Material management method and apparatus

Abstract

Embodiments of the present application provide a material management method and an apparatus. The method includes: receiving first material data from a first system; and determining a first entity data model corresponding to the first material data, the first entity data model being configured to store attribute information of the first material data by a predetermined format; and receiving a data request from a second system, the data request being used for obtaining the attribute information of the first material data; and sending the attribute information of the first material data in the first entity data model to the second system according to the data request. The technical solutions of this application can improve the efficiency of material management.

Description

MATERIAL MANAGEMENT METHOD AND APPARATUS

[0001] The present application is related to, and claims priority to, Russian Federation provisional patent applicationSerial No. PCT / RU2023 / 000267, entitled "SCHEMA FOR MATERIAL INTELLIGENCE MANAGEMENT SOFTWARE", filed on September 11, 2023.

[0002] The disclosures of the aforementioned application are hereby incorporated by reference in its entirety.TECHNICAL FIELD

[0003] Embodiments of the present application relate to the field of information management, and more specifically, to a material management method and an apparatus.BACKGROUND

[0004] In a highly competitive environment, leading industries are faced with the vital task of reducing time and cost in research and development (R&D), design and manufacture of high-tech products. Modem economic conditions dictate the need to move from expensive full-scale tests to digital design and simulation technologies like “digital thread and digital twin strategy”.

[0005] Nowadays materials are one of the highest costs for a manufacturing enterprise in addition to personnel. Yet, while most businesses, rightly, invest in organizations and information technology (IT) to manage human resources, investment in managing materials intellectual property has been small by comparison.

[0006] The primary reason is that older generic database approaches struggled to support the required use cases, due to the complexity of materials information. A material may be defined by several hundred properties or attributes, many highly specialized in their nature and in how they are measured and recorded. Many of these attributes also have their own lifecycles, evolving with new test results, in-service information or analyses, or external factors such as legislation or price volatility. This makes managing materials information a very different proposition to managing human resource (HR) or financial data — or even computer aided design (CAD) data, which has relatively few attributes despite the large file sizes.

[0007] Eventually materials become attached to a product at the conceptual design phase and evolve with the productthrough the lifecycle according to modem digital twin and digital thread strategies. Keeping data up to date and synchronized across the many IT applications used by organizations throughout a lifecycle is extremely complex. Therefore, effective management of materials intelligence is essential to avoiding critical issues and data gaps in simulation, design and manufacturing planning and execution.SUMMARY

[0008] Embodiments of the present application provide a material management method and an apparatus. The technical solutions of this application can improve the efficiency of material management.

[0009] According to a first aspect, an embodiment of the present application provides a material management method including: receiving first material data from a first system; and determining a first entity data model corresponding to the first material data, the first entity data model being configured to store attribute information of the first material data by a predetermined format; and receiving a data request from a second system, the data request being used for obtaining the attribute information of the first material data; and sending the attribute information of the first material data in the first entity data model to the second system according to the data request.

[0010] The method of the present application uses a unified material management system that can interact with multiple systems during the life cycle of a product, with identical materials stored through the same entity data model, ensuring uniformity, integrity and traceability of materials.

[0011] This application provides a material management system that can be embedded into a product lifecycle management (PLM) to provide special extensions to the PLM-entity and data modeling. Thus a unified platform for intelligent data management of materials can be formed.

[0012] The material management system of this application has the most complete material data available for the entire product life cycle. The material data includes attribute information which is configured to describe the properties of the corresponding material, where the attribute information can include reference data from third parties and / or proprietary data (data from tests, statistically valid data, data from simulation analysts and designers, etc.).

[0013] The entity data model provides a description of the data structure at an abstract level, which can be converted into a concrete physical storage form in a practical implementation. In one possible implementation, the first entity data model can be a table, where attributes correspond to columns of the table. In another possible implementation, the first entity data model can be code through a domain specific language. The specific form in which the entity data model is stored depends on the actual implementation and the data storage technology chosen.

[0014] In a possible implementation, the first system or the second system is any one of a laboratory information management system (LIMS), a master data management (MDM) system, a computer-aided engineering (CAE) system, a computer-aided design (CAD) system, and a computer-aided manufacturing (CAM) system.

[0015] The LIMS is a software system for managing laboratory samples, data and processes. In materials information management, the LIMS can be used to record and track materials data for laboratory testing and analysis. It can manage sample information, experimental results, quality control and other data related to laboratory activities.

[0016] The MDM is a data management strategy and technology used to unify master data across an organization. In material information management, the MDM can be used to manage material -related master data, such as material numbers, classifications, attributes, etc.

[0017] The CAE is a method of using computer technology to assist in engineering analysis and design. In material information management, the CAE can use material-related data for engineering analysis, such as material mechanical properties and thermal properties. It can interact with the material management system to obtain the required material data.

[0018] The CAD is a method of product design using computer technology. In material information management, the CAD can use material -related data for product design and modeling, such as material appearance, dimensions, material, etc. The CAD can interact with the material management system to obtain the required material properties and characteristics.

[0019] The CAM is a method of utilizing computer technology to assist in the manufacturing process. In material information management, the CAM can use material -related data for planning and controlling the manufacturing process, such as material processing parameters, process specifications, etc. The CAM can interact with the material management system to obtain the required material information.

[0020] The material management system provided by the present application can interact with multiple systems and ensures uniformity in the storage of the same material through an entity data model, which improves the efficiency of material management during the product life cycle.

[0021] In a possible implementation, the determining a first entity data model corresponding to the first material data includes: creating the first entity data model corresponding to the first material data, or, updating the first entity data model corresponding to the first material data.

[0022] If there is no entity data model about the first material data in the material management system, an entity data model corresponding to the first material data will be created; or if there is an entity data model about the first material data in the material management system, the entity data model corresponding to the first material data will be updated.

