EP4728451A1

EP4728451A1 - Digital twins of chemical products

Info

Publication number: EP4728451A1
Application number: EP24731599.7A
Authority: EP
Inventors: Stefania LANFRANCHINI; Michael Prinz; Thomas Kiciak; Oliver Geiger; Andreas Wollny; Gabriele ECKARDT; Ionel RUSU; Michael-georg SCHMIDT; Nicole Graf; Lukas NIEMEIER; Henning SCHWABE
Original assignee: BASF SE
Current assignee: BASF SE
Priority date: 2023-06-19
Filing date: 2024-06-10
Publication date: 2026-04-22
Also published as: WO2024260756A1; CN121368770A

Abstract

A method for producing a chemical product with a target property, the method comprising: - receiving a request for producing the chemical product with the target property, wherein the request com- prises the target property data, - producing the chemical product associated with the target property data, - gathering chemical product data comprising the target property data based on the chemical product, - receiving a request to provide a decentral identifier associated with the chemical product data set and op- tionally a data owner, - receiving a data model associated with the target property data, - generating a chemical product data set comprising the target property data according to the data model based on the chemical product data, - generating the digital twin of the chemical product including the decentral identifier and the chemical product data set, - providing the chemical product associated with the target property data and/or providing the decentral identi- fier and/or providing the chemical product data set.

Description

DIGITAL TWI NS OF CHEMICAL PRODUCTS

TECHNICAL FIELD

The invention relates to a computer-implemented method for generating a digital twin of a chemical product with a target property, a method for producing a chemical product with a target property, a system for generating a digital twin of a chemical product with a target property, a system for providing a chemical product associated with a digital twin, use of a digital twin, a digital twin, a computer element, a computer-implemented method for using a digital twin

TECHNICAL BACKGROUND

In the supply of chemical products multiple regulatory requirements need to be met, which differ depending on the chemical product. Currently used systems are static regarding data, prone to error and cumbersome in handling or maintenance. Owing to the highly specific and centralized setup of such systems, exchange and sharing of chemicals data is laborious. Hence, there is a need to simplify chemical data exchange and sharing.

SUMMARY

In an aspect, the disclosure relates to a computer-implemented method for generating a digital twin of a chemical product with a target property, the method comprising: gathering chemical product data comprising target property data associated with the chemical product, receiving a request to provide a decentral identifier associated with the chemical product data set and optionally a data owner, receiving a data model associated with the target property data, generating a chemical product data set comprising target property data according to the data model based on the chemical product data, in response to the request, generating the digital twin of the chemical product including the decentral identifier and the chemical product data set, and optionally providing the decentral identifier and/or the chemical product data set.

In another aspect, it relates to a, in particular computer-implemented, method for generating a digital twin of a chemical product having one or more target properties, the method comprising: gathering chemical product data associated with the chemical product, wherein the chemical product data includes target property data associated with the target property, providing a decentral identifier associated with the chemical product data and optionally a data owner, receiving one or more data model(s) associated with the one or more target properties of the chemical product, generating at least one chemical product data set comprising target property data according to the one or more data model(s) based on the chemical product data, in response to the request, generating the digital twin of the chemical product including the decentral identifier and the chemical product data set, and optionally providing the decentral identifier and/or the chemical product data set.

In another aspect, it relates to a method for producing a chemical product having one or more target properties, the method comprising: receiving a request for producing the chemical product with the target property, wherein the request comprises target property data, producing the chemical product based at least in part on the received target property data, gathering chemical product data associated with the produced chemical product, wherein the chemical product data includes target property data associated with the one or more target properties, providing a decentral identifier associated with the chemical product data set and optionally a data owner, receiving at least one data model associated with the target property data, generating a chemical product data set comprising the target property data according to the at least one data model based on the chemical product data, generating the digital twin of the chemical product including the decentral identifier and the chemical product data set, providing the chemical product associated with the target property data and/or providing the decentral identifier and/or providing the chemical product data set.

In an aspect, it relates to a method for producing a chemical product with a target property, the method comprising: receiving a request for producing the chemical product with the target property, wherein the request comprises target property data, producing the chemical product associated with the target property data, gathering chemical product data comprising the target property data based on the chemical product, receiving a request to provide a decentral identifier associated with the chemical product data set and optionally a data owner, receiving a data model associated with the target property data, generating a chemical product data set comprising the target property data according to the data model based on the chemical product data, generating the digital twin of the chemical product including the decentral identifier and the chemical product data set, providing the chemical product associated with the target property data and/or providing the decentral identifier and/or providing the chemical product data set. In an aspect, it relates to a computer-implemented method for using a digital twin of a chemical product, preferably to process the chemical product associated with the digital twin, the method comprising: receiving a request to access one or more chemical product data set(s) associated with a decentral identifier of the digital twin as generated according to the methods as described herein or by the apparatus as described herein or by the system as described herein;

- optionally authenticating and/or authorizing the request to access the one or more chemical product data set(s); based on optionally the authentication and/or authorization, providing access to the one or more chemical product data set(s) associated with the decentral identifier of the digital twin.

In an aspect, it relates to a system for generating a digital twin of a chemical product with a target property, the system comprising: one or more computing node(s); and one or more computer-readable media having thereon computer-executable instructions which, when executed by the one or more computing nodes, configure the apparatus to perform any one of the methods according to one of the methods disclosed herein.

In an aspect, it relates to a system for providing a chemical product associated with a digital twin, the system comprising: a production line configured to produce the chemical product connected to or comprising a physical identifier; a digital twin generator configured to generate the digital twin according to the methods as disclosed herein or by the system as disclosed herein, and an assigning device configured to assign the physical identifier to a decentral identifier included in the digital twin of the chemical product.

In yet another aspect the present disclosure relates to a use of a digital twin of a chemical product as generated according to the methods and/or systems as disclosed herein to process the product associated with the digital twin.

In yet another aspect the present disclosure relates to a digital twin of a chemical product as generated according to the methods and/or systems as disclosed herein.

In yet another aspect the present disclosure relates to a computer element with instructions, which when executed on one or more computing node(s) is configured to carry out the steps of the method(s) of the present disclosure or configured to be carried out by the apparatus(es) of the present disclosure.

Material properties of chemical products may not be directly or indirectly derived from the physical entity of the chemical product even though the information may be critical to determine processing of the respective chemical product. Thus, it is of high importance to collect data related to material properties reliably. Fraud in relation to this data, e.g. by tempering the respective data, should be excluded. In parallel, the producer of the chemical products should retain the control of sensitive property and production data in association with a chemical product. Hence, methods and systems for a reliable, robust and sovereign exchange of production and property data is desired.

In this disclosure, system and methods for an efficient, secure and self-controlled exchange of data are presented. The systems and methods as presented herein enable a trustworthy data providing while maintaining the data sovereignty of the data owner. The properties of chemical products at least partially inaccessible by analytical means can be collected by gathering chemical product data comprising target property data. The target property data may be requested and/or desired for processing the chemical product. Followingly, extracting the target property data from the gathered data and allowing a participant of the supply chain to access the target property data in relation to the chemical product via a decentral identifier enables reliable and trustworthy sharing of target property data with eg a downstream participant. Ultimately, this all contributes to enabling increasingly sustainable chemical supply chains by efficient processing of chemical products.

EMBODIMENTS

In the following, terminology as used herein and/or the technical field of the present disclosure will be outlined by ways of definitions and/or examples. Where examples are given, it is to be understood that the present disclosure is not limited to said examples.

In an embodiment, the chemical product may be a chemical product obtained from at least one chemical reaction, in particular by one or more input material(s) and/or educt(s). The chemical product may include natural chemical products. Natural chemical products may include any chemical product that is produced by nature without human interaction or intervention, i.e. any unprocessed chemical substance that is found in nature, such as chemicals from plants, micro-organisms, animals, the earth and the sea or any chemical substance that is found in nature and extracted using a process that does not change its chemical composition. Natural chemical products may include biologicals like enzymes as well naturally occurring inorganic or organic chemical products. Natural chemical products may be isolated and purified prior to their use or they can be used in unisolated and/or unpurified form. Chemical products may be synthetic chemical products. Synthetic chemical products may include chemical products produced with human interaction or intervention. Synthetic chemical products may be produced with the same chemical reactions occurring in nature or with different chemical reactions.

Chemical products may be any inorganic or organic chemical product obtained by reacting inorganic and/or organic chemical reactants. The inorganic and organic chemical reactants may be natural chemical products or may be synthetic chemical products. Chemical reactions may include any chemical reaction commonly known in the state of the art in which the reactants are converted to one or more different chemical products. Chemical reactions may involve the use of catalysts, enzymes, bacteria, etc. to achieve the chemical reaction between the reactants.

The chemical product may include a raw material. The chemical product may include a chemical material produced by reacting at least two raw materials. The chemical product may include a component. The chemical product may include a component assembly. The chemical product may include an end product.

