WO2022198485A1 - Mapping device and system for relational data and map data for industrial software - Google Patents

Abstract

Provided in the present invention are a mapping device and system for relational data and map data for industrial software, the system comprising: a graph database, which stores map model templates and map model instances; a mapping module, which is coupled to the graph database and a relational database, wherein the mapping module acquires data from the relational database and imports the data into the graph database, so as to generate, on the basis of the map model templates, map model instances having entities and attributes thereof; a map database service device, which is coupled to industrial software and the graph database, wherein the map database service device receives commands from the industrial software, so as to execute operations of addition, deletion, change and query on the map model instances. By means of the present invention, conversion of a relational database and a map database can be implemented between industrial software, and knowledge acquisition and reuse can also be executed.

Description

Device and system for mapping relational data and graph data of industrial software technical field

The invention relates to the field of industrial digitization, in particular to a mapping device and system for relational data and map data of industrial software.

Background technique

Product lifecycle management (PLM, Product lifecycle management) software manages data from inception to production, maintenance, and processing of re-products. Companies utilize PLM software to increase productivity and collaboration to improve quality, long-term creativity, and shorten time-to-market to product. This is applied in various industrial processes to help integrate data and documents, business systems, and people involved in the production process of a product, which allows the introduction of the above to systematically track all changes in a product's production process. Typical PLM software usually uses a reasonable database, such as Oracle database.

Software platforms standardize the way business data and processes are related to each other by defining data in profiles within the software itself and in the database. Among them, a data model is a structured, hierarchical organization of abstract objects intended to represent business data. A data model represents a part of the design involving documents and the relationships between the two, as well as the business processes that apply to them. The schemas define the relevant data, including the definition of the data model.

Figure 1 is a relationship diagram of enterprise R&D, production planning, and production execution in the prior art. As shown in the figure, in the prior art, the product life cycle management software 110 is the R&D end, the production execution system 120 is the production end, the enterprise resource planning system 130 is the production planning end, and the production execution system 120 is connected to the automated workshop 140 . Among them, the product life cycle management software 110, the production execution system 120 and the enterprise resource planning system 130 all have their own databases, and complex customization of the data is required between the three to get through. Therefore, based on the data shown in FIG. 1 Architecture The product life cycle management software 110 , the production execution system 120 and the enterprise resource planning system 130 cannot directly apply data to each other.

The problem of using relational databases in the prior art is that due to changes in commercial applications, frequent customized development is required. In a relational database, data is stored in tables using rigid structures with predefined summaries. These tables have fixed properties, called fields, which have characteristics such as data types and constraints. If customer demand changes, it needs a profile change to accommodate consumer demand. Not to mention the intensity of customization work when a software platform product is deployed to a new customer.

The problem with using relational databases is also that the query performance and efficiency are low. A profile is a logical data graph of a relational database. In a reasonable data storage model, there is no physical connection to specify the relationship between different data records, it is only logically linked by a specific attribute (foreign key), and the rendering and retrieval of related records requires a lookup of the entire target table. As there are more target tables, the efficiency will become very low.

The problem with using relational databases is also the lack of knowledge accumulation and reuse. In a software platform, product designs, processes, resources (people, machines, materials) and suppliers are stored in relational databases. As the scale of data increases, only the number of facts is accumulating, while for highly interconnected data how to discover hidden connections or trends in the data is not resolved, so no logical and related knowledge is discovered and accumulated. For knowledge taking, the main goal is to reduce the operational work of engineers and improve the quality of their work. However, it is difficult to implement knowledge taking function in relational database. On the one hand, it is also difficult for a relational database to recommend secondary operations or related data for engineers based on a large amount of historical data. Therefore, as mentioned above, the query speed will be very low, not to mention providing any function of performing real-time recommendations based on AI measurements. On the other hand, this approach also does not take advantage of an efficient way of applying rule-based reasoning to reuse expertise.

