, the absorption property determination model can be trained to determine one absorption property of the superabsorbent material, but it can also be trained to predict more than one absorption property of the superabsorbent material.

[0026] In a preferred embodiment, the absorption characteristic determination model is further parameterized based on the core and shell sizes of the superabsorbent particles. Surprisingly, the inventors have found that further parameterizing the absorption characteristic determination model based on the core and shell sizes of the superabsorbent particles allows for particularly accurate determination of absorption characteristics. Furthermore, further parameterizing the absorption characteristic determination model based on the core and shell sizes of the superabsorbent particles allows for the separation of the respective influence of each of these parameters on the absorption characteristics. Generally, the core and shell sizes of the superabsorbent particles depend on the particle size, i.e., the penetration depth of the material used in the post-crosslinking process is substantially the same for all particle sizes, such that the size (i.e., volume) of the shell and core depends primarily on the particle size. However, the general penetration depth of the post-crosslinked material, and therefore the thickness of the shell relative to the core, depends on the crosslinking process used, such as the material used, pressure conditions, additives used, temperature, etc. Therefore, further separating the influence of core and shell sizes on absorption characteristics not only allows for the control of absorption characteristics using the size of the superabsorbent particles, but also allows for the determination of the influence of shell and core sizes on absorption characteristics, thus also allowing for the optimization of the post-crosslinking process of the superabsorbent particles regarding the characteristics of the technology application.

[0027] Preferably, the parameterization of the absorption characteristic determination model includes determining performance parameters that quantify the contributions of the core size and shell size of the superabsorbent particle to the absorption characteristics. Using corresponding training datasets for multiple superabsorbent particle sizes, including corresponding core sizes, shell sizes, and absorption characteristics, allows the absorption characteristic determination model to be parameterized, enabling the influence of core size and shell size on absorption characteristics to be accurately quantified by determining the performance parameters. Preferably, the absorption characteristic determination model is based on the following relationship between absorption characteristics and the size of the superabsorbent particle.

[0028]

[0029] Where Vshell is the volume of the shell of the superabsorbent particle, and Vcore is the volume of the core of the superabsorbent particle, the volumes of the shell and core of the superabsorbent particle depend on the size of the superabsorbent particle, and var 壳 and var 芯 These are performance parameters that quantify the contributions of core size and shell size, respectively, and are determined during the parameterization of the characteristic determination model, where var 颗粒 Indicates the measured absorption characteristics.

[0030] In one implementation, the received particle size is the particle size distribution of the superabsorbing particles in the superabsorbing material. In this case, based on the particle size distribution, one or more particle size classes can be determined from a predetermined set of particle size classes, for which particles of corresponding sizes are present in the superabsorbing material. Absorption characteristics can then be determined for the determined particle size classes, and the overall application characteristics of the superabsorbing material can be determined based on the determined absorption characteristics for the corresponding determined particle size classes and based on the particle size distribution. Generally, the particle size distribution of superabsorbing particles can be received in the form of any data information indicating the particle size present in a statistically relevant sample of the superabsorbing material. For example, the particle size distribution can be provided in the form of a list of all sampled superabsorbing particles and superabsorbing particles of corresponding sizes. However, the particle size distribution can also be provided directly in the form of a gradation distribution, which indicates the amount of particles present in a statistically relevant sample for multiple particle size classes. Generally, a particle size class refers to a particle size range and is defined by a minimum and a maximum particle size that defines that range. If the particle size distribution is provided in the form of a graded distribution, the corresponding predetermined particle size grade may refer to the particle size grade that has been used, wherein in this case, determining whether particles are present at the predetermined particle size grade is equivalent to determining whether the amount of particles greater than zero is indicated by the particle size grade distribution in the corresponding particle size grade. However, the predetermined particle size grade may also be independent of any previously used particle size grade to provide the particle size grade distribution. In this case, appropriate statistical methods can be used to determine which grade of the predetermined particle size grade has particles present in the superabsorbent material. Furthermore, if a list of particle sizes is provided as a particle size distribution, the predetermined particle size grades can be used to classify the particle sizes accordingly and determine which predetermined particle size grade has at least one particle. Preferably, for example, the particle size distribution of the water-absorbing polymer particles can be determined by the test method number WSP 220.3(11) "Particle Size Distribution" recommended by EDANA. Furthermore, optical methods such as laser diffraction, photographic analysis, beam arrays, and spatial filtering velocimetry can be advantageously used. The probe, etc., is preferably calibrated according to EDANA or the corresponding ISO test method based on screening analysis. Such calibration may also depend on particle characteristics other than particle size, and is therefore specific to each product grade. In this invention, such calibration methods are particularly useful because they can be used online at one or more locations in the production process and provide the necessary particle size information in real time.