In an embodiment, computer may be a device comprising a processing unit, in particular a processor.

In an embodiment, the digital twin of the chemical product may be a digital representation of a physical entity of the chemical product. The digital representation of the physical entity may comprise a defined semantic description of said physical entity of the chemical product. The digital twin of the chemical product is hence a digital version of the physical entity of the chemical product. The digital twin may be a digital representation of the chemical product in a real-world system. The digital twin may reflect the form and behavior of the chemical product associated with the digital twin. Additionally or alternatively, the digital twin may mirror the properties of the chemical product during its lifetime. For example, sensors may capture real-time (or near real-time) data, such as transport data, from the chemical product to relay it back to a remote digital twin. The digital twin may be updated to maintain its correspondence to the physical entity of the chemical product. The digital twin may be updated based on data gathered independently from the chemical product data and/or the chemical product data set(s) used for generating the digital twin, in particular chemical product data and/or the chemical product data set(s) comprising sensor data. Sensor data may be data gathered by a sensor. For example, a sensor may be hard sensor and/or a soft sensor. The digital twin may contain one or more chemical product data sets. At least one chemical product data set may contain at least one measured physical and/or chemical property of the chemical product and/or at least one physical and/or chemical property determined from collected data associated with the production and/or the use of the chemical product. Each chemical product data set may contain defined chemical product data. Each chemical product data set may be associated with the decentral digital twin identifier. Each chemical product data set may further be associated with a chemical product data set identifier. This allows to uniquely identify each chemical product data set comprised in the digital twin by using the chemical product data set identifier associated with said chemical product data set. The digital twin may comprise the decentral identifier, being in particular a decentral digital twin identifier, the chemical product data set(s) and chemical product data set identifier(s) associated with the chemical product data set(s). The digital twin may further contain a chemical product identifier.

In an embodiment, target property data may indicate and/or comprise one or more target properties of the chemical product. The one or more target properties may determine a processing of the chemical product. The one or more target properties may determine an application with respect to the chemical product having the one or more target properties. The one or more target properties, in particular the target property data, may be specified by the consumer of the chemical product. In an embodiment, target property may comprise at least one of chemical product name, qualitative chemical product composition, quantitative chemical product composition, chemical product processing instruction, qualitative chemical educt composition, quantitative chemical product educt composition, educt processing instruction, product processing instruction, educt material property, product material property, environmental attribute(s) of the chemical product, environmental attribute(s) of the educt, chemical product declaration data, chemical product safety data or a combination thereof. The input material(s), in particular for producing the chemical product, may be one or more educt(s). The chemical product may be obtained from the one or more input material(s). The educt material property may be a material property of the educt, i.e. input material associated with the chemical product. The product material property may be a material property of the product, in particular the chemical product. Educt processing instruction may refer to processing instructions used for processing the educt. Followingly, educt processing instructions may be used for producing the chemical product based on the educt. Product processing instruction may refer to processing instructions used for processing the product. Followingly, product processing instructions may be used for producing a product from the chemical product.

In an embodiment, environmental attribute may comprise at least one of emission data of the chemical product, recy- clate content data of the chemical product, bio-based content data of the chemical product, renewable content data of the chemical product, chemical product production data, or a combination thereof.

In an embodiment, emission data may comprise any data related to environmental footprint. The environmental footprint may refer to an entity and its associated environmental footprint. The environmental footprint may be entity specific. For instance, the environmental footprint may relate to a product, a company, a process such as a manufacturing process, a raw material or basic substance, a chemical product or material, a component, a component assembly, an end product, combinations thereof or additional entity-specific relations. Emission data may include data relating to carbon footprint of a chemical product. Emission data may include data relating to greenhouse gas emissions e.g. released in production of the chemical product. Emission data may include data related to greenhouse gas emissions. Greenhouse gas emissions may include emissions such as carbon dioxide (CO2) emission, methane (CH4) emission, nitrous oxide (N2O) emission, hydrofluorocarbons (HFCs) emission, perfluorocarbons (PFCs) emission, sulphurhexafluoride (SFe) emission, nitrogen trifluoride (NF3) emission, combinations thereof and additional emissions.

Emission data may include data related to greenhouse gas emissions of an entities or companies own operations (production, power plants and waste incineration). Scope 2 comprise emissions from energy production which is sourced externally. Scope 3 comprise all other emissions along the value chain. Specifically, this includes the greenhouse gas emissions of raw materials obtained from suppliers. Product Carbon Footprint (PCF) sum up greenhouse gas emissions and removals from the consecutive and interlinked process steps related to a particular product. Cradle-to-gate PCF sum up greenhouse gas emissions based on selected process steps: from the extraction of resources up to the factory gate where the product leaves the company. Such PCFs are called partial PCFs. In order to achieve such summation, each company providing any products must be able to provide the scope 1 and scope 2 contributions to the PCF for each of its products as accurately as possible, and obtain reliable and consistent data for the PCFs of purchased energy (scope 2) and their raw materials (scope 3).

In an embodiment, recyclate content data, bio-based content data and renewable content data may comprise any data related to the recyclate content or the bio-based content or the renewable content used for producing or manufacturing a physical entity of the chemical product.

In an embodiment, chemical product data may be associated with the chemical product. Chemical product data may indicate at least one property associated with the chemical product. In particular, chemical product data may be related to the at least one property. Preferably, the chemical product data may comprise the at least one property. Property associated with the chemical product may comprise at least one of chemical product name, qualitative chemical product composition, quantitative chemical product composition, chemical product processing instruction, qualitative chemical educt composition, quantitative chemical product educt composition, educt product processing instruction, chemical educt production data, material property associated with the chemical product, environmental attribute associated with the chemical product, chemical product production data, chemical product declaration data, chemical product safety data or a combination thereof. The at least one property may comprise and/or may be a target property. Chemical product data may comprise data related to a property of the chemical product and/or data related to the use of the chemical product and/or data related to the production of the chemical product. Such property may be a static or a dynamic property. A static property may be a property constant over time e.g. melting point, boiling point, density, hardness, flammability or the like. A dynamic property may be a property that changes over time e.g. shelf life, pH value, color, reactivity. Property of the chemical product may include performance properties, chemical properties, such as flammability, toxicity, acidity, reactivity, heat of combustion and/or physical properties such as density, color, hardness, melting and boiling points, electrical conductivity or the like.

Data related to the use of the chemical product may include data related to further processing of the chemical product, for example by using the chemical product as reactant in further chemical reaction(s) and/or data related to the use of the chemical product, for example data related to the use of the chemical product in a treatment process and/or within a manufacturing process.

Data related to the production of the chemical product may comprise any data related to the production of the chemical product at any stage in the chemical supply chain. Said data may include chemical production data from the production of the chemical product. Production data may include monitoring and/or control data associated with the production of the chemical product. Production data may include measurement data related to a product quality at any stage in the chemical supply chain, preferably a chemical product.

In an embodiment, the chemical product data set includes at least one chemical product identifier. The chemical product identifier(s) included in the chemical product data set may correspond to the chemical product identifier(s) included in the received request and/or may correspond to the chemical product identifier(s) included in the chemical product data. Use of at least one chemical product identifier within the chemical product data set allows to correlate said data set with the physical entity of the chemical product the chemical product identifier(s) are associated with.

In an embodiment, chemical product data set may correspond to a data structure obtained upon applying the respective data model to the chemical product data. The chemical product data set may include values and/or value ranges defined in the data model used to generate the chemical product data set. Hence, each chemical product data set contains the data structure and data defined by the data model used for its generation. This ensures that each chemical product data set has a defined structure and contains defined data, thus allowing to simplify data exchange and processing of the exchanged data on chemical products. The chemical data set may be suitable for representing chemical product data. Chemical product data set may represent at least a part of the chemical product data, in particular the target property data. Chemical product data set may comprise a subset of chemical product data, in particular comprising the target property data. Hence, the target property data may be extracted from the chemical product data by the at least one data model. Chemical product data set may refer to a selection of data points within the chemical product data. Chemical product data set may be generated according to a data model based on the chemical product data.

In an embodiment, physical entity may relate to the physical embodiment of the chemical product. The physical entity may be any chemical product in the chemical supply chain. The physical entity of the chemical product may be a raw material or basic substance, a chemical product, a chemical material, a chemical formulation, a chemical mixture, a component, a component assembly, an input product, an output product, an end product or a combination thereof.

In an embodiment, the data model may comprise a semantic description of the respective chemical product data set associated with the digital twin. The semantic description may include the structure of at least a portion of the chemical product data set, and/or properties of the chemical product data set. The properties of the chemical product data set may include data types. The properties of the chemical product data set may include possible or allowable values and/or value ranges. The properties of the chemical product data set may be a physical unit of at least one parameter described by values being comprised in the chemical product data set. The data model may be suitable for extracting a chemical product data set comprising the target property data from the chemical product data comprising the target property data. In particular, the data model may be suitable for extracting a subset of chemical product data into a chemical product data set. The data model may be an aspect model.