The problem with using relational databases is also to achieve a closed-loop connection between the production execution system (MES) and the enterprise resource planning system (ERP). Specific middleware needs to be developed for system integration into enterprise resource planning systems or production execution systems, eg Windchill integrates into SAP using TIBCO as middleware. For example, a software platform utilizes a gateway solution to integrate the software of the software platform with other product information systems and business processes throughout the company, which includes multiple gateways of various software. Closed loop manufacturing of software solutions for software platforms provides a wide range of automated exchange and workflow capabilities to execute semantics between software platforms and Semantic IT Unified Architecture Discrete Manufacturing (UADM). Transfer and sync data.

The disadvantage of the prior art is that these middleware and gateway solutions are buried in specific EPR and MES systems from specific vendors. If the application scenario does not include the application scenario of SAP or Oracle, the gateway solution needs to be customized accordingly, which requires a lot of time and effort. Additionally, due to integration with vendor-specific systems, additional efforts are required to ensure that the software platform gateway solution remains up-to-date with the latest software release.

For example, the software platform provides the Business Modeling Module IDE (BMIDE) to extend the default data model objects, generate customer data model objects and store them in a template. But this approach requires labor costs to define data model goals regardless of business application changes.

SUMMARY OF THE INVENTION

A first aspect of the present invention provides a mapping device for relational data and graph data of industrial software, which includes: a graph database, which stores graph model templates and graph model instances; a mapping module, which is coupled to the graph database and graph model instances; In the relational database, the mapping module obtains data from the relational database and imports it into the graph database to generate a graph model instance with entities and their attributes based on the graph model template; a graph database service device, It is coupled to the industrial software and the graph database, and the graph database service device receives commands from the industrial software to perform add, delete, change, and query operations on the graph model instance.

Further, the industrial software includes product life cycle management software, production execution system and enterprise resource planning system.

Further, the graph model template and the graph model instance are product-centric, wherein the entities in the graph model template and the graph model instance are used to describe the product.

Further, the entities include entities of production, planning and production of products.

Further, the graph database is a marker attribute graph or a resource description structure type.

A second aspect of the present invention provides a mapping system for relational data and graph data of industrial software, wherein the industrial software includes product life cycle management software, a production execution system and an enterprise resource planning system, characterized in that the industrial software The mapping system of the relational data and the graph data includes: a graph database, which stores graph model templates and graph model instances; a mapping module, which is coupled to the graph database and the relational database, and the mapping template from all Obtain data from the relational database and import it into the graph database to generate graph model instances with entities and their attributes based on the graph model template; graph database service means, which are coupled to the graph database and are respectively coupled to the graph database. The product life cycle management software, the production execution system and the enterprise resource planning system, the graph database service device receives commands from the industrial software to perform add, delete, change, and query operations on the graph model instance.

Further, the graph model template and the graph model instance are product-centric, wherein the entities in the graph model template and the graph model instance are used to describe the product.

Further, the entities include entities of production, planning and production of products.

A third aspect of the present invention provides a method for mapping relational data and graph data of industrial software, wherein the mapping method includes the steps of: acquiring data from a relational database, and importing it into the graph database to generate a graph with a graph based on a graph model template. Graph model instances of entities and their attributes, and store the graph model templates and graph model instances in a graph database; receive commands from the industrial software to perform add, delete, change, and query operations on the graph model instances.

A fourth aspect of the present invention provides an electronic device comprising: a processor; and a memory coupled to the processor, the memory having instructions stored therein that, when executed by the processor, cause the electronic device to execute The actions include: acquiring data from a relational database and importing it into a graph database to generate a graph model instance with entities and their attributes based on the graph model template, and storing the graph model template and graph model instance in the graph database; receive commands from the industrial software to perform add, delete, change, and query operations on the graph model instance.

A fifth aspect of the present invention provides a computer program product tangibly stored on a computer-readable medium and comprising computer-executable instructions that, when executed, cause at least one processor to perform a The method described in the third aspect of the present invention.

A sixth aspect of the present invention provides a computer readable medium having computer executable instructions stored thereon which, when executed, cause at least one processor to perform the method according to the third aspect of the present invention.