[0031] The absorption characteristics of the determined particle size class are then determined using an absorption characteristic determination model for corresponding particle sizes falling within a predetermined particle size class. Generally, this absorption characteristic can be determined by providing the absorption characteristic determination model with at least one particle size falling within a predetermined particle size class and using the determined absorption characteristic as a technical application characteristic for all sizes falling within the determined particle size class. However, the minimum and maximum sizes of particles falling within the corresponding determined particle size class can also be used as inputs to the absorption characteristic determination model, and the corresponding determined absorption characteristics can be statistically combined, for example, by averaging, to determine the absorption characteristics representing the corresponding determined particle size class. However, other statistical methods can also be used accordingly. The overall absorption characteristic can then be determined based on the absorption characteristics determined for the corresponding determined particle size class and based on the particle distribution. In particular, the amount of particles falling within the corresponding determined particle size class is considered when determining the overall absorption characteristic. For example, a weighted average can be used to determine the overall absorption characteristic based on the determined absorption characteristics, wherein the weights of the weighted average are determined based on the amount of particles in the particle distribution falling within the corresponding particle size class. For example, if more particles fall within a particle size class, the corresponding absorption characteristic may have a higher weight than the absorption characteristic corresponding to a particle size class with fewer particles. Furthermore, other known or learned relationships may be considered, for example, in the weighting used to determine the overall absorption characteristic. For instance, it may be determined that larger particles generally have a higher impact on the overall absorption characteristic than smaller particles. In this case, a higher weight may be given to the particle size class with larger particles relative to the weighting of the particle size class with smaller particles. However, for some absorption characteristics, it may be determined that smaller particles generally have a higher impact than larger particles. In this case, a higher weight may be given to the particle size class with smaller particles relative to the weighting of the particle size class with larger particles. Generally, for absorption capacities with and without external pressure, an arithmetic mean can be used to predict the overall product characteristics from a single particle size class. This is not the case for performance-critical characteristics such as swelling kinetics and liquid permeability, and rather complex mixing characteristics have been found for blends of superabsorbent particles with different properties, as described, for example, in WO 2019 / 137833. This is due to the fact that for such blends, not only are size-grade-specific properties relevant, but the complex mixing phenomena based on the amount of particles present in different size grades also show a significant impact on overall performance. While finer particles may be advantageous for achieving rapid liquid absorption, they can counteract this in terms of liquid distribution because they can rapidly clog fluid conduction pores. To predict such properties, a weighted average of size grades can be used, which does not treat all particle sizes equally and can depend on the number of particles in each grade.In this invention, the weights are preferably determined experimentally by first measuring the overall performance characteristics of the superabsorbent polymer, then classifying it into corresponding discrete size classes and determining the characteristics of each class. Mixing the corresponding classes with each other in different amounts allows the desired weights to be determined. For such mixing, experimental design can be used. Then, in all further processing, the determined overall absorption characteristics are used as the absorption characteristics of the corresponding particle size distribution, especially for determining hygiene characteristics.

[0032] In another aspect of the invention, a system for controlling the production of hygiene products and / or superabsorbent materials is proposed, wherein the hygiene product comprises a layer of superabsorbent material provided in the form of superabsorbent particles, wherein the system comprises: i) an interface unit configured to receive a) one or more production parameters for producing the hygiene product and b) a target hygiene characteristic of the hygiene product, and to determine one or more absorption characteristics of the superabsorbent material and / or a quantitative model of the hygiene product based on the received one or more production parameters; ii) an apparatus according to any one of the preceding claims, wherein the apparatus is configured to receive the absorption characteristics and / or quantitative model of the superabsorbent material from the interface unit, and is configured to determine the hygiene characteristic, and further configured to compare the determined hygiene characteristic with the target characteristic, and if the determined hygiene characteristic is outside a predetermined range around the target hygiene characteristic, to generate a control signal for correcting one or more of the one or more production parameters for producing the hygiene product and / or the superabsorbent material. Generally, corrections to one or more production parameters for producing the hygiene product and / or the superabsorbent material can be generated according to rules predetermined based on process knowledge. For example, if a predetermined hygiene characteristic lies within a predetermined range around a target hygiene characteristic, a rule can instruct, for instance, that a particular production parameter should be reduced in predetermined increments until the hygiene characteristic again falls within a predetermined range around the target hygiene characteristic. Such rules can typically be based on experimentation or prior experience with the production process.

[0033] In another aspect of the invention, a computer-implemented method for determining the hygienic properties of a hygiene product is proposed, wherein the hygiene product comprises a layer of superabsorbent material provided in the form of superabsorbent particles, wherein the method comprises the steps of: i) receiving a) one or more absorption properties of the superabsorbent material, and b) a quantitative model of the hygiene product, the quantitative model comprising a predetermined amount of liquid at the superabsorbent material layer of the hygiene product over time, ii) using a hygiene product property determination model to determine the hygienic properties of the hygiene product based on the absorption properties and the quantitative model, and iii) generating control data for controlling the production process of the hygiene product and / or the superabsorbent material based on the determined hygienic properties of the hygiene product.

[0034] In another aspect of the invention, a computer-implemented method for controlling the production of hygiene products and / or superabsorbent materials is proposed, wherein the hygiene product comprises a layer of superabsorbent material provided in the form of superabsorbent particles, wherein the method comprises: i) receiving a) one or more production parameters for producing the hygiene product and b) a target hygiene characteristic of the hygiene product; ii) determining one or more absorption characteristics of the superabsorbent material and / or a quantitative model of the hygiene product based on the received one or more production parameters; iii) determining hygiene characteristics based on the received absorption characteristics of the superabsorbent material and / or the quantitative model according to claim 11; and iv) comparing the determined hygiene characteristics with the target characteristics, and generating a control signal for correcting one or more of the one or more production parameters for producing the hygiene product and / or the superabsorbent material if the determined hygiene characteristics are outside a predetermined range around the target hygiene characteristics.

[0035] In another aspect of the invention, a computer program product for determining the hygienic properties of a hygiene product is provided, wherein the computer program product includes program code components for causing the device described above to perform the method described above.

[0036] In another aspect of the invention, a computer program product for controlling the production of hygiene products and / or superabsorbent materials, wherein the computer program product includes program code components for causing the device described above to perform the method described above.

[0037] It should be understood that the methods, devices, and computer program products described above have similar and / or identical preferred embodiments, particularly the preferred embodiments as defined in the dependent claims.

[0038] It should be understood that preferred embodiments of the present invention may also be any combination of the above embodiments with corresponding dependent claims or dependent claims.

[0039] These and other aspects of the invention will be apparent and set forth with reference to the embodiments described below. Attached Figure Description

[0040] In the following figures:

[0041] Figure 1 A system for controlling the production of hygiene products and / or superabsorbent materials used in hygiene products is illustrated schematically and exemplary.

[0042] Figure 2 A flowchart illustrating, and by way of example, is shown for a method of controlling the production of hygiene products and / or superabsorbent materials used in hygiene products.

[0043] Figures 3a, 3b, and 3c schematically and exemplaryly illustrate one-dimensional, two-dimensional, and three-dimensional models used to determine the hygienic properties of hygiene products, respectively.