Chemical product data set(s) may be associated with the target property data. Chemical product data set(s) associated with the target property data may refer to chemical product data set(s) comprising the target property data at least in parts. In an embodiment, the decentral identifier may comprise any unique identifier uniquely associated with the chemical product data set(s) and optionally the data owner. The decentral identifier may include one or more Universally Unique I Dentifier (UUID) or one or more Digital IDentifier (DID). The decentral identifier may be issued by a central or decentral identity issuer. The decentral identifier may be generated by the data owner or on behalf of the data owner. The decentral identifier may include authentication information. Via the decentral identifier and its unique association with the chemical product data(s) and optionally the data owner, access to the chemical product data set(s) may be controlled by the data owner. This contrasts with central authority schemes, where identifiers are provided by such central authority and access to data is controlled by such central authority. Decentral in this context refers to the usage of the identifier in implementations as controlled by the data owner. The decentral identifier may include or be associated with one or more identifier(s) used in the decentral network and allowing for data exchange via the decentral network. For instance, the decentral identifier may include or be associated with chemical product data set identifier(s) of chemical product data sets, such as UUID(s) of chemical product data set(s). Any combination of UUID(s) and DID(s) may be possible. For instance, the decentral identifier may be a DID while the chemical product data identifier(s) may be UUID(s). In another instance, the decentral identifier, and the chemical product data identifier(s) may be UUlDs. Data exchange may include discovery of the decentral identifier and optionally identifier(s) associated with said decentral identifier for participant nodes of the decentral network, authentication of participant nodes of the decentral network and/or authorization of data transfers via a peer-to-peer communication between participant nodes of the decentral network.

In an embodiment, authentication information may be and/or may comprise a public key and/or a decentral participant identifier. The public key may be used by third-party entities to access information. Additionally or alternatively, the authentication information may comprise a certificate. Preferably, the certificate may be a valid certificate. Certificate may specify the entity associated with the request, for example the data consumer. Further, the certificate may be limited to a predetermined time interval. In an embodiment, the decentral participant identifier may comprise any identifier uniquely associated with a participant of a decentral network and/or with a production site of a participant of the decentral network. The participant of the decentral network may be a consumer of the chemical product such as a downstream participant, e.g. may consume the chemical product received from or supplied by the chemical product producer. The production site of a participant of the decentral network may use the received/supplied chemical product to produce further products, such as further chemical products, parts, components, component assemblies and/or end products. The decentral participant identifier may include letters and/or numbers. The decentral participant identifier may include one or more Universally Unique Identifier(s) (UUID(s)) and/or one or more Decentralized Identifier(s) (DID(s)). The decentral participant identifier may be associated with or may include a verifiable claim or credential.

The third-party entities may be given permission by the owner of the chemical product data set the third-party entity desires to access. The third-party entity may desire to access the digital twin and/or information in relation to the digital twin. Information in relation to the digital twin may comprise information to be derived from the digital twin by mathematical operations and/or meta data linked to the digital twin. Meta data may be data related to the chemical product data set. For example, chemical product data set may be linked to the digital twin.

In an embodiment, the chemical product data set may be associated with a digital representation of the chemical product data set, ie the chemical product data set may be linked to the digital twin of the chemical product via the decentral identifier. The digital representation may include a representation for accessing the chemical product data set, such as a locator to the chemical product data set. The digital representation may include a representation of chemical product data set. The digital twin may include data related to the chemical product data set, a public key and the decentral identifier. The data related to the chemical product data set may include the digital representation of the chemical product data set.

In an embodiment, the data owner may comprise any entity generating data. In particular, the data owner may comprise an entity generating the chemical product data, data owner of the digital twin and/or of at least parts of the chemical product data sets) and/or gathering the chemical product data. The data generating node may be coupled to the entity owning the physical entity of the chemical products from or for which data is generated. The data may be generated by a third-party entity on behalf of the entity owning the physical entity of the chemical products from or for which data is generated. The generated data may be stored on one or more dedicated data storage(s) owned or controlled by the data owner. Said dedicated data storage(s) may be accessed by a data consuming service using the data contained in the chemical product data set, such as the decentral identifier and the data related to the digital twin.

In an embodiment processor may refer to an arbitrary logic circuitry configured to perform basic operations of a computer or system, and/or, generally, to a device which is configured for performing calculations or logic operations. In particular, the processor, or computer processor may be configured for processing basic instructions that drive the computer or system. It may be a semi-conductor-based processor, a quantum processor, or any other type of processor configures for processing instructions. As an example, the processor may be or may comprise a Central Processing Unit ("CPU"). The processor may be a ("GPU”) graphics processing unit, (“TPU”) tensor processing unit, ("CISC") Complex Instruction Set Computing microprocessor, Reduced Instruction Set Computing ("RISC") microprocessor, Very Long Instruction Word ("VLIW") microprocessor, or a processor implementing other instruction sets or processors implementing a combination of instruction sets. The processing means may also be one or more specialpurpose processing devices such as an Application-Specific Integrated Circuit ("ASIC"), a Field Programmable Gate Array ("FPGA"), a Complex Programmable Logic Device ("CPLD"), a Digital Signal Processor ("DSP"), a network processor, or the like. The methods, systems and devices described herein may be implemented as software in a DSP, in a micro-controller, or in any other side-processor or as hardware circuit within an ASIC, CPLD, or FPGA. It is to be understood that the term processor may also refer to one or more processing devices, such as a distributed system of processing devices located across multiple computer systems (e.g., cloud computing), and is not limited to a single device unless otherwise specified. In an embodiment memory may refer to a physical system memory, which may be volatile, non-volatile, or a combination thereof. The memory may include non-volatile mass storage such as physical storage media. The memory may be a computer-readable storage media such as RAM, ROM, EEPROM, CD-ROM, or other optical disk storage, magnetic disk storage, or other magnetic storage devices, non-magnetic disk storage such as solid-state disk or any other physical and tangible storage medium which can be used to store desired program code means in the form of computer-executable instructions or data structures and which can be accessed by the computing system. Moreover, the memory may be a computer-readable media that carries computer- executable instructions (also called transmission media). Further, upon reaching various computing system components, program code means in the form of computer-executable instructions or data structures can be transferred automatically from transmission media to storage media (or vice versa). For example, computer-executable instructions or data structures received over a network or data link can be buffered in RAM within a network interface module (e.g., a "NIC”), and then eventually transferred to computing system RAM and/or to less volatile storage media at a computing system. Thus, it should be understood that storage media can be included in computing components that also (or even primarily) utilize transmission media.

In an embodiment, a computing node may refer to any device or system that includes at least one physical and tangible processor, and a physical and tangible memory capable of having thereon computer-executable instructions that are executed by a processor. Computing nodes may, for example, be handheld devices, production facilities, sensors, monitoring systems, control systems, appliances, laptop computers, desktop computers, mainframes, data centers, or even devices that have not conventionally been considered a computing node, such as wearables (e.g., glasses, watches or the like). The memory may take any form and depends on the nature and form of the computing node.

In an embodiment distributed computing may be implemented. Distributed computing may refer to any computing that utilizes multiple computing resources. Such use may be realized through virtualization of physical computing resources. One example of distributed computing is cloud computing. "Cloud computing” may refer a model for enabling on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services). When distributed, cloud computing environments may be distributed internationally within an organization and/or across multiple organizations. In an embodiment, distributed computed may be realized in a federated network.

These and other objects, which become apparent upon reading the following description, are solved by the subject matters of the independent claims. The dependent claims refer to embodiments of the invention.

In an embodiment, the digital twin is updated based on sensor data and/or data gathered after the generation of the digital twin. Updating the digital twin based on sensor data and/or data gathered after the generation of the digital twin may refer to updating at least a part of values associated with the chemical product data set(s) by sensor data and/or data gathered after the gathering the chemical product data associated with the chemical product and/or adding sensor data and/or data gathered after the gathering the chemical product data associated with the chemical product. Additionally or alternatively, updating the digital twin based on sensor data and/or data gathered after the generation of the digital twin may refer to adding one or more numerical value(s) associated with the sensor data and/or data gathered after the generation of the digital twin to the chemical product data set(s) and/or adding one or more generated chemical product data set(s) associated with sensor data and/or data gathered after the generation of the digital twin to the available chemical product data set(s). Sensor data may be data gathered by a sensor. For example, a sensor may be hard sensor and/or a soft sensor. Sensor data may comprise at least one of spectroscopic data and/or spectrometric data. Data gathered after the gathering the chemical product data may comprise at least one of sensor data, modelling data and/or synthetic data. By updating the digital twin current changes like a change in size, shape or a change of storage conditions and/or properties of a product can be observed. Such changes can influence a product itself, its processing and/or its behavior. Updating the digital twin enables the tracking of a product over its lifetime. Depending on the intended lifetime of a product updating the digital twin can reduce the number of digital twins associated with one product. Thus, it helps to reduce computational resources and energy used for generating and maintaining additional twins.