[0023] The method of the present application uses a unified material management system that stores the same material through the same entity data model, ensuring uniformity, integrity and traceability of materials.

[0024] In a possible implementation, the data request includes identifications of the first material data and the attribute information.

[0025] By identifying the first material data and the attribute information, the material management system can retrieve the corresponding attribute information in the first entity data model.

[0026] In a possible implementation, the sending the attribute information of the first material data in the first entity data model to the second system according to the data request includes: obtaining the first entity data model by retrieving the first entity data model among multiple entity data models based on the data request; and sending the attribute information of the first material data in the first entity data model to the second system.

[0027] There are multiple entity data models in the material management system, and by identifying the first material data and the attribute information, the material management system can retrieve the first entity data model among the multiple entity data models, and thus obtain the corresponding attribute information in the first entity data model.

[0028] The method of the present application uses a unified material management system that can interact with multiple systems during the life cycle of a product, with identical materials stored through the same entity data model, ensuring uniformity, integrity and traceability of materials.

[0029] In a possible implementation, the material management system is applied in a product lifecycle management (PLM).

[0030] The method of the present application uses a unified material management system that can interact with multiple systems during the life cycle of a product, with identical materials stored through the same entity data model, ensuring uniformity, integrity and traceability of materials.

[0031] In a possible implementation, the material management system is implemented by a microservices architecture.

[0032] The microservices architecture is a style of software architecture that splits a large application into a set of small, independent services, each focused on accomplishing a specific business function. Each service runs in its own process and communicates with each other through a lightweight communication mechanism, usually an application programming interface (API).

[0033] In the microservices architecture, each service can be developed, deployed, and scaled independently, resulting in a high degree of autonomy. This modular design allows development teams to develop different services in parallel, making it easier to achieve continuous delivery and rapid iteration.

[0034] The material management system based on microservices provides the ability to manage information about materials at each stage of the end-to-end process, and also provides a special data schema, process schema and classifiers.

[0035] The material management system utilizes a microservices architecture that simplifies the integration processwith external systems. It reduces the complexity of integration and customization, making the system more flexible and scalable.

[0036] In a possible implementation, the attribute information of the first material data includes any one or more of reference data, test data, statistical data, simulation data, and design data.

[0037] According to the second aspect, an embodiment of this application provides a computing apparatus, and the computing apparatus has the function of implementing the method in the first aspect. The function may be implemented by hardware executing corresponding software. The hardware or the software includes one or more modules corresponding to the function.

[0038] According to a third aspect, an embodiment of this application provides a computer-readable storage medium including instructions. When the instructions are run on a computer, the computer is enabled to perform the method in the first aspect or any possible design of the first aspect.

[0039] According to a fourth aspect, an embodiment of this application provides a computing device, including a processor, a memory, and a communications interface. The processor is connected to the memory and the communications interface. The memory is configured to store instructions, the processor is configured to execute the instructions, and the communications interface is configured to communicate with another network element under control of the processor. When the processor executes the instructions stored in the memory, the processor is enabled to perform the method in the first aspect or any possible design of the first aspect.

[0040] According to a fifth aspect, an embodiment of this application provides a computing device cluster, including at least one computing device, where the computing device includes a processor and a memory coupled with the processor, where the memory is configured to store a computer program, and the processor is configured to invoke and run the computer program stored in the memory, so that the computing device executes the method in the first aspect or any possible design of the first aspect.

[0041] According to a sixth aspect, a chip system is provided, where the chip system includes a memory and a processor, the memory is configured to store a computer program, and the processor is configured to invoke the computer program from the memory and run the computer program, so that a server on which a chip is disposed performs the method in the first aspect or any possible design of the first aspect.

[0042] According to a seventh aspect, a computer program product is provided, where when the computer program product is run on a computing device cluster, the computing device cluster is enabled to perform the method in the first aspect or any possible design of the first aspect.DESCRIPTION OF DRAWINGS

[0043] FIG. 1 is a schematic diagram of variety of material requirements according to an embodiment of the present application.

[0044] FIG. 2 is a schematic diagram of material information types according to an embodiment of the present application.

[0045] FIG. 3 is a schematic diagram of multiple datasets of materials according to an embodiment of the present application.

[0046] FIG. 4 is a schematic diagram of managing information in the context of a product lifecycle according to an embodiment of the present application.

[0047] FIG. 5 is a schematic diagram of a material data management architecture according to prior art.

[0048] FIG. 6 is a schematic diagram of a material intelligence management process in a typical architecture according to prior art.

[0049] FIG. 7 is a schematic diagram of a material management method according to an embodiment of the present application.

[0050] FIG. 8 is a schematic diagram of an architecture of material intelligence management software according to an embodiment of the present application.

[0051] FIG. 9 is a schematic diagram of an end-to-end process for intelligent management of materials according to an embodiment of the present application.

[0052] FIG. 10 is a schematic diagram of intelligent data model engine (IDME) according to an embodiment of the present application.

[0053] FIG. 11 is a schematic block diagram of a computing apparatus 600 according to an embodiment of the present application.

[0054] FIG. 12 is a schematic diagram of an architecture of a computing device according to an embodiment of the present application.

[0055] FIG. 13 is a schematic diagram of an architecture of a computing device cluster according to an embodiment of the present application.

[0056] FIG. 14 is a schematic diagram of a connection between computing devices over a network according to an embodiment of the present application.DESCRIPTION OF EMBODIMENTS

[0057] The following describes the technical solutions in the present application with reference to the accompanying drawings.

[0058] The following describes the technical solutions in the present application with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, and not all of them. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without making creative labor shall fall within the scope of protection of the present application.