[0044] Figures 4a to 4d schematically and exemplary illustrate the application of the present invention in the control process for the production of hygiene products and / or superabsorbent materials, and

[0045] Figure 5 The use of Torricelli's law for quantitative models is illustrated schematically and exemplarily. Detailed Implementation

[0046] Figure 1 A system 100 for controlling the production of hygiene products and / or superabsorbent materials used in hygiene products is illustrated schematically and exemplary. System 100 includes a device 110 for determining the hygiene properties of the hygiene products. Furthermore, the system includes an interface unit 120 for engaging with a production system 130 for producing hygiene products and / or superabsorbent materials for hygiene products. Device 110 can be implemented as any dedicated or general-purpose computing hardware including one or more processors. In particular, device 110 can be implemented in distributed computing, where different functions of the device are performed by different processors in the same or different locations. Then, by performing [the process]... Figure 2 The functions defined by the described method are implemented in device 110. Generally speaking, the functions performed by device 110 may be performed, for example, by receiving unit 111, hygiene characteristic determination unit 112, and control data generation unit 113.

[0047] Device 110 is configured to determine the hygienic properties of a hygiene product. A receiving unit 111 of device 110 is configured to receive one or more absorption properties of a superabsorbent material. For example, receiving unit 111 may be configured to utilize a user interface into which a user can input a corresponding superabsorbent material to be used in the hygiene product. Based on the input superabsorbent material, receiving unit 111 may then be configured to access a storage unit or library where the absorption properties of various superabsorbent materials are stored. Alternatively, receiving unit 111 may also receive the absorption properties of superabsorbent materials directly from the user via an input interface. Alternatively, corresponding superabsorbent materials with associated one or more absorption properties may be predetermined for use in all cases without further notification. However, in a preferred embodiment, system 100 may further include or be communicatively coupled to device 140 for determining the absorption properties of the corresponding superabsorbent material.

[0048] The device 140 includes, for example, a receiving interface 141, one or more processors 142, and an output interface 143. Generally, the device is configured to determine the absorption characteristics of a superabsorbent material. The superabsorbent material is preferably provided in the form of superabsorbent particles, which comprise superabsorbent polymers provided in the form of interconnect cores and surface cross-linked shells, the surface cross-linked shells having higher connectivity than the interconnect cores. Generally, the device 140 can be provided as a standalone device, for example, as a dedicated computing device, but can also be provided as part of a more general-purpose computing device providing additional functionality. In particular, the device can be provided as part of a quality control system, or, for example, as part of a production control system.

[0049] In this example, receiving interface 141 is configured to receive the particle size of the superabsorbent particles of the superabsorbent material. Generally, the receiving interface can be implemented as any interface that allows receiving corresponding data indicating the particle size. Specifically, the receiving interface can be configured as a storage unit providing the interface on which the particle size has been stored. However, device 110 may also provide the particle size, or the control system of production system 130 may provide sensor measurements indicating the particle size. Particle size can refer to any quantity that allows quantification of the particle volume of the superabsorbent particles of the superabsorbent material. Preferably, particle size refers to the volume of the particles, or if the particles can be approximated as spherical particles, it refers to the radius or diameter of the particles. The particle size of the superabsorbent particles is typically provided in the dry state of the superabsorbent particles, i.e., before fluid is absorbed into the superabsorbent particles, causing an increase in the size of the superabsorbent particles. The received particle size of the superabsorbent particles is then provided to one or more processors 142.

[0050] The one or more processors 142 are then configured to determine the absorption properties of the superabsorbent material based on particle size using an absorption property determination model. For example, the one or more processors may be configured to access storage units on which absorption property determination models are stored. Generally, more than one absorption property determination model may be stored in the storage unit; for example, property determination models for different superabsorbent materials produced according to manufacturing specifications, such as using different superabsorbent polymers, different crosslinking methods, and / or production parameters, may be stored. In this case, the one or more processors may then be configured to select the appropriate absorption property determination model for the superabsorbent material using relevant information about the superabsorbent material, such as 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, the one or more processors may be configured to select all absorption property determination models available for the corresponding superabsorbent material and then apply each of the absorption property determination models to determine all absorption properties available for the corresponding superabsorbent material, or, based on further information about the desired absorption properties provided, for example, via a user interface, the one or more processors may be configured to select the appropriate absorption property determination model to utilize.

[0051] Generally, absorption characteristic determination models are parameterized to make them suitable for determining the absorption characteristics of superabsorbent particles based on particle size. In particular, data-driven determination models can be any machine learning-based model that allows learning from historical data to determine the absorption characteristics of superabsorbent particles based on particle size. For example, absorption characteristic determination models can refer to regression model-based algorithms such as neural network algorithms, lasso algorithms, ridge regression algorithms, principal component regression methods, robust multiple linear regression, MASS algorithms, or random forest algorithms. However, absorption characteristic determination models can 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 Chemometers, K. Varmuzza, P. Filzmoser, CRC Press, New York 2009," which is explicitly incorporated herein by reference. In particular, it is preferable to further parameterize the utilized absorption characteristic determination model based on the core and shell sizes of the corresponding superabsorbent particles to allow quantification and determination of the respective contributions of core and shell sizes to the corresponding absorption characteristics. This allows for storing the absorption characteristic determination model by storing the corresponding performance parameters of the quantified contributions. The absorption characteristic determination model can then be selected by choosing performance parameters corresponding to the corresponding core size and shell size and using these performance parameters in the absorption characteristic determination model.