In an embodiment, the chemical product is produced based on a continuous and/or batch process, and/or the chemical product may include at least one of alkyl group, alkenyl group, alkynyl group, phenyl group, carbonyl group, ketone group, aldehyde group, hydroxyl group, haloformyl group, ester group, carboxylate group, halo group, carboxyl group, peroxy group, carboalkoxy group, hydroperoxyl group, ether group, acetal group, hemiacetcal group, hemiketal group, ketal group, carboxylic anhydride group, carboxamide group, amidine group, amine group, ketamine group, aldimine group, imide group, cyante group, azo group, nitrite group, nitrate group nitro group, nitrile group, sulfide group, thiol group, sulfinyl group, sulfonyl group, sulfo group, thiocyanate group, thionoester group, thiolester group, phosphino group, phosphono group, phosphate group or any combination thereof.

In an embodiment, chemical product data and/or chemical product data set may indicate and/or may comprise at least one of chemical product name data, qualitative chemical product composition data, quantitative chemical product composition data, chemical product processing data, qualitative chemical educt composition, quantitative chemical product educt composition, educt product processing instruction, chemical educt production data, material property data, environmental attribute data, chemical product production data, chemical product declaration data, chemical product safety data or a combination thereof.

In an embodiment, providing the decentral identifier comprises assigning a physical identifier associated with the chemical product to the decentral identifier and/or providing a chemical product associated with the decentral identifier. By doing so, the digital twin including the decentral identifier is linked to a physical entity. This enables directly linking the physical product with its digital twin to access for example production or ingredient information. Such a physical identifier may be readily used to retrieve the information by a non-expert user. Additionally or alternatively, providing the decentral identifier may include reading a physical identifier element physically associated with the chemical product, for example using a device configured to scan the physical identifier element. Additionally or alternatively, providing the decentral identifier may include accessing, for example with an operating system, a database containing decentral identifiers. Further, the decentral identifier associated with the chemical product may be fetched.

In an embodiment, gathering chemical product data associated with the chemical product with the target property comprises selecting the chemical product data comprising the target property and/or generating the chemical product data comprising the target property. Chemical product data may be generated by measurement and/or simulation. Selecting the chemical product data comprising the target property may comprise retrieving the chemical product data from a data storage unit, e.g. a database. In particular, selecting the chemical product data may comprise retrieving the chemical product data from a data storage unit, wherein the data storage unit may comprise the chemical product data associated with the target property. Followingly, chemical product data comprising the target property may be selected based on the target property provided by the downstream participant.

In an embodiment, gathering chemical product data is associated with an authentication and/or authorization. Authentication and/or authorization may be required before retrieving the chemical product data. Gathering chemical product data may include providing a request for gathering the chemical product data and receiving the chemical product data. The request for gathering the chemical product data may include authentication information and/or authorization information. Authentication information may be suitable for authenticating the request for gathering chemical product data.

In an embodiment, accessing the digital twin and/or one or more of the chemical product data set(s) associated with the digital twin is preceded by authentication. Thus, a request for accessing the digital twin and/or one or more of the chemical product data set(s) associated with the digital twin may comprise authentication information.

In an embodiment, a request for authenticating and/or authorizing prior to gathering chemical product data and/or prior to providing the decentral identifier and/or prior to providing the at least one chemical product data set is provided. Based on the providing of the request for authenticating and/or authorizing the chemical product data may be received. The request for authenticating and/or authorizing may comprise authentication information and/or authorization information. The request may be authenticated and/or authorized based on authentication information and/or authorization information.

Access to chemical product data may be restricted to a limited number of participants. Authenticating a data request may enable the conscious sharing of data. In particular, this is advantageous in a decentral system allowing the data ownership to reside with the data generator and enabling the data owner to securely share data only with selected recipients.

In an embodiment, the request for producing the chemical product may be related to and/or may comprise a request to provide a decentral identifier associated with the chemical product data set and optionally a data owner. Providing and/or receiving the request for producing the chemical product may trigger providing the request to provide the decentral identifier. The chemical product may be associated with the target property data and/or may comprise the target property. The request for producing the chemical product in relation to the request to provide a decentral identifier may refer to the request for producing the chemical product comprising the request to provide the decentral identifier and/or the receiving of the request for producing the chemical product may trigger generating the request to provide the decentral identifier and/or the request for providing the chemical product may require receiving the request to provide the decentral identifier. Additionally or alternatively, a request to provide a decentral identifier associated with the chemical product data set and optionally a data owner may be received prior to generating the digital twin and/or the generating the digital twin may be in response to receiving the request to provide a decentral identifier associated with the chemical product data set and optionally a data owner. The beforementioned embodiments in relation to the request for producing the chemical product may show different implementations of the relation between the chemical product being a physical entity and the digital twin being a digital entity representing the chemical product. Digital representation of a product enables an efficient processing of resources.

In an embodiment, at least a part of the chemical product data is associated with measurement data. Measurement data may comprise direct measurement data and indirect measurement data. Direct measurement data may comprise raw data and/or data obtained from processing raw data. Indirect measurement data may comprise data obtained based on a model. Model may be a mechanistic model and/or a data-driven model. Data-driven model may be based on machine-learning architectures. Data-driven model may be parametrized and/or trained based on historical data including chemical product data. Mechanistic model may be based on and/or may describe the laws of natural science. Measurement data may be obtained by performing a measurement. Measurement data may be obtained with a sensor. For example, sensors may be installed in a chemical production plant to monitor the production of the chemical product and/or to obtain properties associated with the chemical product after the production.

For this purpose, such sensors may be installed within a chemical reactor and/or along a production line. By doing so, the chemical product data is closely related to the chemical product by including as-is measurement data. This measurement data can be included automatically into the digital twin of the chemical product. For example, the measurement data can be included without human interaction enabling an error-free providing of as-is data in relation to the chemical product. Using chemical product data indirectly related to measurement data may provide a realistic insight into the characteristics of a product enabling the shipping or processing of the full chemical product. Thus, using chemical product data indirectly related to measurement data increases the efficiency of a production process by lowering the amount of chemical product to be wasted for analysis.

In an embodiment, the chemical product is produced by using a production line, in particular a production line comprising at least one chemical reactor or production. Additionally or alternatively, the chemical product may be produced within a chemical production network such as a Verbund.

In an embodiment, the digital twin of the chemical product is a digital twin of a first chemical product. The digital twin of a first chemical product may be linked to a digital twin of a first educt of the production process associated with the chemical product and/or to a second chemical product of the production process associated with the chemical product. The second chemical product may have a property independent of the target property and/or the chemical product data set associated with the second chemical product may comprise chemical product data set independent of target property. Chemical product data set(s) independent of target property may be referred to as second chemical product data set (s). Chemical product data set(s) associated with the target property may be referred to as first chemical product data set(s).

Preferably, the digital twin of the chemical product may be linked to a digital twin of the first educt and to a digital twin of a second educt. Furthermore, the digital twin of the first chemical product and the second chemical product may be linked to a digital twin of the first educt and to a digital twin of a second educt. Chemical reactions usually produce more than one product, namely the desired product and a byproduct. In an efficient process the desired product and the byproduct are both used and hence, keeping track of both products is desired. By linking the desired product with its byproduct or educt, the connection within the production of chemical products becomes transparent and the controlling of the product stream is enhanced.

In an embodiment, the target property data and/or target property of the chemical product is specified by a downstream participant of a supply chain including the chemical product. Additionally or alternatively, the target property may be received from a downstream participant of a supply chain including the chemical product. Downstream participant of a supply chain may be a consumer of the chemical product. Consumer of the chemical product may be an entity using the chemical product, in particular processing the chemical product. The chemical product may be an educt for the consumer of the chemical product. Consumer of the chemical product and/or the producer of the chemical product may be part of a supply chain. Producer of the chemical product may further be the generator of the digital twin. Producer of the chemical product may be a supplier for chemical products. Consumer of the chemical product may demand chemical products, in particular form the producer of the chemical products. Consumer of the chemical product may be a downstream participant in the supply chain in relation to the producer of the chemical product. By doing so, the downstream participant's desires can be considered for selecting the chemical product in an automated way. This interaction does not rely on human interaction and hence, time and resources can be saved. Measurement may include analytical measurement. For example, analytical measurement may include spectrometric measurement and/or spectroscopic measurement such as emission spectroscopy, electron spectroscopy or absorption spectroscopy. Obtaining indirect measurement data may include performing a mathematical operation and/or using a model.

In an embodiment, the chemical product data is gathered during production of the chemical product and/or after production of the chemical product. The chemical product data may be associated with the chemical product and/or its production. Hence, this data can be collected before, during and/or after the production. Chemical product data gathered before, during and/or after the production of the chemical product may be collected with a sensor. Chemical product data collected with a sensor may be stored in a data storage unit, e.g. in a database.