The present invention can adapt to different industrial standards, and enables the product life cycle management software to be converted from a relational database to a graph-based database. The present invention can make the product life cycle management software more intelligent, and can make full use of the advantages of the graph database, such as more natural and clear description for highly interconnected data, and better data storage and editing performance, and it is easy to add AI. Algorithms to improve business or engineering applications.

Description of drawings

Fig. 1 is the relational structure diagram of enterprise R&D, production planning and production execution of the prior art;

2 is a schematic structural diagram of an apparatus for mapping relational data and graph data of industrial software according to a specific embodiment of the present invention;

3 is a schematic diagram of a graph model according to a specific embodiment of the present invention;

4 is a data table in a relational database according to a specific embodiment of the present invention;

Fig. 5 is a schematic diagram of a map example after execution mapping and expansion according to a specific embodiment of the present invention;

6 is a schematic diagram of an artificial intelligence and artificial cooperative research and development process based on a graph database according to a specific embodiment of the present invention;

Fig. 7 is according to a specific embodiment of the present invention

Detailed ways

The specific embodiments of the present invention will be described below with reference to the accompanying drawings.

The present invention utilizes an ontology based on product life cycle management software product centralization to perform knowledge acquisition and reuse as well as facilitate system and a production environment interconnectivity. Among them, the present invention sets a graph database.

FIG. 2 is a schematic structural diagram of an apparatus for mapping relational data and graph data of industrial software according to a specific embodiment of the present invention. As shown in FIG. 2, a first aspect of the present invention provides an apparatus 200 for mapping relational data and graph data of industrial software, wherein the mapping apparatus 200 includes a graph database 220, a mapping module 230 and a graph database Service device 240 . The graph database 220 stores graph model templates and graph model instances. The mapping module 230 is coupled to the graph database 220 and the relational database 300, and the mapping module 230 obtains data from the relational database 300 and imports it into the graph database 220 to generate based on the graph model template A graph model instance with entities and their properties. The graph database service device 240 is coupled to the industrial software and the graph database 220, and the graph database service device 240 receives commands from the industrial software to perform add, delete, change, and query operations on the graph model instance. Wherein, in the embodiment shown in FIG. 2 , the industrial software is product life cycle management software PLM.

Further, the industrial software includes product life cycle management software, production execution system and enterprise resource planning system.

As shown in Figure ₃ , the graph model M1 includes the following key objects: employees, orders, shippers, products, catalogs, suppliers, equipment, and processes. The relationship between the above key objects is: the employee initiates the order, the shipper sends the order, the order includes the product, the product is included in the catalog, the supplier provides the product, the device produces the product, the device supports the process, and the product has a process. Preferably, the atlas template is product-centric.

FIG. 4 is a data table T in a relational database according to a specific embodiment of the present invention. As shown in FIG. 4 , the data table T includes entities and their attributes. The entities include employees, orders, customers, products, and shippers. Among them, the attributes of employees include employee number, reporting line, name and region, the attributes of orders include order number, customer name, employee number and product number, the attributes of customers include customer name, company name, contact name and region, product The attributes include the product number and the name of the shipper, and the attributes of the shipper include the name of the shipper, the company name, the attribute name and the region. The same attributes are connected together by foreign key PK, which refers to the key attribute of the entity. Among them, the relational database includes many such data tables, the following attributes are each column, entities and attributes are not together, and are scattered in the form of tables, which are connected and referenced by key values. Preferably, the relational database used by the product life cycle management software is usually an Oracle database

Specifically, the mapping module 230 has two functions of target mapping and data migration. _The target mapping function refers to identifying and extracting data entity types, and mapping entities and attributes to the graph template M1, which is the metadata ontology model _of the graph template M1. Specifically, entities are mapped to types, properties are mapped to properties, and foreign key PKs are mapped to target properties. For entities and attributes that do not have mapping objects in the ontology model, it is only necessary to extend the ontology model accordingly, which is the evolutionary feature of the metadata model. The data migration function refers to exporting data from the relational database as shown in FIG. 4 , and then instantiating the data into the graph database 220 based on the mapping relationship. Among them, the entity mapping to the graph database is the type, the attribute mapping to the graph database is the data feature, and the foreign key mapping to the graph database is the target feature.