[0052] Generally, an absorption property determination model can be trained in any known manner. In particular, the model is trained using historical training data. This historical training data includes at least two, preferably multiple, granularities for superabsorbent materials and one or more corresponding measured absorption properties of the superabsorbent material. Such training data can be generated, for example, by measuring the corresponding superabsorbent material using known measurement methods for determining absorption properties and also for measuring the corresponding granularity of the superabsorbent material. Generally, such historical training data is typically generated during the quality control of the superabsorbent material or during the design process of the superabsorbent material in which the corresponding measurements are performed. The absorption property determination model can then be parameterized using the historical training data, such that the parameterized model is suitable for determining the absorption properties of the superabsorbent material based on granularity. For example, known machine learning (i.e., parameterization) methods can be used. Based on such a trained property determination model, one or more processors 142 of device 140 are then configured to determine the absorption properties of the superabsorbent material based on the provided granularity. The determined absorption properties, and optionally the utilized granularity, can then be provided to device 110. Therefore, the device for determining the absorption properties of superabsorbent materials allows for the determination of absorption properties of superabsorbent materials not directly stored in a database or library. In particular, in most cases, the effect of particle size can be determined more accurately when using device 140.

[0053] Furthermore, receiving unit 111 receives a quantitative model of the hygiene product, which includes a predetermined quantity of liquid at the superabsorbent material layer of the hygiene product over time. Generally, the quantitative model allows for the specification of the appropriate application for which the hygienic properties of the hygiene product should be determined. Additionally, the quantitative model can implicitly take into account different compositions and structures of the hygiene product, particularly those that affect the reach of the fluid applied to the hygiene product to the superabsorbent material in the superabsorbent layer.

[0054] The hygiene characteristic determination unit 112 is then configured to use a hygiene product characteristic determination model to determine the hygiene characteristics of the hygiene product based on absorption characteristics and a quantitative model. A preferred example of such a product characteristic determination model will be described below with reference to Figure 3a.

[0055] Figure 3a schematically and exemplary illustrates a one-dimensional (1D) model for determining the hygienic properties of a hygiene product. However, the model can also refer to more dimensions, for example, it can be a 2D model or even a 3D model, as shown in Figures 3b and 3c. In the case of a 1D model, ordinary differential equations that only include a function of time can be used, while in 2D and 3D models, partial differential equations that include functions of time t and spatial liquid distribution can be utilized. In a 2D model, the hygiene product can be mathematically divided into stripes to describe the liquid distribution in only one direction, while in a 3D model, the liquid can be described as distributed in two spatial orientations, such as the liquid distribution in the x and y directions. Such 2D and 3D models are illustrated in Figures 3b and 3c. To optimize the absorption properties of superabsorbent polymers in hygiene products, a simple 1D model is sufficient in most cases, while a 2D or 3D model is preferred to optimize the hygiene product itself.

[0056] The model shown in Figure 3a is a 1D model, in which, in this example, layers comprising a superabsorbent material and optionally a fluffy material are illustrated. Furthermore, the model illustrates the fluid source used for the quantitative model, here a funnel reservoir. Additionally, in some cases, the model also includes the effect of the pressure supplied to the superabsorbent material layer, as indicated by the weight shown. Arrows indicate possible flow directions of fluid from the reservoir within the layer. In this model, the free fluid in the layer can be described, for example, based on a differential equation comprising three terms, specifically a term indicating quantitative flow, a term indicating liquid absorption, and a term indicating unabsorbed free liquid. Preferably, the model is based on a differential equation.

[0057]

[0058] in Describes the free fluid in hygiene products over time. Describe the fluid absorption of superabsorbent materials over time based on their absorption characteristics, and Describes the quantitative amount of fluid entering the hygiene product over time. Quantitative item. This can be expressed as the differential form of Torrizel's law, as a gravitational quantification used in many laboratory tests, through which the target hygiene properties in a hygiene product can be defined. In Torrizel's law, the effective cross-sectional area A2 is the bottleneck for the outflowing fluid into the hygiene product and represents the fluid permeability of the product under use, testing, or simulation conditions. For example, the quantification term... It can be represented as:

[0059]

[0060] Where A2 is the effective cross-sectional area of ​​the inflow pad and A1 is the cross-sectional area of ​​the cylinder, v1 and v2 are the velocities of the liquid flow, as shown below. Figure 5All parameters are shown in the table. Generally, A2 can be set according to the permeability characteristics of the sanitary product, especially considering the permeability of the superabsorbent material and surrounding structure. For example, for high-permeability areas, A2 can be set higher than the lower permeability of the sanitary product. v2 depends on the gravity and height of the liquid in the cylinder and can be adjusted according to... The calculation is performed, where h is the height of the liquid in the cylinder and g is the gravitational constant. Based on this, the liquid discharge time (also known as the collection time) can be calculated using the following formula.

[0061]

[0062] Where h t＝0 This refers to the height of the liquid in the cylinder at the start of the metering process. Furthermore, the collection time determines the time it takes for the liquid to be completely collected by the hygiene product and can therefore also depend on the product's construction. Both collection time and free liquid can be optimized as hygienic properties of the hygiene product.

[0063] Alternatively, the quantification term can be any coded liquid quantification profile simulating a pump or natural flow, and can include the effects of liquid management elements or inefficiencies observed in the hygiene product. In this invention, one or more subsequent liquid quantifications in the hygiene product can be simulated to define one or more target hygiene characteristics. An example of a target hygiene characteristic is the amount of free liquid remaining in the hygiene product at a simulated time and after a certain amount of liquid has been quantified. More than one time point can be defined to calculate the amount of free liquid and define the target hygiene characteristic. Another example of a target hygiene characteristic is the collection time required to absorb all liquid in the hygiene product up to a preset threshold for one or more subsequent flows. Another example of a target hygiene characteristic is the maximum amount of free liquid available in the hygiene product after each flow. Yet another example of a target hygiene characteristic is simulating the free liquid available in the hygiene product over time and as an integral over one or more subsequent flows.

[0064] The absorption of a fluid is preferably described by the following equations, which include the absorption characteristics:

[0065]

[0066] The absorption characteristic in the above equation can be the free swelling absorption capacity Q, which can be determined, for example, as CRC or FSC, or, if external pressure is applied during the absorption process, as the resistance absorption (AAP). Furthermore, the characteristic absorption time tau can be used as an absorption characteristic to describe the time dependence of the absorption process. Both tau and Q can be functions of the external pressure p during the absorption process. Qmax refers to the maximum absorption capacity equal to the equilibrium swelling capacity after an infinite or experimentally reasonable long swelling time. Since permeability is generally inversely proportional to the equilibrium absorption capacity, permeability can be indirectly derived for optimization purposes.