[0059] The present application will present aspects, embodiments, or features around systems that include multiple devices, components, modules, etc. It should be understood and appreciated that the individual systems may include additional devices, components, modules, etc., and / or may not include all of the devices, components, modules, etc., discussed in connection with the accompanying drawings. In addition, combinations of these options may be used.

[0060] In addition, in the embodiments of the present application, the word "exemplarily" and the phrase "as an example" are used to indicate, for example, illustration or description. Any embodiment or design solution described as "exemplarily" in this application should not be construed as being superior to or more advantageous than other embodiments or design solutions. Rather, the use of the word "example" is intended to present the concept in a specific manner.

[0061] The phrases "in some possible embodiments", "in some possible application scenarios", etc., appearing in various places in this description, do not necessarily refer to the same embodiments, but rather mean "one or more, but not all, embodiments" unless otherwise specifically emphasized. Unless otherwise specifically emphasized, the terms "including", "comprising", "having", and variations thereof all mean "including but not limited to".

[0062] In the present application, "at least one" refers to one or more, and "multiple" refers to two or more. "And / or", describing the association of the associated objects, indicates that three relationships can exist. For example, A and / or B can mean A alone, both A and B, and B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following associated objects are in an "or" relationship.

[0063] The application scenarios described in the embodiments of the present application are intended to illustrate the technical solutions of the embodiments of the present application more clearly and do not constitute a limitation to the technical solutions provided by the embodiments of the present application. It is known to those of ordinary skill in the art that the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems as the system architecture evolves and new application scenarios emerge.

[0064] In order to better describe the solutions of embodiments in the present application, concepts and terms that maybe involved in the present application will be described below.

[0065] (1) Digital twin

[0066] Digital twin is a virtual representation of real -world entities and processes that are synchronized at a specified frequency and fidelity.

[0067] (2) Digital thread

[0068] Digital thread is a mechanism for correlating information across multiple dimensions of a virtual representation, with these dimensions including (but not limited to) time or lifecycle stage (including design intent), model type, and configuration history.

[0069] (3) Material intelligence

[0070] Material intelligence (MI) refers to the ability of materials to sense, respond, and adapt to their environment through a combination of advanced materials design, preparation, and characterization techniques, as well as technological tools such as data science and artificial intelligence, in the field of materials science and engineering. Material intelligence is a resource of material data knowledge and experience that can help improve business efficiency.

[0071] (4) Intelligent data model engine (IDME)

[0072] IDME provides an industry digital backbone network of industry data model-driven engines, industry data model standards, and industry data connectivity capabilities required by the industry software field. It is based on metadata- driven multi-tenancy concepts and technologies to provide an industry data management engine that supports data model- driven, feature -configurable, service orchestration, and one-click release. It also provides multiple out-of-the-box data management, multi -database support, and total product (TP) / average product (AP) convergence capabilities.

[0073] (5) Master data (MD)

[0074] Master data is the core data shared by various departments or systems within an organization, which usually changes infrequently and is widely used throughout the organization.

[0075] In a highly competitive environment, leading industries such as automotive, aerospace and defense (A&D), electronic and semiconductors (E&S), energy and utilities (E&U), etc. are faced with the vital task of reducing time and cost in research and development (R&D), design and manufacture of high-tech products. Modem economic conditions dictate the need to move from expensive full-scale tests to digital design and simulation technologies like “digital thread and digital twin strategy”. In addition, to achieve breakthrough results, it is necessary to consider the massive adoption of cloud computing (private / hybrid / public), which has become a key driver of many of the most revolutionary technology trends, including artificial intelligence (Al), the Internet of things (loT), as well as remote and hybrid work.

[0076] Nowadays materials are one of the highest costs for a manufacturing enterprise in addition to personnel. Yet,while most businesses, rightly, invest in organizations and IT to manage human resources, investment in managing materials intellectual property has been small by comparison.

[0077] Typical costs and risks due to uncontrolled materials information are shown in Table 1.Table 1

[0078] FIG. 1 is a schematic diagram of variety of material requirements according to an embodiment of the present application.

[0079] The primary reason is that older generic database approaches struggled to support the required use cases, due to the complexity of materials information. A material may be defined by several hundred properties or attributes, many highly specialized in their nature and in how they are measured and recorded. Many of these attributes also have their own lifecycle s, evolving with new test results, in-service information or analyses, or external factors such as legislation or price volatility. This makes managing materials information a very different proposition to managing HR or financial data — or even CAD data, which has relatively few attributes despite the large file sizes.

[0080] Eventually materials become attached to a product at the conceptual design phase and evolve with the product through the lifecycle according to modem digital twin and digital thread strategies. Keeping data up to date and synchronized across the many IT applications used by organizations throughout a lifecycle is extremely complex. Therefore, effective management of materials intelligence is essential to avoiding critical issues and data gaps in simulation, design and manufacturing planning and execution.

[0081] FIG. 2 is a schematic diagram of material information types according to an embodiment of the present application.

[0082] Multiple data sets are attached to materials. Engineers often focus on technical properties such as strength, toughness, or thermal response. To assemble and manage this data for a material is a difficult challenge requiring, for example, complex multi-dimensional mathematical models to describe properties for use in simulation. But, for a manufacturing enterprise to fully describe a material, it also requires data on many other factors, such as aesthetics, regulatory compliance, cost, environmental properties, suppliers, alternative grades, and application history. This data is typically generated in many different places, and managed (if it is managed at all) in varied systems.

[0083] FIG. 3 is a schematic diagram of multiple datasets of materials according to an embodiment of the present application.