FIG. 5 is a schematic diagram of an example of a map after performing mapping and expansion according to a specific embodiment of the present invention. Wherein, the graph instance _M2 is obtained based _on the graph template M1 and after the mapping module 230 executes the mapping. As shown in Figure 5, on the basis of Figure 2, the attributes of the entity and their real values are imported. Among them, the order number and customer name are imported under the entity order, the product number is imported under the product, and the supplier is imported. Supplier name and company name.

Preferably, the graph database is a Labeled Property Graph (LPG, Labeled Property Graph) or a Resource Description Frame (RDF, Resource Description Frame). The product-centric metadata model is embedded in the graph database, which is based on ISO 10303 STEP/PDM and IEC 62264 B2MML standards. The ISO 10303 STEP/PDM standard is used as a reference for product technical data, and the IEC 62264 B2MML is used as a reference for conceptualized production execution system and enterprise resource planning system related data.

Preferably, the graph model template and the graph model instance are product-centric, wherein the entities in the graph model template and the graph model instance are for describing the product. Among them, the entity includes the entity of production, planning and production of the product.

The graph database service device 240 receives commands from the industrial software to perform add, delete, change, and query operations on the graph model instance. Therefore, the application of the product life cycle management software PLM can interact with the data of the graph database 220 . For example, as shown in FIG. 5, the graph instance _M2 is obtained based _on the graph template M1 and after the mapping module 230 executes the mapping, the graph instance _M2 adds the entity "customer" _on the basis of the graph template M1, and is in the graph template M1. The attribute "customer number" and its attribute value are added under the entity "customer". Among them, the relationship between products and customers is "selling products to customers".

The present invention also increases the graph scale for knowledge aggregation and reuse. Besides knowledge aggregation, graph-based algorithms such as relation discovery and path finding such as hidden and explicit connections. Aggregated historical data points can be used to make recommendations to help engineers perform product or process design on a software-centric platform. As shown in Figure 6, the artificial intelligence algorithm is based on the graph database and manpower in the design of bill of materials (EBOM, Engineering Bill of Material), manufacturing bill of materials (MBOM, Manufacturing Bill of Material), product process list (product BOP, Bill of Process) Cooperate with the plant BOP (Bill of Process) generation process, and recommend auxiliary materials, manufacturing processes, resources and perform data consistency checks. The algorithm-related relationship discovery of the present invention can facilitate product quality analysis, which can display all materials, labor, and equipment related to the product process, so that the scope of analysis of quality problems can be reduced. The intelligent functions described above can perform relational discovery, and these data are linked to each other. For example, the products with quality problems in the production environment, the equipment that the product and its related people pass through, and the relationship with him can be found out, and the quality problem analysis is performed based on Figure 6.

For cross-system interoperability, since the metadata model is defined from ISO 10303 STEP PDM and IEC 62264 B2MML, it is compatible with data model objectives designed in commercial production execution systems and enterprise resource planning systems.

As shown in FIG. 6, using the present invention, different engineers in the product design, production and planning process perform editing on the graph model in the graph database, and the present invention can provide recommendation functions in the process. Wherein, starting from the product model P, the present invention can automatically extract the data of its entities and attributes and the specific values of the attributes and generate the atlas model template M ₃₁ based on the atlas template, and the product engineer E ₁ can perform editing on the basis of the atlas model template M ₃₁ , generating an entity-added graph instance M ₃₂ . The manufacturing engineer E ₂ can perform editing on the basis of the map instance M ₃₃ and add entity extensions to generate M ₃₄ on this basis. The process is that E ₃ can perform editing on the basis of the map instance M ₃₅ and delete and change entities to generate The map instance M ₃₆ , and finally the manufacturing engineer E ₄ performs editing on the basis of the map instance M ₃₇ and then generates the final map instance and provides it to the factory for production. As shown in FIG. 6 , the above-mentioned engineers all perform editing on the graph models and instances in the graph database 200 in conjunction with the AI service device.

