Resource model structured database construction method of complex equipment large-scale production line

Abstract

The invention belongs to the technical field of process knowledge management, and particularly relates to a resource model structured database construction method of a complex equipment large-scale production line. The specific process is as follows: product information modeling: modeling product information into three levels of product classification, product series and product instances; complex equipment manufacturing resource information modeling: establishing a process resource information base for each manufacturing process, and storing four types of knowledge, namely process data, tool knowledge, auxiliary tools and process equipment in the process of processing; modeling the process ontology information of the complex equipment, wherein the process ontology information comprises process composition information and process requirement information, and during modeling, establishing a composition relationship between the process composition information, a hierarchical relationship between the process requirement information and an association relationship between the process composition information and the process requirement information; and process resource database management module establishment: the process resource database management module establishes process resource model management and process resource object management.

Description

Technical Field

[0001] The present invention belongs to the technical field of process knowledge management, and specifically relates to a method for constructing a structured database of a resource model for a large-scale production line of complex equipment. Background Art

[0002] The traditional research and development model oriented towards equipment quality and performance has resulted in problems such as high equipment costs, difficulty in increasing production scale, low production efficiency and insufficient production capacity. It is difficult to cope with the supply needs of complex equipment for high-intensity and high-intensity continuous work in the future. In order to cope with the growing demand for production efficiency and cost control, a low-cost, high-efficiency process technology with general industrial scale characteristics is needed in production and manufacturing.

[0003] Data information is increasingly used in enterprises. By processing this data information, enterprises can conduct in-depth analysis and find the knowledge hidden behind the data, which plays a great role in guiding the decision-making of enterprises and can also improve the production efficiency of enterprises. Therefore, in order to improve the ability of knowledge innovation, it is necessary to master data information processing technology. The knowledge storage and classification of the required information is a prerequisite for intelligent management of various information.

[0004] In the management system, information and data are the main sources of organizational and personal knowledge. By integrating information and data, a shareable and searchable knowledge warehouse is constructed, and relevant tools and technologies are used to effectively manage and utilize knowledge, thus forming a management system. The construction of this system can provide enterprises with a complete knowledge management platform, and the analysis tools of the knowledge management system can be used to analyze and summarize the data of the enterprise, and then the data generated in the production activities of the enterprise can be more deeply mined, and the data can be classified and summarized accordingly, providing enterprises with more accurate, complete and efficient data.

[0005] At present, in the field of process knowledge management, the existing general technology is based on specific process resources to establish its knowledge system and conduct knowledge management. The data to be managed is classified, and after the classification is completed, the data is sorted according to the goals and principles of digital resource construction. Through the analysis of the domain knowledge of various process resources, the knowledge attributes of various process resources are determined, and the corresponding domain ontology model is established using ontology technology, so that process resources can be managed visually according to domain knowledge, which enhances the user's search experience and efficiency to a certain extent.

[0006] 1) Insufficient depth of knowledge model: The existing technology is too simplistic in the classification of product structure information, making it difficult to adapt to the increasingly complex changes in product structure. In particular, it lacks detailed process requirements and parameter configurations at the product instance level.

[0007] 2) Limited ability to optimize resource allocation: Existing technologies lack the ability to conduct in-depth analysis and optimize the allocation of process resources, and are unable to maximize resource utilization.

[0008] 3) The model is not targeted enough: Although the existing technology has established a knowledge system and ontology model, it is not deep enough to support process design activities and cannot quickly retrieve and match the knowledge required to generate manufacturing solutions. Summary of the invention

[0009] In view of the problem that the process information database is difficult to construct due to the complex product structure, wide variety of parts and components, and multiple and complex process schemes of existing complex equipment, the present invention proposes a resource model structured database construction method based on low-cost complex equipment large-scale production lines to achieve efficient construction of the process information database.

[0010] The technical solution for implementing the present invention is as follows:

[0011] A method for constructing a structured database of a resource model for a large-scale production line of complex equipment, the specific process is as follows:

[0012] Step 1: Product information modeling:

[0013] Model product information into three levels: product category, product series and product instance. Product series is subordinate to product category, and product instance is subordinate to product series.

[0014] Step 2: Complex equipment manufacturing resource information modeling:

[0015] For each manufacturing process, a process resource information database is established, which mainly stores four categories of knowledge: process data, tooling knowledge, auxiliary tooling and process equipment in the process of process processing;

[0016] Step 3: Modeling of complex equipment process information:

[0017] The process ontology information includes process composition information and process requirement information. When modeling, it also includes establishing the composition relationship between process composition information, the top-down hierarchical relationship between process requirement information, and the association relationship between process composition information and process requirement information.

[0018] Step 4: Build the process resource database management module:

[0019] The process resource database management module establishes process resource model management and process resource object management.

[0020] Furthermore, the step 1 of the present invention includes product classification modeling, product series modeling and product instance modeling, wherein:

[0021] Product classification modeling: complex equipment products are classified according to similarities in selected dimensions, forming a product classification method with clear structure and clear boundaries;

[0022] Product series modeling: Group products with similar product elements into a product series. The product elements include: function, structure and process;

[0023] Product instance modeling: The product BOM material list, technical requirements and product parts technical characteristics are used as features of the product instance model, where the product BOM contains all necessary raw materials and components, including their models, quantities and sources; the technical requirements contain performance standards and test conditions; the product parts technical characteristics provide detailed size, shape and material properties of each component.