In an embodiment, the data model is received based on an identifier associated with the data model. Receiving the data model based on the identifier associated with the data model may comprise providing the identifier, in particular the decentral identifier, associated with the data model and retrieving the data model associated with the provided identifier, e.g. from a data storage. The identifier may be associated with and/or linked to the one or more target properties.

In an embodiment, the digital twin generator is further configured to request the decentral identifier.

In an embodiment, generating a chemical product data set associated with the target property data according to a data model based on the chemical product data comprises and/or refers to applying the respective received data model to the chemical product data. Applying the received data model to the chemical product data may result in generating the chemical product data set. The chemical product data set may be generated by applying the respective received data model to the gathered chemical product data.

In an embodiment, the request to access the chemical product data set associated with the decentral identifier of the digital twin may be associated with and/or provided by the initiator of the request. The request to access may comprise authentication information associated with and/or related to the initiator of the request, authorization information associated with the initiator of the request or a combination thereof. Authenticating and/or authorizing the request to access the chemical product data set may be based on at least one of an initiator of the request, authentication information associated with the initiator of the request, authorization information associated with the initiator of the request or a combination thereof.

In an embodiment, providing the generated digital twin for access by a data consuming node under control of the data owner of the digital twin may comprise providing the decentral identifier associated with the digital twin.

BRIEF DESCRIPTION OF THE DRAWINGS In the following, the present disclosure is further described with reference to the enclosed figures. The same reference numbers in the drawings and this disclosure are intended to refer to the same or like elements, components, and/or parts.

Figs. 1 a-1 c illustrate example embodiments of a centralized computing environment (Fig. 1 a), a decentralized computing environment (Fig. 1 b) and a distributed computing environment (Fig. 1c).

Fig. 2 illustrates an example embodiment of a method for producing a chemical product with a target property.

Fig. 3 illustrates an example embodiment of a supply chain including a first chemical product and a second chemical product.

Fig. 4 illustrates an example embodiment of a chemical production controlled by an operating system.

FIG. 5 illustrates an example embodiment of a decentral network environment.

DETAILED DESCRIPTION

The following embodiments are mere examples for implementing the method, the system or application device disclosed herein and shall not be considered limiting.

Figures 1 a to 1c illustrate different computing environments, central, decentral and distributed. The methods, apparatuses, systems, uses, computer elements of this disclosure may be implemented in decentral or at least partially decentral computing environments. Providing, determining or processing of data may be realized by different computing nodes, which may be implemented in a centralized, a decentralized or a distributed computing environment.

Figs. 1 a,b illustrate example embodiments of a centralized and a decentralized computing environment with computing nodes. Fig. 1c illustrates an example embodiment of a distributed computing environment.

In this example, the peripheral computing nodes 101.1 to 101. n may be connected to one central computing system (or server). In another example, the peripheral computing nodes 101.1 to 101. n may be attached to the central computing node via e.g. a terminal server (not shown). The majority of functions may be carried out by, or obtained from the central computing node (also called remote centralized location). One peripheral computing node 101 .n has been expanded to provide an overview of the components present in the peripheral computing node. The central computing node 101 may comprise the same components as described in relation to the peripheral computing node 101.n. Each computing node 101 , 101.1 to 101. n may include at least one hardware processor 102 and memory 104. The computing nodes 101, 101.1 ...101. n may include multiple structures 106 often referred to as an executable component, executable instructions, computer-executable instructions or instructions. For instance, memory 104 of the computing nodes 101, 101.1 ...101. n may be illustrated as including executable component 106. Executable component or any equivalent thereof may be the name for a structure that is well understood to one of ordinary skill in the art in the field of computing as being a structure that can be software, hardware, or a combination thereof or which can be implemented in software, hardware, or a combination. For instance, when implemented in software, one of ordinary skill in the art would understand that the structure of an executable component includes software objects, routines, methods, and so forth, that is executed on the computing nodes 101, 101.1...101.n, whether such an executable component exists in the heap of a computing node 101, 101.1...101. n, or whether the executable component exists on computer-readable storage media. In such a case, one of ordinary skill in the art will recognize that the structure of the executable component exists on a computer-readable medium such that, when interpreted by one or more processors of a computing node 101, 101.1...101. n (e.g., by a processor thread), the computing node 101,

101.1 ...101 n is caused to perform a function. Such a structure may be computer-readable directly by the processors (as is the case if the executable component were binary). Alternatively, the structure may be structured to be interpretable and/or compiled (whether in a single stage or in multiple stages) so as to generate such binary that is directly interpretable by the processors. Such an understanding of example structures of an executable component is well within the understanding of one of ordinary skill in the art of computing. Examples of executable components implemented in hardware include hardcoded or hard-wired logic gates, that are implemented exclusively or near-ex- clusively in hardware, such as within a field- programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or any other specialized circuit. In this description, the words component, agent, manager, service, engine, module, virtual machine or the like are used synonymously with executable component.

The processor 102 of each computing node 101, 101.1... 101. n may direct the operation of each computing node

101. 101.1 ...101. n in response to having executed computer-executable instructions that constitute an executable component. For example, such computer-executable instructions may be embodied on one or more computer-readable media that form a computer program product. The computer-executable instructions may be stored in the memory 104 of each computing node 101, 101.1...101. n. Computer-executable instructions comprise, for example, instructions and data which, when executed at a processor 101, cause a general purpose computing node 101,

101.1...101. n, special purpose computing node 101, 101.1...101. n, or special purpose processing device to perform a certain function or group of functions. Alternatively, or in addition, the computer-executable instructions may configure the computing node 101, 101.1...101.n to perform a certain function or group of functions. The computer executable instructions may be, for example, binaries or even instructions that undergo some translation (such as compilation) before direct execution by the processors, such as intermediate format instructions such as assembly language, or even source code.

Each computing node 101, 101.1...101. n may contain communication channels 108 that allow each computing node

101.1...101.n to communicate with the central computing node 101, for example, a network enabling the transport of electronic data between computing nodes 101, 101.1...101.n and/or modules and/or other electronic devices. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a computing node 101, 101.1...101.n, the computing node 101, 101.1... 101. n properly views the connection as a transmission medium. A wireless communication medium may comprise any known network technology such as GSM, GPRS, EDGE, UMTS /HSPA, LTE technologies using standards like 2G, 3G, 4G or 5G, the wireless communication protocol may further comprise a wireless local area network (WLAN), e.g. Wireless Fidelity (Wi-Fi). Transmission media can include a network and/or data links which can be used to carry desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general-purpose or special-purpose computing nodes 101, 101.1... 101. n. Combinations of the above may also be included within the scope of computer-readable media.

The computing node(s) 101, 101.1 to 101. n may further comprise a user interface system 110 for use in interfacing with a user. The user interface system 110 may include output mechanisms 110A as well as input mechanisms 110B. The principles described herein are not limited to the precise output mechanisms 110A or input mechanisms 110B as such will depend on the nature of the device. However, output mechanisms 110A might include, for instance, displays, speakers, displays, tactile output, holograms and so forth. Examples of input mechanisms 110B might include, for instance, microphones, touchscreens, holograms, cameras, keyboards, mouse or other pointer input, sensors of any type, and so forth.

Figure 1b illustrates an example embodiment of a decentralized computing environment 100' with several computing nodes 101. T to 101. n' denoted as filled circles. In contrast to the centralized computing environment 100 illustrated in Fig. 1a, the computing nodes 101. T to 101. n' of the decentralized computing environment are not connected to a central computing node 101 and are thus not under control of a central computing node. Instead, resources, both hardware and software, may be allocated to each individual computing node 1O1.T...1O1.n' (local or remote computing system) and data may be distributed among various computing nodes 1O1.T...1O1.n' to perform the tasks. Thus, in a decentral system environment, program modules may be located in both local and remote memory storage devices. One computing node 10T has been expanded to provide an overview of the components present in the computing node 10T. In this example, the computing node 101' comprises the same components as described in relation to Fig. 1a.

Figure 1c illustrates an example embodiment of a distributed computing environment 103. In this example, the distributed computing environment 103 may comprise the following computing resources: mobile device(s) 114, applications 116, databases 118, data storage 120 and server(s) 122. The distributed computing environment may be referred to as cloud computing environment. The cloud computing environment 103 may be deployed as public cloud 124, private cloud 126 or hybrid cloud 128. A private cloud 124 may be owned by an organization and only the members of the organization with proper access can use the private cloud 126, rendering the data in the private cloud at least confidential. In contrast, data stored in a public cloud 126 may be open to anyone over the internet. The hybrid cloud 128 may be a combination of both private and public clouds 124, 126 and may allow to keep some of the data confidential while other data may be publicly available.

Figure 2 illustrates an example embodiment of a chemical production controlled by an operating system.