The above entity properties are edited in full, or nodes are provided. The human-computer interaction method is very beneficial to recommend through AI, and engineers only need to modify the recommendation function slightly, or only perform confirmation. There are product engineers, manufacturing engineers, process engineers, etc. in the product-related process. Using the present invention not only improves database performance, but also develops intelligent recommendation functions in the collaborative process of the above-mentioned roles. Therefore, the present invention has better performance, less customization, and more intelligence.

A second aspect of the present invention provides a mapping system 500 for relational data and graph data of industrial software, wherein the industrial software includes product life cycle management software PLM, production execution system (EMS) and enterprise resource planning system (ERP), It is characterized in that the mapping system of relational data and graph data of the industrial software includes a graph database 220, a mapping module 230 and a graph database service device. The graph database 220 stores graph model templates and graph model instances. The mapping module 230 is coupled to the graph database and the relational database. The mapping template obtains data from the relational database and imports the data from the relational database. In the graph database, a graph model instance with entities and their attributes is generated based on the graph model template. a graph database service device, which is coupled to the graph database and is respectively coupled to the product life cycle management software, the production execution system and the enterprise resource planning system, the graph database service device receives commands from the industrial software To perform add, delete, change, and query operations on the graph model instance.

Further, the graph model template and the graph model instance are product-centric, wherein the entities in the graph model template and the graph model instance are used to describe the product.

Further the entities include entities that manufacture, plan and produce products.

A third aspect of the present invention provides a method for mapping relational data and graph data of industrial software, wherein the mapping method includes the steps of: acquiring data from a relational database, and importing it into the graph database to generate a graph with a graph based on a graph model template. Graph model instances of entities and their attributes, and store the graph model templates and graph model instances in a graph database; receive commands from the industrial software to perform add, delete, change, and query operations on the graph model instances.

A fourth aspect of the present invention provides an electronic device comprising: a processor; and a memory coupled to the processor, the memory having instructions stored therein that, when executed by the processor, cause the electronic device to execute The actions include: acquiring data from a relational database and importing it into a graph database to generate a graph model instance with entities and their attributes based on the graph model template, and storing the graph model template and graph model instance in the graph database; receive commands from the industrial software to perform add, delete, change, and query operations on the graph model instance.

A fifth aspect of the present invention provides a computer program product tangibly stored on a computer-readable medium and comprising computer-executable instructions that, when executed, cause at least one processor to perform a The method described in the third aspect of the present invention.

A sixth aspect of the present invention provides a computer readable medium having computer executable instructions stored thereon which, when executed, cause at least one processor to perform the method according to the third aspect of the present invention.

In response to the problems of frequent customization and poor performance of the prior art, the present invention provides a self-evolving graph data architecture, which is modeled with data objects in the production domain, including product design, process, manufacturing resources, suppliers, sales quotient and their relationship to each other. Wherein, the manufacturing resources include manpower, equipment and materials. Graphs allow data to be presented symbolically and are easier and more natural to understand than tables of numerical data.

The graph database provided by the present invention is embedded in a product-centered metadata ontology model. Atlas databases do not have any fixed schema. To be precise, any pattern is a simple reflection of the incoming data. Once the various data comes in, the schema grows or evolves accordingly. Even as datasets grow, the performance of graph databases tends to remain relatively constant. This is because the query is targeted to a part of the graph. Therefore, the execution time of each query is only proportional to the size of the part of the graph that satisfies the covered query, not the size of the entire data.

Because the product-centric data model is self-evolving, developers of product lifecycle management software do not need to update the software-centric gateway solution for the production execution system or enterprise resource planning system to update when the production execution system or enterprise resource planning system is updated to the latest date.