[0084] The traditional set of mechanical and physical characteristics contained in reference hard / electronic databases does not allow for a long time to carry out high-quality complex computer aided engineering (CAE) calculations and modeling (1-D CAE, finite element analysis (FEA), computational fluid dynamics (CFD), electromagnetic analysis (EMA), etc.), especially since in most use cases, materials at different enterprises can have specific processing (for example, thermal or mechanical), be obtained from blanks other than standard specifications, etc. for which qualifications procedures are required. The qualification can be summarized as the collection of sufficient data to demonstrate that a material or process will function as expected. Extensive empirical testing to fully qualify a material often requires many thousands of individual tests, costing millions of dollars and 5 to 15 years to complete. Equally important is the need to integrate into the product data management (PDM) system of the enterprise the processes of collecting, storing and analyzing test data for materials, prototypes and the product as a whole and linking this data with CAE systems.

[0085] FIG. 4 is a schematic diagram of managing information in the context of a product lifecycle according to an embodiment of the present application.

[0086] In the context of product lifecycle management (PLM), materials information management is a key component in ensuring the effective management and transfer of materials -related data during product design, manufacturing, and delivery. The following are the roles and interactions of each system in materials information management:

[0087] CAD : CAD systems are used for product design and model creation. In material information management, CAD can directly use material properties and characteristics provided by material data management systems to ensure proper material selection and design.

[0088] Material data management: The material data management system is used to store and manage material -related data, including material properties, characteristics, and supplier information. It provides accurate material data for CAD and CAE to ensure consistency and accuracy of material information used in the design and analysis process.

[0089] CAE: The CAE system is used for engineering analysis and simulation. It uses material properties andcharacteristics provided in the material data management system to analyze and simulate products in terms of structure, thermodynamics, and fluid mechanics.

[0090] Product lifecycle management (PLM): The PLM system is a comprehensive product lifecycle management platform for integrating and managing information throughout the entire process of product design, manufacturing, and service. PLM can receive data from material data management systems, CAD, and CAE, and integrate and manage these data to ensure consistency and traceability of material information at all stages.

[0091] Enterprise resource planning (ERP): ERP systems are used for planning and management of resources within an enterprise, including supply chain, inventory, production planning, and procurement. In terms of material information management, ERP interacts with PLM to obtain data such as product bill of materials, supplier information and costs to support the enterprise's procurement and supply chain management.

[0092] Manufacturing execution system (MBS): MBS systems are used to monitor and control the manufacturing process to ensure that products are produced according to plan. In material information management, MBS interacts with PLM to obtain data such as process routes, product specifications and material requirements to support production planning and inventory management.

[0093] FIG. 5 is a schematic diagram of a material data management architecture according to prior art.

[0094] In the context of PLM, materials management is the process of effectively managing materials-related data and information during product development and production. It involves the collaborative work of multiple systems and tools, including laboratory information management system (LIMS), materials management systems, product lifecycle management (PLM), master data management (MDM), computer aided engineering (CAE), computer aided design (CAD), and computer aided manufacturing (CAM). The following is a brief description of these concepts and how they relate to each other.

[0095] Laboratory information management system (LIMS): LIMS is a software system for managing laboratory samples, data and processes. In materials information management, LIMS can be used to record and track materials data for laboratory testing and analysis. It can manage sample information, experimental results, quality control and other data related to laboratory activities. LIMS typically includes master data management (MDM), application programming interface (API), and object storage subsystems. An MDM subsystem includes material management service, and an API subsystem includes data import service.

[0096] Materials management: a material data management system is a specialized system for materials-related data and information. It is used to store, organize, and manage material -related data such as material properties, characteristics, supplier information, and test data. A material data management system can be used as a data source for PLM, CAD, CAE and CAM. The materials management system includes data management subsystem, API subsystem, object storage service,relational database service, and data analysis service.

[0097] PLM is a methodology and system for managing the entire life cycle of a product from conceptual design to retirement. In materials information management, PLM can be used to integrate and coordinate materials-related data and information. It can track material usage, change management, supply chain information, etc. and interact data with material management systems. PLM typically includes MDM, API, data management, classification management, process management, change management, object storage subsystems, and also relational database subsystems.

[0098] MDM is a data management strategy and technology used to unify master data across an organization. In material information management, MDM can be used to manage material-related master data, such as material numbers, classifications, attributes, etc. MDM can be used for data synchronization and data transfer with material data management systems. MDM (custom) typically includes MDM subsystem, API subsystem, object storage subsystem, and relational database.

[0099] CAE is a method of using computer technology to assist in engineering analysis and design. In material information management, CAE can use material -related data for engineering analysis, such as material mechanical properties and thermal properties. It can interact with the material data management system to obtain the required material data. The CAE typically includes MDM, API, and object storage subsystems.

[0100] CAD is a method of product design using computer technology. In material information management, CAD can use material-related data for product design and modeling, such as material appearance, dimensions, and material. CAD can interact with the material data management system to obtain the required material properties and characteristics. The CAD typically includes MDM, API, and object storage subsystems.

[0101] CAM is a method of utilizing computer technology to assist in the manufacturing process. In material information management, CAM can use material -related data for planning and controlling the manufacturing process, such as material processing parameters, process specifications, etc. CAM can interact with the material data management system to obtain the required material information. The CAM typically includes MDM, API, and object storage subsystems.

[0102] Each domain in the IT landscape of the enterprise uses its own set of software and uses a specific set of data about the materials necessary for the effective operation of these systems. This scheme has the following key disadvantages:

[0103] (1) The lack of the possibility of organizing end-to-end processes regarding information about materials due to the fragmentation of systems.

[0104] (2) The fragmentation of stored knowledge about materials. Different software may have different values for the same material, or even the storage structure and names may not match.

[0105] (3) The relevance of data is difficult to track, which entails duplication of information, high complexity and laboriousness of keeping data up-to-date due to the large number of systems and the lack of two-way integration / interactionbetween systems.

[0106] (4) The highest labor intensity and complexity of implementing a material intelligence management system solution / software.

[0107] (5) Outdated deployment architectures for software solutions, such as for desktop systems (non-cloud) or web versions.