The chemical production 204 may product a chemical product 206 from one or more educt(s) (also denoted as input material(s)) 202 in connection with an operating system 208 including a digital twin management system. The operating system 208 is used to operate the chemical production 204, for example by managing different production chains present within the chemical production. The chemical production 204 may produce chemical products from one or more chemical materials, for example by reacting one or more of the chemical materials and/or by physically processing one or more materials.

For producing one or more chemical product(s) 206, different materials 202 (also called educts 202 hereinafter) may be provided as physical inputs from material providers or suppliers. The physical inputs to the chemical production 204 may include materials, such raw materials, intermediate materials or a combination thereof. Raw materials may be virgin or recycled raw materials.

The chemical production 204 may be a chemical production network including multiple interlinked processing steps. The chemical production network may be an integrated chemical production network with interrelated production chains. The chemical production network may include multiple different production chains that have at least one intermediate product in common. The chemical production network may include multiple stages of the chemical value chain. The chemical production network may include multiple production chains that produce from one or more educts as input chemical products an output. The chemical production network may include multiple tiers of a chemical value chain. The chemical production network may include a physically interconnected arrangement of production sites. The production sites may be at the same location or at different locations. In the latter case, the production sites may be interconnected by means of dedicated transportation systems such as pipelines, supply chain vehicles, like trucks, supply chain ships or other cargo transportation means.

The chemical production 204 may convert educts 202 by way of chemical conversion to one or more chemical products 206, that exit the chemical production 204. The conversion may be performed via intermediate products or components. The conversion may be a chemical reaction or any other processing step. The educts 202 may be fed into the chemical production 204 at any entry point. The educts 202 may be fed into the chemical production 204 at the start of the chemical production 204. The educts may be considered input for the chemical production.

The chemical production 204 may include multiple production steps. The production steps included in the chemical production 204 may be defined by the system boundary of the chemical production 204. The system boundary may be defined by location or control over production processes. The system boundary may be defined by the site of the chemical production 204. The system boundary may be defined by production processes controlled by one entity or multiple entities jointly. The system boundary may be defined by value chain with staggered production processes to an end product, which may be controlled by multiple entities separately.

The operating system 208 of the chemical production may monitor and/or control the chemical production 204 based on operating parameters associated with the different processes performed by the chemical production 204. One process step monitored and/or controlled may be the feed of educts or the release of produced chemical product(s). Another process step monitored and/or controlled may be the generation of digital twins. Yet another process step monitored and/or controlled may be the provisioning of the generated digital twins to a data providing service for access by a data consuming service. Yet another process step monitored and/or controlled may be the generation of chemical product data set(s) associated with generated digital twins.

The operating system 208 may be configured to receive at least one data model associated with the one or more target properties of the chemical product. The operating system 208 may be configured to gather data associated with the physical entity of the chemical product. The operating system 208 may be configured to generate - for each received data model - a chemical product data set associated with the physical entity of the chemical product from the gathered data according to the respective data model. The operating system 208 may be configured to request a decentral identifier associated with the chemical product data set(s) and optionally a data owner. The operating system 208 may be configured to generate the digital twin of the chemical product using the received decentral identifier and the chemical product data set(s). The operating system 208 may be configured to generate a digital twin by requesting the decentral identifier associated with the one or more target properties of the chemical product and generating the digital twin including the decentral identifier and optionally the chemical product data set.

In an embodiment, the process steps of the chemical production 204 as described above may be executed via the operating system 208 in interaction with a data gathering device, an ID reader, an ID assignor, an aspect agent and a digital twin generator. In this embodiment, the operating system 208 may be communicatively connected to the chemical production 204 and the data gathering device, the ID reader, the ID assignor, the aspect agent, and the digital twin generator. The operating system 208 may be configured to gather chemical product data from the chemical production 204 and/or from a database storing chemical product data eg generated during production of the chemical product. The operating system 208 may include a data gathering device configured to gather said data from the chemical production 204.

The ID reader may be configured to read the physical identifier element physically connected to the material and/or the produced chemical products. The ID assignor may be configured to assign the decentral identifier and associated information to the physical identifier of the produced chemical products. Aspect agent may be configured to receive at least one data model associated with the one or more target properties of the chemical product and to generate - for each received data model - a chemical product data set from the chemical product data and gathered by the data gathering device according to the received data models, for example. The digital twin generator may be configured to request the decentral identifier as well as to generate the digital twin including the decentral identifier and the chemical product data set(s) as. The data gathering device, the ID assignor, the ID reader, the aspect agent and/or digital twin generator may be configured as decentral services or applications executed via the decentral network.

In an embodiment, the ID reader may be configured as part of the operating system 208, while the ID provider and the ID assignor may not be configured as part of the operating system 208.

Figure 3 illustrates an example embodiment of a supply chain including a first chemical product and a second chemical product.

The sketched supply chain constitutes a simplified example with the intention to outline the relation between products and materials within the supply chain and the digital twins. As it can be seen in the drawing, each product may be associated with a digital twin. Digital twins may be interconnected. Preferably, a digital twin associated with a first chemical product may be associated with the raw materials used for producing the first chemical product. In the example the first chemical product may be produced based on raw material 1. From the first chemical product downstream product 1 may be produced. Followingly, the digital twin of the first chemical product may be linked to the digital twin of the raw material 1 and the digital twin of downstream product 1 may be linked to the digital twin of the first chemical product. Linking digital twins may refer to one of the digital twin or a chemical product data set included in such digital twin pointing to the other digital twin. In particular, one of the digital twins may comprise the digital twin ID of the other digital twin. For example, the digital twin of the first chemical product may comprise an identifier, preferably a decentral identifier associated with the digital twin of the raw material 1 . The digital twin of the first chemical product may be linked to the digital twin of the downstream product based on the first chemical product via the digital twin of the downstream product comprising the decentral identifier associated with the first chemical product. Similarly, the digital twin of the second chemical product may be linked with the digital twin of the raw material 1, the digital twin of the raw material 2 and the digital twin of the downstream product 2. Further, the end-of-life product may be associated with a digital twin. End-of-life product may refer to a product intended to be become waste after usage. In contrast, raw material, chemical product and/or downstream product may be intended for further processing before becoming at least part of an end-of-life product.

In an embodiment, the digital twin of the first chemical product may comprise one or more decentral identifier(s) associated with a digital twin of one or more educt(s) and/or input material(s) for producing the first chemical product. The one or more decentral identifier(s) associated with a digital twin of one or more educt(s) and/or input material(s) may be suitable for identifying and/or accessing the digital twin of one or more educt(s) and/or input material(s). This may be realized similarly for the second chemical product. By doing so, the digital twin of the first chemical product may represent the upstream relationship of the first chemical product. In particular, the digital twins associated with the products of a supply chain can represent the processing of the respective products. For this purpose, the digital twin connects the real world of the physical product entity with the digital representation of the physical product entity. This is utterly important since especially with the chemical product being for example a liquid or a salt production details and product details can be not accessible due to the nature of chemistry. In chemistry, every atom of a kind looks the same independent of its origin, but especially the origin may be important to establish sustainable and equitable supply chains. Further, handling of such information digitally in a decentral approach as presented herein enables a responsible data sharing and hinders tempering of data.

The first chemical product and the second chemical product may be produced by a chemical production network as described within the context of Figure 2.

Figure 4 illustrates an example embodiment of a method for producing a chemical product with a target property.

A request for producing the chemical product with the target property is received 410. The request includes target property data. Target property data may comprise and/or indicate the target property. The request may be initiated and/or provided by a downstream participant of a supply chain including the chemical product. Additionally or alternatively, the request for providing the chemical product may be generated based on a request by the downstream participant, for example by a request generation unit within a production system. The downstream participant may be a customer of the producer of the chemical product. The downstream participant may desire to process the chemical product into a downstream product of the supply chain and/or into an end-of-life product. An example of such a supply chain may be seen in Figure 3. The downstream participant may desire a digital representation in the form of a digital twin of the chemical product. The digital twin may include information that consumers of the end-of-life product desire and/or governmental regulations may require. For example, the digital twin may include environmental attrib- ute(s) associated with the chemical product. Information in relation to the environmental attribute(s) may be required for the sale of the chemical product and/or an end-of-life product produced from the chemical product. Hence, the digital twin enables the sharing of product-related data to increase the efficiency of producing, disposing, recycling and/or reprocessing of a chemical product within the supply chain. The desired and/or required information may not be available from analyzing the chemical product. For example, the origin of an educt including the content of recy- clate-based or biobased educt used for producing, in particular synthesizing the chemical product may not be obtained from the chemical product itself but is highly desired and/or required. The digital twin enables the allocation of the chemical product to educts and/or input materials, in particular within complex chemical networks. Thus, the digital twin is a major enabler for sustainable supply chains.