[0067] In the 1D model, it is preferably assumed that the liquid immediately and evenly distributes to all accessible superabsorbent materials, and that all superabsorbent materials in the layer have the same degree of swelling. However, for this model, not all superabsorbent materials are necessarily accessible. In this model, the absorbent layer is not spatially discretized. Figure 3b schematically and exemplaryly illustrates a model of a hygiene product in 2D form. In this case, the absorbent layer is spatially discretized in one direction. Preferably, since most hygiene products have absorbent layers with a predetermined layer thickness and longer in one direction than in the other remaining directions, discretization is performed in the longer direction of the layer. However, the discretization direction can also be in the direction in which the greatest variation in the superabsorbent layer is expected. In this 2D model, it is preferably assumed that the liquid diffuses isotropically to all accessible superabsorbent materials, and that the superabsorbent material swells once the liquid reaches the superabsorbent material layer. Figure 3c schematically and exemplary illustrates a model of a hygiene product in 3D form. In this case, the absorbent layer is spatially discretized in two directions. Preferably, the two directions are the directions in which the superabsorbent layer extends on the surface of the hygiene product, i.e., the layer thickness is not discretized. In this scenario, it is assumed that the liquid diffuses isotropically to all accessible superabsorbent materials, and that the superabsorbent materials swell once the liquid reaches them.

[0068] In the model, only superabsorbent properties are considered, preferably, the absorption capacity, absorption rate, or permeability at the operating pressure. For example, this can be determined experimentally based on synthetic sanitary products, such as in the case of SAP-fluff mixtures, by experimental design to provide a quantitative model, and thus provide a quantitative measure of the fluid over time. Preferably, the quantitative model further considers the permeability of the superabsorbent material or the combined permeability of the mixture. This can be achieved, for example, again by quantitative experimental measurements, and also by utilizing known physical relationships between the permeability of the material and the possible fluid flow through the material, such as using Torrischeli's law. However, the quantitative model can also be a theoretical quantitative model that does not consider the permeability of the sanitary product or its specific arrangement. Such theoretical quantitative models are particularly useful for comparing different superabsorbent materials, especially comparing the effects of different superabsorbent properties in a theoretical setting. The model can then calculate the time-dependent amount of unabsorbed (i.e., free) fluid changing with absorption capacity, the amount of superabsorbent, and the time elapsed after collection. Free liquid is a preferred hygienic property because it determines the amount of unabsorbed liquid present in the hygienic article at time t after the flow, and determines the degree of dryness of the article after a predetermined time following each liquid flow.

[0069] The experimental determination of unabsorbed liquid (rewetting) is cumbersome because it is conducted by applying predetermined pressure to squeeze out the unabsorbed liquid after a predetermined elapsed time t (t = 1 min – 20 min) following each flow, via absorbent paper placed on top of the sanitary product. The quantification volume, the quantification sequence, and the time t used for rewetting determination are variable and differ for different applications. Since the experimental method can only provide such rewetting data at a fixed time for each sanitary product, and typically only at the end of the test after the last flow, two complete test series are required, for example, to examine two different t values ​​for a superabsorbent grade used at the same concentration and in the same sanitary product design. Therefore, changing the superabsorbent grade, superabsorbent concentration, quantification sequence, and rewetting test time (t) involves a significant amount of manual labor, which slows down the development and commercialization of optimized superabsorbents. For example, as mentioned above, the model enables such changes to be made quickly, for example, via a grid search across a matrix having these characteristics, with far less manual labor and significantly less time consumption. Unlike manual rewetting methods, this approach generates time-dependent drying profiles, allowing for the derivation of the optimal balance between absorbability, absorption rate, and liquid permeability for varying rewetting time requirements. To achieve this, the model can utilize experimental information on absorption characteristics, such as absorbability, absorption rate, and liquid permeability, determined experimentally for pure superabsorbents and stored in a database. Alternatively, absorbability and absorption rate at least under external operating pressure can be estimated using the theory described in FLBuchholz, AT Graham, Modern Superabsorbent Polymer Technology, Wiley-VCH, Weinheim, 1998. Furthermore, as mentioned above, appropriate data-driven models can also be used. In particular, the effects of particle size distribution on absorbability, absorption rate, and permeability can be accurately modeled using the data-driven models described above, since absorption rate and permeability are typically non-linear functions of particle size mixing, and it is important during production to approximate a constant particle size distribution with an optimal performance balance that is as close as possible to these parameters. In a preferred embodiment, the model is based solely on permeability and absorption rate.

[0070] The control data generation unit 113 can then generate control data for controlling the production process of hygiene products and / or superabsorbent materials based on the determined hygiene characteristics of the hygiene products. The control data is... Figure 1The image is indicated by arrow 114. In a preferred embodiment, control data is generated for direct control of the production process performed by production unit 130. In this case, production parameters for producing the hygiene product indicated by arrows 115 and 116 are provided to device 110 via interface unit 120. In this case, interface unit 120 is further configured to determine one or more absorption properties of the superabsorbent material based on one or more production parameters and / or to determine a quantitative model of the hygiene product based on the received one or more production parameters. For example, the production parameters may indicate which superabsorbent material is used to produce the hygiene product, and interface unit 120 may then utilize the same database or library as receiving unit 111. However, interface unit 120 may also utilize device 140 to determine absorption properties, for example, based on the particle size of the superabsorbent material, using a corresponding absorption property determination model. However, other knowledge, such as other databases and libraries, may also be utilized that correlates, for example, one or more production properties of the superabsorbent material with corresponding absorption properties, or correlates one or more production properties of the hygiene product with corresponding quantitative models. However, the absorption properties and / or quantitative models of the superabsorbent material may also be provided to the interface unit from the user, for example, via input unit. Furthermore, interface unit 120 can receive the target hygiene characteristics of the hygiene product. Then, as indicated by arrow 116, the corresponding received and / or determined parameters are provided to device 110, which can then predict the hygiene characteristics of the produced hygiene product based on the provided parameters, as described above. This allows for avoiding multiple measurements of the hygiene characteristics of the hygiene product during production. Based on the determined hygiene characteristics of the hygiene product, device 110, such as control data generation unit 113, can then be configured to further compare the determined hygiene characteristics with the target hygiene characteristics. If the determined hygiene characteristics are outside a predetermined range around the target hygiene characteristics, a control signal can be generated to directly correct the production parameters used to produce the hygiene product and / or superabsorbent material. Generally, the correction of production parameters can be based on known rules, such as rules determined experimentally or empirically, which indicate that deviations in a particular hygiene characteristic can be corrected by incrementally adjusting the corresponding production parameters.