[0108] FIG. 6 is a schematic diagram of a material intelligence management process in a typical architecture according to prior art.

[0109] In a typical schema architecture, the material intelligence management process is shown in FIG. 6. At the same time, separate blocks of the process are implemented in each domain, and the interaction between domains and actors is performed either in manual or semi -automated mode, which implies complex customization. What is equally important is the fact that each domain is defined by its software, and the relationship therewith is only one-way.

[0110] The present application provides a technical solution to the problem of material intelligence management due to the lack of a suitable software architecture that enables an end-to-end process to be embedded into the processes of a PLM system.

[0111] FIG. 7 is a schematic diagram of a material management method according to an embodiment of the present application. The material management method is applied to a material management system.

[0112] 310, receiving first material data from a first system.

[0113] The first material data includes attribute information, where the first material data includes any one or more of reference data, test data, statistical data, simulation data, and design data.

[0114] The first system is any one of a LIMS, a MDM system, a CAE system, a CAD system, and a CAM system.

[0115] 320, determining a first entity data model corresponding to the first material data.

[0116] The first entity data model is configured to store the attribute information of the first material data by a predetermined format.

[0117] If there is no entity data model about the first material data in the material management system, an entity data model corresponding to the first material data will be created; or if there is an entity data model about the first material data in the material management system, the entity data model corresponding to the first material data will be updated.

[0118] 330, receiving a data request from a second system.

[0119] The data request is used for obtaining the attribute information of the first material data. The data request can include identifications of the first material data and the attribute information.

[0120] The second system is any one of a LIMS, an MDM system, a CAE system, a CAD system, and a CAM system.

[0121] 340, sending the attribute information of the first material data in the first entity data model to the second system according to the data request.

[0122] FIG. 8 is a schematic diagram of an architecture of material intelligence management software according to an embodiment of the present application.

[0123] The architectural scheme for managing knowledge about materials implies the use of a single platform based on a PLM system, in which it can be built as separate services and microservices. This is a unique difference between this scheme and the monolithic architecture of most existing materials management systems.

[0124] There are a variety of possible application scenarios for the material intelligence management architecture solution provided by this application, for example, importing data from different sources (test equipment, legacy software, and reference data), storing this data in a unified view, manipulating the data (creating, searching, reporting, etc.), processing the data (special math algorithms, integration with dedicated tools, etc.), exporting the data to third-party software (in particular, simulation software), and so on.

[0125] In the context of PLM, materials management is the process of effectively managing materials -related data and information during product development and production. It involves the collaborative work of multiple systems and tools, including LIMS, PLM, MDM, CAE, CAD, and CAM.

[0126] In embodiments of the present application, a PLM embedded with a material data management system provides a unified platform for intelligent data management of materials. It interacts with LIMS, MDM, CAE, CAD and CAM, supports the import of data from these systems into PLM, and stores and manages this data in a unified view. This ensures data consistency between different systems and provides the data needed for LIMS, MDM, CAE, CAD and CAM. By integrating a material data management system, PLM can provide more comprehensive, efficient and consistent material information management capabilities to support the optimization and coordination of product development and manufacturing processes.

[0127] The following is a brief description of these concepts and how they relate to each other:

[0128] LIMS is a software system for managing laboratory samples, data and processes. In materials information management, LIMS can be used to record and track materials data for laboratory testing and analysis. It can manage sample information, experimental results, quality control and other data related to laboratory activities. LIMS typically includes master data management (MDM), application programming interface (API), and object storage subsystems. An MDM subsystem includes material management service, and an API subsystem includes data import service.

[0129] PLM is a methodology and system for managing the entire life cycle of a product from conceptual design to retirement. In materials information management, PLM can be used to integrate and coordinate materials -related data and information. It can track material usage, change management, supply chain information, etc. and interact data with materialmanagement systems. PLM includes MDM cloud, API, data management, classification management, process management, object storage, user management, change management, SDK, task management subsystems, and also relational data and search services.

[0130] MDM is a data management strategy and technology used to unify master data across an organization. In material information management, MDM can be used to manage material -related master data, such as material numbers, classifications, attributes, etc. MDM (custom) typically includes MDM subsystem, API subsystem, object storage subsystem, and relational database.

[0131] CAE is a method of using computer technology to assist in engineering analysis and design. In material information management, CAE can use material -related data for engineering analysis, such as material mechanical properties and thermal properties. The CAE typically includes MDM, API, and object storage subsystems.

[0132] CAD is a method of product design using computer technology. In material information management, CAD can use material-related data for product design and modeling, such as material appearance, dimensions, material, etc. The CAD typically includes MDM, API, and object storage subsystems.

[0133] CAM is a method of utilizing computer technology to assist in the manufacturing process. In material information management, CAM can use material -related data for planning and controlling the manufacturing process, such as material processing parameters, process specifications, etc. The CAM typically includes MDM, API, and object storage subsystems.

[0134] The developed schema architecture based on separate services and microservices provides the ability to manage information about materials at each stage of the end-to-end process, and also provides a special data schema, process schema and classifiers.

[0135] The material data management system utilizes a cloud and multi -tenant deployment architecture with cloud and IDME as the basis for data management. This will certainly provide data security and flexibility during setting up of two-way integrations with application solutions.

[0136] FIG. 9 is a schematic diagram of an end-to-end process for intelligent management of materials according to an embodiment of the present application.

[0137] The intelligent material management system serves as one single unified system that integrates materials information from a variety of sources, including reference data from third-party sources and proprietary data. The proprietary data can be data from tests, statistically valid data, data for simulation analysts and designers, etc. By integrating these data, the system provides the most complete resource of material information.

[0138] The system provides specialized services for material scientists, including statistical data processing and dataimport. It satisfies the needs of different roles such as environmental control specialists, manufacturing engineers, procurement engineers, simulation analysts, materials managers, materials engineers and testing and quality assurance (QA) professionals.