The chemical product associated with the target property data is produced 420. This may refer to producing the chemical product with the target property. The production may be initiated based on the request for producing the chemical product associated with the target property data. The chemical product may be produced within a production line. The chemical product may be produced based on a batch process and/or a continuous process. Producing the chemical product may comprise synthesizing the chemical product. Producing the chemical product may result in producing more than one chemical product. Specifically, producing the chemical product may result in producing a byproduct. The byproduct may be the main product and/or a side product of the chemical reaction associated with the production of the chemical product. The chemical product may be produced within a chemical plant and/or a chemical reactor. The producing of the chemical product may further or alternatively include a purification of the chemical product. For example, a material may comprise more than one compound. Extracting one compound of the material may result in obtaining the chemical product. The material may be obtained by a chemical reaction. The material may comprise a byproduct. It is remarked that chemical reactions may converse a fraction of the amount of educt provided for producing the chemical product since chemical reactions are based on a chemical equilibrium. Hence, the material obtained from a chemical reaction may further comprise an educt and/or an intermediate. The intermediate may be a compound that can be reacted from the educt to the chemical product. It is remarked that the intermediate can be a downstream product as described in the context of Figure 3. During the producing of the chemical product, chemical product data may be generated directly, e.g. with a sensor. Additionally or alternatively, chemical product data may be obtained indirectly. Such indirect measurement data may include data obtained from deploying a model. The model may be configured to receive an indication of the chemical product, e.g. a denotation, one or more educt(s) for producing the chemical product and/or a structure associated with the chemical product. The model may be configured to determine the chemical product data in response to receiving the indication of the chemical product. For example, the model may be a whitebox model, a hybrid model of a whitebox model and a blackbox model and/or a blackbox model. The obtained chemical product data may be stored in a database. The obtained chemical product data may be available for a part of a system for generating a digital twin to be accessed. At least a part of the obtained chemical product data may comprise the target property data. For example, chemical product data associated with three chemical products may be obtained. The chemical products may be produced for example in three different production batches. At least one of the products may be associated with the target property data. At least one of the product may be independent of the target property data, e.g. because of a different treatment of one production batch compared to the at least one other production batches. Followingly, at least a part of the chemical product data may comprise the target property data. The chemical product associated with the target property data may be suitable for a target processing. Hence, a chemical product consumer may request to process the chemical product associated with the target property data. The chemical product data may be transferred into the database. The chemical product data may be processed after being obtained or generated. Additionally or alternatively, the chemical product data may be processed prior to and/or after being transferred into the database. Processing the chemical product data may include performing mathematical operations onto the chemical product data.

The chemical product data comprising the target property data is gathered 430. For example, the chemical product data comprising the target property data may be selected from the databased comprising the chemical product data. The selected chemical product data may be associated with the chemical product with the target property. The chemical product data comprising the target property data may be received. Gathering the chemical product data comprising the target property data may include receiving the chemical product data comprising the target property data. In another embodiment, gathering the chemical product data may comprise generating the chemical product data, e.g. with a sensor and/or by processing raw data into the chemical product data. For example, during the production of the chemical product raw material data associated with the production of the chemical product may be obtained, in particular raw material data associated with the chemical product may be obtained. The raw material data associated with the production of the chemical product and/or with the chemical product may be processed. Processing the raw material data may result in obtaining the chemical product data. Gathering the chemical product data may include obtaining the chemical product data. Hence, chemical product data may be obtained, produced and/or generated by processing raw data associated with the chemical product and/or associated with the production of the chemical product.

A request to provide a decentral identifier associated with the chemical product data set and optionally a data owner is received 440. The decentral identifier may correspond to the decentral identifier included in the digital twin or may be a newly decentral identifier. The decentral identifier (ID) may be generated by a decentral ID generator. The generation of the decentral ID may be requested. Based on a request to generate a decentral ID, the decentral ID may be generated and/or provided, in particular to a digital twin generator. The decentral ID generator may be computing node. The decentral ID generator may act as a DID owner's management module, user agent, ID hub and/or certification issuer. The request to provide a decentral identifier may initiate the providing of a request for generating a decentral ID. The request for generating a decentral ID may be provided to the decentral ID generator and/or received by the decentral generator. The decentral identifier may be requested as described within the context of Figure 2.

A data model associated with the target property data is received 450. The data model may be received based on a request to receive the data model. The data model may be received and/or retrieved from a database. The data model may be associated with an identifier. The chemical product, the request for producing the chemical product and/or a request for initiating the generation of a digital twin may be associated with an identifier. Preferably the chemical product, the request for producing the chemical product and/or a request for initiating the generation of a digital twin may be associated with the identifier the data model is associated with. Based on the identifier associated with the data model, the data model may be requested, retrieved and/or received, in particular based on providing the identifier associated with the data model. The data model may be suitable for selecting the data corresponding to the chemical product data set from the gathered chemical product data and/or transforming the chemical product data into the chemical product data set. The data model may define a structure associated with the chemical product data set. The data model may be received as described within the context of Figure 2.

A chemical product data set comprising the target property data is generated according to the data model based on the chemical product data 460. The sematic description of the data model may define the chemical product data set, in particular the structure and/or the content of the chemical product data set. The chemical product data set may be generated by applying the data model to the chemical product data. The data model may transform the chemical product data into the chemical product data set and/or the data model may select the data corresponding to the chemical product data set from the gathered chemical product data. The chemical product data set may comprise a defined structure, in particular a defined structure of the content. The chemical product data set may be generated as described within the context of Figure 2.

A digital twin of the chemical product including the decentral identifier and the chemical product data set is generated 470. Preferably, the generation of the digital twin is generated in response to the request to provide a decentral identifier. The generation of the digital twin may be triggered by the request to provide a decentral identifier. The digital twin may be generated as described within the context of Figure 2. The digital twin may be stored by a data owner associated with the digital twin, in particular the chemical product data set linked to the digital twin. The data owner may be in control of access to the digital twin and/or the chemical product data set linked to the digital twin.

The chemical product associated with the target property data and/or the decentral identifier and/or the chemical product data set is provided 480. Providing the decentral identifier may result in granting the downstream participant access to the chemical product data set and/or the digital twin under control of the data owner of the digital twin. Providing the chemical product may comprise supplying the downstream participant with the chemical product. The chemical product may be associated with the decentral identifier. Preferably, the chemical product is associated with a physical identifier. The physical identifier may be associated with the decentral identifier. In particular, the physical identifier may link the chemical product with the decentral identifier and/or the digital twin. Providing the decentral identifier may include providing the chemical product with the physical identifier. Providing the decentral identifier may include reading the physical identifier element physically connected to the chemical product, for example using a device configured to scan the physical identifier element. Reading the physical identifier may result in receiving access to the chemical product data set and/or the digital twin under control of the data owner of the digital twin.

FIG. 5 illustrates an example embodiment of a decentral network environment.

The decentral network environment may include a decentral participant network 530. The decentral participant network 530 may include one or more decentral network participants 502 to 514. The decentral network participants 502 to 514 may be part of a product ecosystem including chemical products. The product ecosystem may include production chains to produce a use product. The product ecosystem may include recycling chains to recycle at least part of a use product, preferably at the end-of-use stage. The product ecosystem may include a raw input material supplier 502, a chemical product producer 504, a chemical product consumer 506, an OEM 508, an end-product use product user 510, an EOL product collector 512, wherein EOL is an abbreviation for end-of-life, and a recycler 514. The decentral participant network 530 may be a chemical supply chain. The product ecosystem may allow to use materials resulting from recycling of use products to produce new products, such as chemical products. The product ecosystem may be associated with the production and/or recycling of physical products. The product may be a chemical product, an intermediate chemical product, a component, a component assembly, a use product, an end-of-life product or a recycled product. The participant(s) of the decentral participant network 530 may be associated with the production of the product and/or recycling of the product. The decentral network participant 502 to 514 may refer to a manufacturer of physical products, such as input material supplier 502, chemical product producer 504, chemical product consumer 506, OEM 508, a user of physical goods, such as use product user 510, and/or a participant of a recycling chain associated with the physical product, such as EOL product collector 512 and recycler 514. The decentral network participant may be associated with a decentral participant identifier. The decentral participant identifier may uniquely identify the decentral network participant within the decentral participant network 530.

The participant(s) of the decentral participant network 530 may be connected via physical material flow 536. The material flow 536 may correspond to the flow of product from one participant of the decentral participant network 530 to the downstream participant of the decentral participant network 530. The material flow 536 may refer to a continuous or a discontinuous flow of product. The flow of product may include any means of transportation suitable to transport the product from a participant to the downstream participant. The means of transportation may include pipes, containers, barrels, packages. The material flow 536 may be associated with raw materials used to produce the chemical product, such as virgin raw materials. The raw materials may be provided to the chemical product manufacturer for producing chemical product(s) and/or intermediate chemical product(s) (not shown).