The present invention follows product and production-related industrial standards, and enables product life cycle management software to be converted from a relational database to a graph-based database. The present invention can make the product life cycle management software more intelligent, and can make full use of the advantages of the graph database, such as more natural and clear description for highly interconnected data, and better data storage and editing performance, and it is easy to add AI. Algorithms to improve business or engineering applications.

While the content of the present invention has been described in detail by way of the above preferred embodiments, it should be appreciated that the above description should not be construed as limiting the present invention. Various modifications and alternatives to the present invention will be apparent to those skilled in the art upon reading the foregoing. Accordingly, the scope of protection of the present invention should be defined by the appended claims. Furthermore, any reference signs in a claim shall not be construed as limiting the claim involved; the word "comprising" does not exclude other claims or means or steps not listed in the specification; Words such as "two" are used only to denote names and do not denote any particular order.

Claims (12)

1. A device for mapping relational data and graph data for industrial software, including:

   A graph database, which stores graph model templates and graph model instances;

   A mapping module is coupled to the graph database and the relational database, and the mapping module obtains data from the relational database and imports it into the graph database to generate entities and their entities based on the graph model template. The graph model instance of the attribute;

   A graph database service device, which is coupled to the industrial software and the graph database, the graph database service device receives commands from the industrial software to perform add, delete, change, and query operations on the graph model instance.
2. The apparatus for mapping relational data and graph data of industrial software according to claim 1, wherein the industrial software includes product life cycle management software, production execution system and enterprise resource planning system.
3. The apparatus for mapping relational data and graph data of industrial software according to claim 1, wherein the graph model template and the graph model instance are product-centric, wherein the graph model Templates and entities in the graph model instance are used to describe the product.
4. The apparatus for mapping relational data and graph data of industrial software according to claim 3, wherein the entities include entities of production, planning and production of products.
5. The apparatus for mapping relational data and graph data of industrial software according to claim 1, wherein the graph database is a tag attribute graph or a resource description structure type.
6. A mapping system for relational data and graph data of industrial software, wherein the industrial software includes product life cycle management software, a production execution system and an enterprise resource planning system, characterized in that the relational data and graph data of the industrial software The mapping system includes:

   A graph database, which stores graph model templates and graph model instances;

   A mapping module is coupled to the graph database and the relational database, and the mapping template obtains data from the relational database and imports it into the graph database to generate entities and their associated entities based on the graph model template. The graph model instance of the attribute;

   a graph database service device, which is coupled to the graph database and is respectively coupled to the product life cycle management software, the production execution system and the enterprise resource planning system, the graph database service device receives commands from the industrial software To perform add, delete, change, and query operations on the graph model instance.
7. The system for mapping relational data and graph data for industrial software according to claim 6, wherein the graph model template and the graph model instance are product-centric, wherein the graph model Templates and entities in the graph model instance are used to describe the product.
8. The apparatus for mapping relational data and graph data of industrial software according to claim 6, wherein the entities include entities of production, planning and production of products.
9. A mapping method for relational data and map data of industrial software, wherein the mapping method comprises the following steps:

   Obtain data from a relational database and import it into a graph database to generate a graph model instance with entities and their attributes based on the graph model template, and store the graph model template and the graph model instance in the graph database;

   Commands from the industrial software are received to perform add, delete, change, and query operations on the graph model instance.
10. Electronic equipment, including:

    processor; and

    a memory coupled to the processor, the memory having stored therein instructions that, when executed by the processor, cause the electronic device to perform actions, the actions comprising:

    Obtain data from a relational database and import it into a graph database to generate a graph model instance with entities and their attributes based on the graph model template, and store the graph model template and the graph model instance in the graph database;

    Commands from the industrial software are received to perform add, delete, change, and query operations on the graph model instance.
11. A computer program product tangibly stored on a computer-readable medium and comprising computer-executable instructions that, when executed, cause at least one processor to perform the method of claim 9 .
12. A computer-readable medium having stored thereon computer-executable instructions that, when executed, cause at least one processor to perform the method of claim 9 .

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