[0139] The following are some of the specialized services that the system offers to material scientists.

[0140] Environmental control specialists can work in the field of environmental control as compliance bill of materials (BOM) analyzers and specify the regulation state (REACH).

[0141] Manufacturing engineers in the manufacturing field can request material information and assign materials.

[0142] Procurement engineers can handle material supply and approve materials in the procurement field.

[0143] Simulation analysts can perform the following tasks in the field of simulations and design: request material information, search material information, conduct intelligent searches, assign material in CAD, and process test data.

[0144] In the field of material management, material managers are responsible for tasks such as material management, managing material data schemes, inputting data, processing data, validating and publishing information, uploading reference data, conducting statistical analysis, utilizing artificial intelligence and machine learning, and applying material information.

[0145] In the field of self-made materials, material managers are involved in activities including material creation, requesting process parameters for material optimization using machine learning, inputting test material data, inputting training material data, algorithm evaluation, and prediction of material properties using models.

[0146] Testing and QA professionals perform a range of tasks in different domains: in the testing laboratory domain, their responsibilities include receiving test requests, conducting tests, uploading test results, and processing test data. In the qualify control domain, they are involved in uploading versions and verifying material batches. In the self-made materials domain, their tasks encompass material creation, requesting process parameters for material optimization using machine learning (ML), inputting test material data, inputting training material data, developing algorithms, conducting evaluations, and predicting material properties using models.

[0147] This material intelligence management system provides flexible material management, for example, a batch of material is associated with a series of tests for that batch, including, but not limited to, the source of the data, data generation, date, and the responsible specialist, which ensures the full traceability of the data. Users can easily find and manage data related to specific materials.

[0148] The system provides a unified set of auxiliary specialized services, including process management, task management, user management, search and so on. These functions help users to manage and perform tasks and operations related to material information.

[0149] The system utilizes a microservices architecture that simplifies the integration process with external systems. It reduces the complexify of integration and customization, making the system more flexible and scalable.

[0150] The use of machine learning and Al algorithms for end-to-end processes in this system is much more efficient and less labor intensive.

[0151] In summary, the materials management system provided in this application is a powerful software system for centralized management and tracking of data and information related to product materials. It provides the most complete material information resources, specialized services for material scientists and other related roles, and flexible material management and auxiliary specialized services capabilities.

[0152] The intelligent material management scheme provided in this application is compatible with the end-to-end processes of the current digital twin and digital thread trends for high tech products, as well as the ISO / IEC / IEEE 15288:2015 systems and software engineering - system lifecycle processes. ISO / IEC / IEEE 15288:2015 establishes a common framework of process descriptions for describing the life cycle of systems created by humans. It defines a set of processes and associated terminology from an engineering viewpoint. These processes canbe applied at any level in the hierarchy of a system's structure. Selected sets of these processes can be applied throughout the life cycle for managing and performing the stages of a system's life cycle. This is accomplished through the involvement of all stakeholders, with the ultimate goal of achieving customer satisfaction.

[0153] FIG. 10 is a schematic diagram of IDME according to an embodiment of the present application.

[0154] The data model-driven engine is the root of industrial data. The architectural diagram of the material management system provided in this application is the basis for the materials intelligence management cloud (MIM Cloud) software solution, which in turn is deployed on the IDME platform.

[0155] A comparison of the material management solution provided in this application with the prior art is listed in Table 2.Table 2

[0156] FIG. 11 is a schematic block diagram of a computing apparatus 600 according to an embodiment of the present application. As shown in FIG. 11, the computing apparatus 600 includes: a receiving module 610, a processing module 620, and a sending module 630. Optionally, it can also include an obtaining module 640.

[0157] The computing apparatus 600 implements the method as shown in FIG. 7 -FIG. 9. The computing apparatus 600 can be applied to cloud management platforms.

[0158] The receiving module 610 is configured to receive first material data from a first system.

[0159] The processing module 620 is configured to determine a first entity data model corresponding to the first material data, the first entity data model being configured to store attribute information of the first material data by a predetermined format.

[0160] The receiving module 610 is further configured to receive a data request from a second system, the data request being used for obtaining the attribute information of the first material data.

[0161] The sending module 630 is configured to send the attribute information of the first material data in the first entity data model to the second system according to the data request.

[0162] The first system or the second system is any one of a LIMS, a MDM system, a CAE system, a CAD system,and a CAM system.

[0163] Optionally, the processing module 620 is further configured to create the first entity data model corresponding to the first material data, or, update the first entity data model corresponding to the first material data.

[0164] Optionally, the data request includes identifications of the first material data and the attribute information.

[0165] The obtaining module 640 is configured to obtain the first entity data model by retrieving the first entity data model among multiple entity data models based on the data request, and the sending module 630 is further configured to send the attribute information of the first material data in the first entity data model to the second system.

[0166] Optionally, the material management system is applied in a PLM.

[0167] Optionally, the material management system is implemented by a microservices architecture.

[0168] Optionally, the attribute information of the first material data includes any one or more of reference data, test data, statistical data, simulation data, and design data.

[0169] FIG. 12 is a schematic diagram of an architecture of a computing device according to an embodiment of the present application. The computing device 1700 can be a server or a computer or other device with computing capabilities. The computing device 1700 shown in FIG. 12 includes: a processor 1720, a memory 1730, a transceiver 1740, and a bus 1710. The processor 1720, the memory 1730, and the transceiver 1740 are in communication with each other via the bus 1710. The computing device 1700 can be a server or a terminal device. The present application does not limit the number of processors, and memories in the computing device 1700.