At least part of the participants of the decentral participant network 530 may be associated with decentral participant network nodes 516 to 528. The decentral participant nodes 516 to 528 may be under control of the respective decentral participant associated with the respective decentral participant node. The decentral participant nodes 516 to 528 may form decentral network 534. The decentral network 534 may be a peer-to-peer communication network. The decentral network 534 may be configured to perform data transactions. The data flows 532 may be based on a transaction protocol including authentication and/or authorization mechanism(s). Based on the authentication and/or authorization mechanism(s) a peer-to-peer communication between decentral network nodes 516 to 528 associated with decentral network participants 502 to 514 may be established. The one or more authentication mechanism(s) may be associated with or linked to a decentral identifier. The one or more authentication mechanism(s) associated with the decentral identifier may be accessible by a decentral data providing network node and/or a decentral data consuming network node. The decentral configuration allows for more efficient use of computing resources and strengthens control by the data owners of the decentral network.

Data transactions between decentral network participant nodes may be based on a decentral identifier associated with respective product data to be accessed. The decentral identifier may be uniquely associated with the physical entity of the product and associated product data. The decentral identifier may uniquely identify the respective product within the decentral network. The decentral identifier may be associated with further decentral identifier(s), such as decentral identifier(s) of product(s) used to produce the product. This may allow to track the product(s) used to produce a product, such as a use product. The decentral identifier may be included in a digital access element associated with the product. The data flow 532 (e.g. transactions) between decentral network participant nodes may be directly or indirectly associated with the physical material flow 536 between the decentral network participants. For instance, data flow 532 may be directly associated with material flow 536 if data associated with an input material provided from the input material supplier 502 to the chemical product producer 504 is accessed by a decentral data consuming network node associated with said chemical product producer 504. For instance, data flow 532 may be indirectly associated with material flow 536 if data associated with a chemical product produced by chemical product producer 504 is accessed by a decentral data consuming network node associated with recycler 514.

The decentral participant nodes 516 to 528 may be decentral computing nodes. The decentral computing node may be any device or system that includes at least one physical and tangible processor, and a physical and tangible memory capable of having thereon computer-executable instructions that are executed by a processor. The memory may take any form and depends on the nature and form of the computing node.

At least part of the decentral participant nodes 516 to 528 may be decentral data providing network nodes. At least part of the participant nodes 516 to 528 may be decentral data consuming network nodes. A participant of the decentral participant network 530 may be associated with a decentral data providing network node and/or a decentral data consuming network node depending on whether data is provided to downstream participants and/or consumed from upstream participants. For instance, input material supplier 502 may be associated with a decentral data providing network node configured to provide input material data to a downstream participant (e.g. chemical product producer 504). In addition to or alternatively, chemical product producer 504 may be associated with a decentral data consuming network node configured to access data associated with a recycled input material produced by an upstream participant (e.g. recycler 514).

The decentral network 534 may further include decentral network nodes. The further decentral network nodes may be decentral infrastructure service nodes (not shown in FIG. 5). The decentral infrastructure service nodes may not be associated with a participant of the product ecosystem. The decentral infrastructure service nodes may provide services for decentral participant nodes 516 to 528, such as verifying the identity of the decentral network participant nodes 516 to 528 prior to performing a data exchange. The decentral network participant nodes 516 to 528 may be associated with or include certificate(s), such as X.509 certificate(s).

The certificate(s) may be associated with decentral infrastructure service node(s) including e.g. a certificate issuing service and/or a dynamic provisioning service providing dynamic attribute tokens (e.g. OAuth Access Tokens). This way the decentral network participant nodes 516 to 528 possess a unique identifier embedded in a X.509 certificate that identifies the respective decentral network participant node 516 to 528. The information required to verify the certificate may be provided via an authentication registry associated with the certificate issuing service and/or a dynamic provisioning service. For instance, in the IDSA Reference Architecture Model, Version 3.0 of April 2019, a decentral data providing network node associated with a data owner, a Certification Authority (CA), a Dynamic Attribute Provisioning Service (DAPS) and a decentral data consuming network node associated with a data consumer are used to verify the identity prior to performing a data exchange (not shown).

The method may be implemented by a system for generating a digital twin of a chemical product with a target property and/or providing a chemical product associated with a digital twin. The embodiments on the method may equally apply to the system disclosed herein. Further, the embodiments may equally apply to a method for generating a digital twin of a chemical product with a target property and/or a method for using a digital twin, preferably to process the chemical product associated with the digital twin. Further, the embodiments may equally apply to the digital twin as generated by the methods and/or systems disclosed herein.

The present disclosure has been described in conjunction with preferred embodiments and examples as well. However, other variations can be understood and effected by those persons skilled in the art and practicing the claimed invention, from the studies of the drawings, this disclosure and the claims. Notably, in particular, any steps presented can be performed in any order, i.e. the present invention is not limited to a specific order of these steps. Moreover, it is also not required that the different steps are performed at a certain place or at one computing node of a distributed computing system, i.e. each of the steps may be performed at different computing nodes using different equip- ment/data processing.

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

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

Any disclosure and embodiments described herein relate to the methods, the systems, devices, the computer program element lined out above and vice versa. Advantageously, the benefits provided by any of the embodiments and examples equally apply to all other embodiments and examples and vice versa.

Claims

CLAIMS:

1 . A computer-implemented method for generating a digital twin of a chemical product having one or more target properties, the method comprising: gathering chemical product data associated with the chemical product, wherein the chemical product data includes target property data associated with the target property, providing a decentral identifier associated with the chemical product data and optionally a data owner, receiving one or more data model(s) associated with the one or more target properties of the chemical product, generating at least one chemical product data set comprising target property data according to the one or more data model (s) based on the chemical product data, in response to the request, generating the digital twin of the chemical product including the decentral identifier and the chemical product data set, and optionally providing the generated digital twin for access by a data consuming node under control of the data owner of the digital twin.

2. A method for producing a chemical product having one or more target properties, the method comprising: receiving a request for producing the chemical product with the target property, wherein the request comprises target property data, producing the chemical product based at least in part on the received target property data, gathering chemical product data associated with the produced chemical product, wherein the chemical product data includes target property data associated with the one or more target properties, providing a decentral identifier associated with the chemical product data set and optionally a data owner, receiving at least one data model associated with the target property data, generating a chemical product data set comprising the target property data according to the at least one data model based on the chemical product data, generating the digital twin of the chemical product including the decentral identifier and the chemical product data set, providing the chemical product associated with the digital twin and/or providing the decentral identifier and/or providing the chemical product data set.

3. The method according to any one of the preceding claims, wherein the target property data is specified by a downstream participant of a supply chain associated with the chemical product and/or the target property is received from a downstream participant of a supply chain associated with the chemical product.

4. The method according to any one of the preceding claims, wherein generating a chemical product data set associated with the target property data according to the data model based on the chemical product data comprises and/or refers to applying the respective received data model to the chemical product data.

5. The method according to any one of the preceding claims, wherein the chemical product data is gathered during production of the chemical product and/or after the production of the chemical product.

6. The method according to any one of the preceding claims, wherein providing the decentral identifier comprises assigning a physical identifier associated with the chemical product to the decentral identifier and/or providing a chemical product associated with the decentral identifier.

7. The method according to any one of the preceding claims, wherein the method further includes providing a request for authenticating and/or authorizing prior to gathering chemical product data and/or prior to providing the decentral identifier and/or prior to providing the chemical product data set.

8. The method according to any one of the preceding claims, wherein the target property comprises at least one of chemical product name, qualitative chemical product composition, quantitative chemical product composition, chemical product processing instruction, qualitative chemical educt composition, quantitative chemical product educt composition, educt product processing instruction, chemical educt production data, material property, environmental attribute, chemical product production data, chemical product declaration data, chemical product safety data or a combination thereof.

9. The method according to any one of the preceding claims, wherein at least a part of the chemical product data is associated with measurement data.

10. The method according to any one of the preceding claims, wherein the data model is received based on an identifier associated with the data model.

11. A system for generating a digital twin of a chemical product with a target property, the system comprising: one or more computing node(s); and one or more computer-readable media having thereon computer-executable instructions which, when executed by the one or more computing nodes, configure the one or more computing nodes to perform any one of the methods according to claim 1-10.

12. A system for providing a chemical product associated with a digital twin, the system comprising: a production line configured to produce the chemical product connected to or comprising a physical identifier; a digital twin generator configured to generating the digital twin according to the methods as claimed in any one of claims 1 to 10 or by the system as claimed in claim 11 , and an assigning device configured to assign the physical identifier to the decentral identifier included in the digital twin to the chemical product.

13. Use of a digital twin as generated according to the methods as claimed in any one of claims 1 to 10 or as generated by the systems as claimed in claim 11 and 12 to process the product associated with the digital twin.

14. Digital twin as generated according to the methods as claimed in any one of claims 1 to 10 or as generated by the systems as claimed in claims 11 and 12.

15. A computer element with instructions, which when executed on one or more computing node(s) are configured to carry out the steps of any one of the methods as claimed in any one of claims 1 to 10 or are configured to be carried out by any one of the systems according as claimed in any one of claims 11 and 12.