[0071] Additionally or alternatively, the device 110 can also optimize the hygiene product using target hygiene characteristics, particularly before the production of the hygiene product, and then provide corresponding control data for the production of the optimized hygiene product. In this case, the device 110, such as the control data generation unit 113 or the characteristic determination unit 112, can be further configured to compare the determined hygiene characteristics with the target hygiene characteristics. Based on the comparison, in particular, if the determined hygiene characteristics meet the target hygiene characteristics within predetermined limits, the corresponding superabsorbent material used, in particular the particle size distribution, composition, and amount of the superabsorbent material, can be set as the target superabsorbent material. However, if the comparison result shows that the determined hygiene characteristics do not meet the target hygiene characteristics within predetermined limits, a new superabsorbent material can be determined, and the hygiene characteristics of the hygiene product can be repeatedly determined using the new superabsorbent material. This optimization can then be performed iteratively until a termination criterion is met, such as a predetermined number of iteration steps, or a superabsorbent material that can be set as the target superabsorbent material is found. New superabsorbent materials can be determined by modifying, for example, the size distribution of the particles forming the superabsorbent material, the composition of the superabsorbent material itself, and / or the amount of superabsorbent material in the superabsorbent layer. Any of these variables in a hygiene product can have a corresponding impact on the absorption properties of the superabsorbent material, and thus allow for the finding of superabsorbent materials that meet the target hygiene properties during iteration.

[0072] Figure 2 A method for controlling the production process of superabsorbent materials and / or hygiene products including superabsorbent materials is illustrated schematically and exemplary. Generally, the method includes the steps of receiving the absorption characteristics of the superabsorbent material and receiving a quantitative model indicating the application and / or composition of the hygiene product. Optionally, the receiving of the absorption characteristics is based on production parameters of the production of the received hygiene product, such as those described above regarding... Figure 1 As described above. In another step, the hygienic properties of the hygiene product are then determined using the corresponding absorption characteristics and quantitative models of the absorption. The models used may refer to those described above regarding... Figure 1The differential equation model is described in more detail in Figure 3. In an optional step, the method may further include receiving a target hygiene characteristic and further comparing the determined hygiene characteristic with the target hygiene characteristic. Based on the comparison, a new hygiene characteristic can then be determined, in particular, if the deviation is found to be higher than a predetermined limit, and the model is again used to determine the hygiene characteristic of the new superabsorbent material; or if the deviation is below the predetermined limit, the corresponding superabsorbent material can be identified as the target superabsorbent material. Control data can then be generated directly based on the determined hygiene characteristics, for example, for directly controlling the production process of the superabsorbent material or hygiene product to meet the corresponding target hygiene characteristics of the final product, or control data can be generated based on the target superabsorbent material, for example, by instructing the production process to utilize the correspondingly determined target superabsorbent material.

[0073] Figure 4a schematically and exemplaryly illustrates a more detailed example of applying the above invention to the production of a specific hygiene product. Specifically, first process parameters such as polymerization, drying, and sieving, as well as formulation parameters, are provided for the corresponding superabsorbent material. These parameters allow for the determination of the corresponding base polymer that can be used to produce the superabsorbent particles. The base polymer used to produce the superabsorbent particles includes characteristics such as capacity, swelling time, particle size distribution, and particle morphology. Based on these characteristics, the formulation and production process, along with corresponding parameters, referred to as SXL parameters, can be further determined. This complete production process then results in the production of superabsorbent particles, which include corresponding absorption properties, particularly capacity, swelling time, and permeability. These superabsorbent particle parameters, along with diaper target performance parameters indicating the diaper's target hygiene properties (such as free liquid after a predetermined amount of time), can then be provided to a hygiene property determination model based on differential equations, as described above, for example, with respect to Figure 3. The model then allows the calculation of diaper performance, particularly hygiene properties, from the superabsorbent particle parameters and the comparison of the calculated diaper performance with the target performance. Based on this comparison, process and formulation parameters can then be adjusted using, for example, machine learning, white-box models, or a combination thereof, to optimize hygiene products (in this case, diapers) to meet target performance.

[0074] Figures 4b and 4d illustrate the production of superabsorbent particles in more detail and which steps in the production process can be optimized based on target performance. In Figure 4b, the optimization process is configured to optimize the production of superabsorbent materials in all production steps. Arrows at corresponding steps indicate whether process or formulation parameters can be modified at that step to optimize the superabsorbent material. Generally, optimization can be performed using a hygienic property determination model based on differential equations, as described above, for example, with respect to Figure 3, to determine the corresponding hygienic properties and compare them with the corresponding target performance (i.e., with target hygienic properties), as described with respect to Figure 4a. Figure 4c shows the optimization process where only steps in the production of superabsorbent materials without surface adaptation (e.g., without surface crosslinking and / or coating steps) are optimized. Furthermore, in this example, the hygienic property determination model has already determined the optimal target absorption properties of the superabsorbent material, which allow for the provision of the corresponding target performance of the hygienic product. Therefore, in this case, optimization can be performed directly by comparing the absorption properties of the superabsorbent material, determined, for example, using the corresponding absorption property determination model as described above, with the target absorption properties. Another optimization process is illustrated in Figure 4d, which only shows the final steps in the production of the superabsorbent material involving surface adaptation (e.g., crosslinking). Again, in this case, it is exemplarily shown that optimization can be performed directly based on the target absorption characteristics of the absorbent material previously determined relative to the target performance of the hygiene product.