[0170] The bus 1710 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. Buses can be categorized as address buses, databuses, control buses, etc. For ease of representation, only one line is used in FIG. 12, but it does not mean that there is only one bus or one type of bus. The bus 1710 may include pathways for transferring information between various components of the computing device 1700 (e.g., the memory 1730, the processor 1720, or the transceiver 1740).

[0171] The processor 1720 can include any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP) processor.

[0172] The memory 1730 can include volatile memory, such as random access memory (RAM). The processor 1720 can also include non-volatile memory, such as read-only memory (ROM), flash memory, a mechanical hard disk (HDD), or a solid state drive (SSD).

[0173] An executable program code is stored in the memory 1730, and the processor 1720 executes the executable program code to implement the functions of the aforementioned receiving module 610, the processing module 620, the sending module 630, and the obtaining module 640, respectively, so as to implement the material management method described in theabove embodiment. That is, the memory 1730 has instructions on it for executing the material management method described in the above embodiment.

[0174] The transceiver 1740 uses, for example, but not limited to, a transceiver module such as a network interface card, a transceiver, or the like, to enable communication between the computing device 1700 and other devices or communication networks.

[0175] The structure of the computing device 1700 enumerated above is only an exemplary illustration, and the present application is not limited thereto. The computing device 1700 of embodiments of the present application includes a variety of hardware found in computer systems in the prior art, e.g., the computing device 1700 also includes memory other than the memory 1730, such as, for example, a disk memory, and the like. It should be understood by those skilled in the art that the computing device 1700 can also include other devices necessary to achieve proper operation. In addition, depending on the specific needs, one of skill in the art should understand that the above-described computing device 1700 may also include other hardware devices for realizing other additional functions. In addition, one of skill in the art should understand that the abovedescribed computing device 1700 may also include only the devices necessary to realize the embodiments of the present application, and need not include all of the devices shown in FIG. 12.

[0176] FIG. 13 is a schematic diagram of an architecture of a computing device cluster according to an embodiment of the present application.

[0177] The computing device cluster includes at least one computing device. The computing device can be a server, such as a central server, an edge server, or a local server in a local data center. In some embodiments, the computing device can also be a terminal device such as a desktop computer, a laptop computer, or a smartphone.

[0178] As shown in FIG. 13, the cluster of computing devices described includes at least one computing device 1700. The memory 1730 in one or more of the computing devices 1700 in the cluster of computing devices can hold the same instructions for performing the material management method described in the above embodiment.

[0179] In some possible implementations, some of the instructions for performing the material management method described in the above embodiments can also be separately held in the memory 1730 of the one or more computing devices 1700 in the cluster of computing devices. In other words, a combination of the one or more computing devices 1700 canjointly execute instructions for performing the material management method described in the above embodiment.

[0180] It is noted that the memories 1730 in the different computing devices 1700 in the cluster of computing devices can store different instructions for performing some of the functions of the computing devices 1700, respectively. That is, the instructions stored in the memories 1730 in the different computing devices 1700 can realize the functions of one or more of the receiving module 610, the processing module 620, the sending module 630, and the obtaining module 640.

[0181] In some possible implementations, one or more computing devices in a cluster of computing devices can be connected via a network. Among other things, the network can be a wide area network or a local area network, etc. FIG. 14 illustrates one possible implementation. FIG. 14 is a schematic diagram of a connection between computing devices 1700A and 1700B over a network according to an embodiment of the present application. The two computing devices 1700A and 1700B are connected to each othervia a network. Specifically, the connection to said network is made through a communication interface in each computing device. In this class of possible implementations, the memory 1730 in the computing device 1700A holds instructions for performing the functions of the receiving module 610. At the same time, the memory 1730 in the computing device 1700B holds instructions for performing the functions of the processing module 620.

[0182] The connection between the clusters of computing devices shown in FIG. 14 can be such that, considering that the material management method provided in the present application requires collecting a large number of material data, it is contemplated that the functions realized by the receiving module 610 be performed by the computing device 1700B.

[0183] The functions of computing device 1700 A illustrated in FIG. 14 can also be accomplished by multiple computing devices 1700. Similarly, the functions of computing device 1700B can be accomplished by multiple computing devices 1700.

[0184] This embodiment also provides a computer program product comprising instructions. Said computer program product can be a software or program product containing instructions that can run on a cluster of computing devices or be stored in any available medium. When run by a cluster of computing devices, it causes the cluster of computing devices to perform the material management method provided above, or causes the cluster of computing devices to perform the functions of the computing apparatus 600 provided above.

[0185] In this embodiment, a computer-readable storage medium is also provided. The computer-readable storage medium can be any usable medium that a computing device can store or a data storage device such as a data center containing one or more usable media. The usable medium can be a magnetic medium (e.g., floppy disk, hard disk, and tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state drive). The computer-readable storage medium includes instructions that, when executed on the computing device, cause the computing device to perform the material management method provided above.

[0186] In this embodiment, a computer-readable storage medium is also provided. The computer-readable storage medium can be any usable medium that a computing device can store or a data storage device such as a data center containing one or more usable media. The usable medium can be a magnetic medium, (e.g., floppy disk, hard disk, and tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state drive). The computer-readable storage medium includes instructions that, when executed by the cluster of computing devices, cause the cluster of computing devices to perform the material management method provided above.

[0187] In various embodiments of the present application, the magnitude of the serial number of each of the above processes does not imply the order of execution, and the order of execution of each process shall be determined by its function and inherent logic without constituting any limitation of the process of implementation of the embodiments of the present application.

[0188] A person of ordinary skill in the art may be aware that, in combination with the examples described in the embodiments disclosed in this specification, units and algorithm steps can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are performed by hardware or software depends on particular applications and design constraints of the technical solutions. A person skilled in the art may use different methods to implement the described functions for each particular application, but it should not be considered that the implementation goes beyond the scope of this application.

[0189] It may be clearly understood by a person skilled in the art that, for the purpose of convenient and brief description, for a detailed working process of the foregoing system, apparatus, and unit, refer to a corresponding process in the foregoing method embodiment. Details are not described herein again.

[0190] In the several embodiments provided in this application, it should be understood that the disclosed system, apparatus, and method may be implemented in other manners. For example, the described apparatus embodiment is merely an example. For example, the unit division is merely logical function division and may be other division in actual implementation. For example, a plurality of units or components may be combined or integrated into another system, or some features may be ignored or not performed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections may be implemented through some interfaces. The indirect couplings or communication connections between the apparatuses or units may be implemented in electronic, mechanical, or other forms.

[0191] The units described as separate parts may be or may not be physically separate, and parts displayed as units may be or may not be physical units, may be located in one position, or may be distributed on a plurality of network units. Some or all of the units may be selected based on actual requirements to achieve the objectives of the solutions of the embodiments.

[0192] In addition, functional units in the embodiments of this application may be integrated into one processing unit, or each of the units may exist alone physically, or two or more units are integrated into one unit.

[0193] When the functions are implemented in a form of a software functional unit and sold or used as an independent product, the functions may be stored in a computer readable storage medium. Based on such an understanding, the technical solutions in this application essentially, or the part contributing to the prior art, or some of the technical solutions may be implemented in a form of a software product. The computer software product is stored in a storage medium, and includes several instructions for instructing a computer device (which may be a personal computer, a server, a network device, or thelike) to perform all or some of the steps of the methods described in the embodiments of this application. The foregoing storage medium includes: any medium that can store program code, such as a USB flash drive, a removable hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc.

[0194] The foregoing descriptions are merely specific implementations of this application, but are not intended to limit the protection scope of this application. Any variation or replacement readily figured out by a person skilled in the art within the technical scope disclosed in this application shall fall within the protection scope of this application. Therefore, the protection scope of this application shall be subject to the protection scope of the claims.

Claims

CLAIMSWhat is claimed is:

1. A material management method, applied to a material management system, comprising: receiving first material data from a first system; and determining a first entity data model corresponding to the first material data, the first entity data model being configured to store attribute information of the first material data by a predetermined format; and receiving a data request from a second system, the data request being used for obtaining the attribute information of the first material data; and sending the attribute information of the first material data in the first entity data model to the second system according to the data request.

2. The method according to claim 1, wherein the first system or the second system is any one of a laboratory information management system (LIMS), a master data management (MDM) system, a computer-aided engineering (CAE) system, a computer-aided design (CAD) system, and a computer-aided manufacturing (CAM) system.

3. The method according to claim 1 or 2, wherein the determining a first entity data model corresponding to the first material data comprises: creating the first entity data model corresponding to the first material data, or, updating the first entity data model corresponding to the first material data.

4. The method according to any one of claims 1 to 3, wherein the data request comprises identifications of the first material data and the attribute information.

5. The method according to any one of claims 1 to 4, wherein the sending the attribute information of the first material data in the first entity data model to the second system according to the data request comprises: obtaining the first entity data model by retrieving the first entity data model among multiple entity data models based on the data request; and sending the attribute information of the first material data in the first entity data model to the second system.

6. The method according to any one of claims 1 to 5, wherein the material management system is applied in a product lifecycle management (PLM).

7. The method according to any one of claims 1 to 6, wherein the material management system is implemented by a microservices architecture.

8. The method according to any one of claims 1 to 7, wherein the attribute information of the first material data comprises any one or more of reference data, test data, statistical data, simulation data, and design data.

9. A computing apparatus, applied to a material management system, comprising: a receiving module configured to receive first material data from a first system; and a processing module configured to determine a first entity data model corresponding to the first material data, the first entity data model being configured to store attribute information of the first material data by a predetermined format; wherein the receiving module is further configured to receive a data request from a second system, the data request being used for obtaining the attribute information of the first material data; and a sending module configured to send the attribute information of the first material data in the first entity data model to the second system according to the data request.

10. The computing apparatus according to claim 9, wherein the first system or the se cond system is any one of a laboratory information management system (LIMS), a master data management (MDM) system, a computer-aided engineering (CAE) system, a computer-aided design (CAD) system, and a computer-aided manufacturing (CAM) system.

11. The computing apparatus according to claim 9 or 10, wherein the processing module is further configured to create the first entity data model corresponding to the first material data, or, update the first entity data model corresponding to the first material data.

12. The computing apparatus according to any one of claims 9 to 11, wherein the data request comprises identifications of the first material data and the attribute information.

13. The computing apparatus according to any one of claims 9 to 12, wherein the computing apparatus further comprises an obtaining module configured to obtain the first entity data model by retrieving the first entity data model among multiple entity data models based on the data request; and the sending module is further configured to send the attribute information of the first material data in the first entity data model to the second system.

14. The computing apparatus according to any one of claims 9 to 13, wherein the material management system is applied in a product lifecycle management (PLM).

15. The computing apparatus according to any one of claims 9 to 14, wherein the material management system is implemented by a microservices architecture.

16. The computing apparatus according to any one of claims 9 to 15 , wherein the attribute information of the first material data comprises any one or more of reference data, test data, statistical data, simulation data, and design data.

17. A computing device cluster, comprising at least one computing device, wherein the computing device comprises aprocessor and a memory coupled with the processor, wherein the memory is configured to store a computer program, and the processor is configured to invoke and run the computer program stored in the memory, so that the computing device cluster executes the method according to any one of claims 1 to 8.

18. A computer readable storage medium storing instructions that, when run on a computing device cluster, enable the computing device cluster to perform the method according to any one of claims 1 to 8.

19. A computer program product, wherein when the computer program product is run on a computing device cluster, the computing device cluster is enabled to perform the method according to any one of claims 1 to 8.

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