[0075] Although the invention has been described using a differential equation-based model in the above embodiments, other models can also be used, especially data-driven models implemented as machine learning models trained on corresponding historical training data.

[0076] To improve diaper performance and develop / supply sufficient superabsorbent polymers (SAPs), it is necessary to understand how many different performance parameters affect good diaper performance. This has historically been accomplished through trial and error and incremental development activities. However, due to increasing market complexity, evolving diaper designs, and increased commoditization, there is now a need to develop methods that drive innovation more effectively and efficiently. Therefore, computational methods are needed to define key performance SAP parameters and select the optimal set of parameters in superabsorbent polymers to enable the rapid development of superabsorbent polymers that will produce improved diaper performance.

[0077] The invention, in particular, allows for improved balance between absorbability, absorption rate, and collection rate, necessitating optimization of this balance to suit specific application tests and / or consumer preferences. This invention enables more effective decision-making in the development of new hygiene products.

[0078] In the above description, various absorption characteristics are described, which in most cases are defined by the corresponding measurement or test methods used to determine the absorption characteristics. The corresponding sources of details in these measurement and test methods are provided below. Generally speaking, various methods for determining the absorption characteristics of superabsorbents are available in publications as industry standards, specified by user applications, or widely used in the market based on experience. For example, methods for determining FSC, CRC, and AAP characteristics are available as EDANA methods from the European Disposables and Nonwovens Association (EDANA). Specifically, for FSC characteristics, the measurement method is described in standard NWSP 240.0.R2(15), for CRC characteristics, the measurement method is described in standard NWSP 241.0.R2(15), and for AAP characteristics, the measurement method is described in standard NWSP 242.0.R2(15). In addition, the national test methods of the People's Republic of China are available from the PRC Standardization Management Committee. Furthermore, for example, a method for measuring saline conductivity (SFC) is disclosed in patent publication EP 0752892 B1. For example, a method for measuring volumetric absorbance under load (VAUL) is disclosed in patent publication EP 2922882 B1. For example, a method for measuring T20 absorption kinetics is disclosed in patent publication EP 2535698A1. Additionally, an exemplary method for measuring vortex absorption kinetics is disclosed in the article "Modern Superabsorbent Polymer Technology," Buchholz FL and Graham AT, 1st edition, Weinheim: Wiley-VCH, 1998, page 155. Furthermore, an automated method for measuring AAP is disclosed in patent application WO 2021 / 001221 A1.

[0079] In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality.

[0080] A single unit or device can perform the functions of several items recited in the claims. The fact that certain measures are recited only in mutually different dependent claims does not mean that combinations of these measures cannot be used advantageously.

[0081] Procedures performed by one or more units or devices, such as receiving absorption characteristics, determining hygiene characteristics, and generating control data, can be performed by any other number of units or devices. These processes can be implemented as program code components of a computer program and / or dedicated hardware.

[0082] Computer program products may be stored / distributed 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, such as via the Internet or other wired or wireless telecommunications systems.

[0083] Any unit described herein may be a processing unit as part of a classical computing system. Processing units may include general-purpose processors and may also include field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), or any other special-purpose circuitry. Any memory may be physical system memory, which may be volatile, non-volatile, or some 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 and / or memory capabilities may also be distributed. The computing system may include multiple structures as "executable components." The term "executable component" is a structure well understood in the computing field as a structure that may be software, hardware, or a combination thereof. For example, when implemented in software, those 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 executable components in the heap of the computing system or on a 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 the computing system (e.g., by processor threads), it causes the computing system to perform functions. Such a structure can be directly computer-readable by the processor, for example, as in the case where the executable is binary, or it can be structured to be interpretable and / or compilable, whether in a single stage or in multiple stages, to generate such binary that can be directly interpreted by the processor. In other instances, the structure can be hard-coded or hard-wired logic gates that are exclusively or nearly exclusively implemented in hardware, such as in a field-programmable gate array (FPGA), application-specific integrated circuit (ASIC), or any other dedicated circuit. Thus, the term "executable" is a term well understood by those skilled in the art of computing for a structure, whether implemented in software, hardware, or a combination thereof. Any embodiment described herein is described with reference to actions performed by one or more processing units of a computing system. If such actions are implemented in software, one or more processors direct the operation of the computing system in response to having executed computer-executable instructions constituting the executable. The computing system may also include communication channels that allow the computing system to communicate with other computing systems via, for example, a network. A "network" is defined as one or more data links that enable the transfer of electronic data between computing systems and / or modules and / or other electronic devices. When information is transmitted or provided to a computing system via a network or another communication connection (e.g., hardwired, wireless, or a combination of hardwired and wireless), the computing system appropriately treats the connection as a transmission medium. The transmission medium may include a network and / or a data link that can be used to carry desired program code components in the form of computer-executable instructions or data structures, and that the network and / or data link may be accessed by a general-purpose or special-purpose computing system or combination thereof.While not all computing systems require a user interface, in some implementations, the computing system includes a user interface system for interaction with the user. The user interface, for example, acts as an input or output mechanism for the user via a display.

[0084] Those skilled in the art will understand that at least parts of the present invention can be practiced in networked computing environments with many types of computing system configurations, including personal computers, desktop computers, laptop computers, message processors, handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile phones, PDAs, pagers, routers, switches, data centers, wearable devices (such as glasses), etc. The invention can also be practiced in distributed system environments, where local and remote computing systems linked, for example, via hardwired data links, wireless data links, or a combination of hardwired and wireless data links, perform tasks over a network. In a distributed system environment, program modules can reside in both local and remote memory storage devices.

[0085] Those skilled in the art will also understand that at least parts of the present invention can be practiced in a cloud computing environment. A cloud computing environment can be distributed, although this is not required. When distributed, a cloud computing environment can be internationally distributed within an organization and / or have components owned across multiple organizations. In this specification and the following claims, “cloud computing” is defined as a model for enabling on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage devices, applications, and services). The definition of “cloud computing” is not limited to any of the many other advantages that can be obtained from such a model at the time of deployment. The computing system of the figures includes various components or functional blocks that can implement the various embodiments disclosed herein as explained. The various components or functional blocks can be implemented on a local computing system or on a distributed computing system that includes elements residing in the cloud or aspects of implementing cloud computing. The various components or functional blocks can be implemented as software, hardware, or a combination of software and hardware. The computing system shown in the figures may include more or fewer components than those shown in the figures, and some of the components may be combined where environmental guarantees are in place.

[0086] Any reference numerals in the claims should not be construed as limiting the scope.

Claims

1. An apparatus for determining the hygienic properties of a hygiene product, wherein the hygiene product comprises a layer of superabsorbent material provided in the form of superabsorbent particles, wherein the apparatus (110) includes one or more processors configured to The device receives a) one or more absorption properties of a superabsorbent material, and b) a quantitative model of the hygiene product, the quantitative model including a predetermined amount of liquid at the superabsorbent material layer of the hygiene product over time. A hygiene product characteristic determination model is used to determine the hygiene characteristics of the hygiene product based on the absorption characteristics and the quantitative model, and Generate control data for controlling the production process of the hygiene product and / or the superabsorbent material based on the determined hygiene characteristics of the hygiene product.

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

3. The device of claim 2, wherein determining the 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 device according to any one of the preceding claims, wherein the hygienic characteristic indicates the amount of free liquid in the hygienic product.

5. The device according to any one of the preceding claims, wherein the one or more absorption properties of the superabsorbent material indicate at least one of permeability, absorption capacity, and absorption rate.

6. The device according to any one of the preceding claims, wherein the hygiene product characteristic determination model comprises solving the following differential equations in Describe the free liquid in the hygiene product over time. Describe the fluid absorption of the superabsorbent material over time based on the absorption characteristics stated therein, and Describes the amount of fluid entering the hygiene product over time.

7. The device according to any one of the preceding claims, wherein it further receives an indication of the amount of superabsorbent material in the hygiene product layer, and wherein the one or more absorption properties of the superabsorbent material are adjusted based on the amount of superabsorbent material in the hygiene product.

8. The device according to any one of the preceding claims, wherein the device further comprises one or more processors configured to determine one or more absorption properties of the superabsorbent material based on the particle size distribution of the received superabsorbent material using an absorption property determination model, wherein the property determination model is a data-driven model, the data-driven model being parameterized such that it is adapted to determine the technical application properties of the superabsorbent particles based on the particle size, wherein the determined one or more absorption properties are then used in the hygiene property determination model.

9. The device of claim 8, wherein the superabsorbing particles of the superabsorbing material comprise a superabsorbing polymer provided in the form of: i) an interconnecting core and ii) a surface-crosslinked shell having higher connectivity than the core, and wherein the provided absorption characteristic determination model is further parameterized based on the core size and shell size of the superabsorbing particles.

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

11. A system for controlling the production of hygiene products and / or superabsorbent materials, wherein the hygiene products include a layer of superabsorbent material provided in the form of superabsorbent particles, wherein the system (100) comprises: An interface unit (120) is configured to receive a) one or more production parameters for producing the hygiene product and b) target hygiene characteristics of the hygiene product, and is configured to determine one or more absorption characteristics of the superabsorbent material and / or a quantitative model of the hygiene product based on the received one or more production parameters. The device (110) according to any one of the preceding claims, wherein the device is configured to receive the absorption characteristics and / or quantitative model of the superabsorbent material from the interface unit, and is configured to determine the hygiene characteristics and further configured to compare the determined hygiene characteristics with the target characteristics, and if the determined hygiene characteristics are outside a predetermined range around the target hygiene characteristics, generate a control signal for correcting one or more of the one or more production parameters for producing the hygiene product and / or the superabsorbent material.

12. A computer-implemented method for determining the hygienic properties of a hygiene product, wherein the hygiene product comprises a layer of superabsorbent material provided in the form of superabsorbent particles, wherein the method comprises the following steps: The device receives a) one or more absorption properties of a superabsorbent material, and b) a quantitative model of the hygiene product, the quantitative model including a predetermined amount of liquid at the superabsorbent material layer of the hygiene product over time. A hygiene product characteristic determination model is used to determine the hygiene characteristics of the hygiene product based on the absorption characteristics and the quantitative model, and Generate control data for controlling the production process of the hygiene product and / or the superabsorbent material based on the determined hygiene characteristics of the hygiene product.

13. A computer-implemented method for controlling the production of hygiene products and / or superabsorbent materials, wherein the hygiene product comprises a layer of superabsorbent material provided in the form of superabsorbent particles, wherein the method comprises: Receive a) one or more production parameters for producing the hygiene product and b) the target hygiene characteristics of the hygiene product. One or more absorption properties of the superabsorbent material and / or a quantitative model of the hygiene product are determined based on one or more production parameters received. The method according to claim 12 is performed based on the absorption characteristics and / or quantitative model of the received superabsorbent material to determine the hygienic properties, and The determined hygiene characteristic is compared with the target characteristic, and if the determined hygiene characteristic is outside a predetermined range around the target hygiene characteristic, a control signal is generated to correct one or more of the production parameters used to produce the hygiene product and / or the superabsorbent material.

14. A computer program product for determining the hygienic properties of a hygienic product, wherein the computer program product includes program code components for causing a device according to any one of claims 1 to 10 to perform the method according to claim 12.

15. A computer program product for controlling the production of hygiene products and / or superabsorbent materials, wherein the computer program product includes program code components for causing the device of claim 11 to perform the method of claim 13.

Images