[0024] Furthermore, the step 2 of the present invention includes: process data modeling, auxiliary tooling modeling, process knowledge modeling and equipment resource modeling;

[0025] Process data modeling: classify process data according to its type and purpose, and define a unified data model for each type of data. During the modeling process, define multiple key attributes, data sources and validity for the process data;

[0026] Auxiliary tooling modeling: First, identify and classify the various tools and equipment used in the manufacturing process, and determine the functions and application scenarios of each type of tooling; second, establish a detailed classification system to group the tooling according to its function, purpose and design standards; third, define a series of key attributes for auxiliary tooling to comprehensively describe its characteristics and application conditions.

[0027] Process knowledge modeling: The process knowledge is summarized into three types: process decision knowledge, process instance knowledge, and auxiliary process resources. In the process of process knowledge modeling, the expert experience, factual knowledge, and procedural knowledge accumulated in the process of process design are systematically organized and digitally expressed.

[0028] Equipment resource modeling: The model not only contains the basic information of the equipment, but also covers the equipment's operating status, capability parameters and remarks.

[0029] Furthermore, the step three of the present invention includes: modeling of process composition information and process requirement information;

[0030] Process component information modeling includes process step information modeling, process attribute information modeling and process route information modeling;

[0031] Process requirement information modeling includes process attribute feature representation, process parameter feature representation and process ontology information representation.

[0032] Furthermore, the process resource database management module of the present invention includes: a database storage tool, a complex equipment product resource management module, a complex equipment manufacturing resource management module and a complex equipment process information management module.

[0033] Furthermore, the complex equipment product resource management module of the present invention is used for product classification management, product series management and product specification management;

[0034] Product classification management uses a tree structure to divide the products of manufacturing companies based on macro characteristics, and is used for the basic functions of adding, deleting, modifying, and checking classification tree nodes.

[0035] Product series management includes: establishing a product attribute library and parameter library that describe product features, configuring attributes and parameters for product series, assigning values ​​to product parameters included in the product series, and forming product specification information that contains complete product feature descriptions;

[0036] Product specification management uses ER diagrams to represent the data relationships between concepts. Entity relationship diagrams can be converted into relational models through a formulaic method to establish tables in relational databases.

[0037] Furthermore, the complex equipment manufacturing resource management module of the present invention includes three levels: resource classification, resource series and manufacturing resource instance, which are used for manufacturing resource classification management, manufacturing resource series management and manufacturing resource specification management;

[0038] Manufacturing resource classification management uses a tree structure to divide the products of manufacturing enterprises based on macro characteristics. The functional logic includes adding, deleting, modifying and checking classification tree nodes.

[0039] The establishment elements of the manufacturing resource series correspond to the model, including the series name, series category, and series description. A resource attribute library and parameter library that describe product characteristics are established to configure attributes and parameters for the resource series.

[0040] The resource parameters included in the manufacturing resource specification management are assigned values ​​to form resource specification information containing a complete resource feature description.

[0041] Furthermore, the complex equipment process information management module of the present invention realizes the establishment and integrated application functions of process composition information and process requirement information related models, including process step management, process management, process route management and process requirement management submodules;

[0042] In the process requirement management submodule, process requirements are divided into two categories: target requirements and operation requirements. The process requirements are associated with which type of process component information, and the process requirements under the associated relationship represent the requirements of the corresponding level. During the configuration process, it is specified whether each process requirement is displayed in the final process design result;

[0043] The work step management submodule includes the creation and maintenance of work steps, and the configuration management functions of work steps and work step requirements;

[0044] The process management submodule adds a process classification function based on the process content, so that the processes can be classified and managed according to needs;

[0045] The functions of the process route management submodule are basically the same as those of the process management submodule, except that there is no classification and manufacturing resource allocation.

[0046] Furthermore, the present invention also includes database updating, and the specific process is as follows:

[0047] First, various parameters on the real-time monitoring production line equipment are sent to the database system in the form of streams;

[0048] Secondly, the data stream is processed to convert the corresponding data changes into feature changes in the manufacturing resource model and written into the database. By monitoring data change events, specific events or data patterns are identified and responded to, and corresponding update operations are taken immediately when events occur, thereby achieving real-time updates.

[0049] Thirdly, after receiving the update request, the database management system will detect the parent category of the update feature and handle multiple simultaneous update operations through the concurrency control mechanism;

[0050] Finally, after the data is successfully written to the database, the data backup and recovery strategy is further updated.

[0051] In the second aspect, the embodiment of the present application provides a process design method based on a resource model structured database of a low-cost complex equipment large-scale production line, and the specific process is as follows:

[0052] (1) For the production and manufacturing of a specific product, obtain the bill of materials characteristics and parts characteristics of the product instance based on the product classification information, and list the manufacturing solution requirements;

[0053] (2) Based on the manufacturing solution requirements, search the process ontology information database to find similar process examples. If the same examples are found, they can be directly borrowed. If there are similar examples, they can be used as references to design manufacturing solutions.

[0054] (3) In the production process analysis and manufacturing plan determination stage, on the basis of considering part information and process constraints, the process data and process knowledge in the manufacturing resource information are considered, and more auxiliary tooling and equipment resource information is applied to select idle equipment and tooling resources;

[0055] (4) During the manufacturing plan verification phase, it is necessary to consider process data and process knowledge in more detail to ensure the safe production of the manufacturing plan, and after the manufacturing plan is roughly determined, it should be inspected according to the technical requirements of the product instance in the product information database;

[0056] (5) Finally, a complete set of process documentation is compiled, including process flow charts, operating procedures, and quality control plans, and new process knowledge is fed back into the knowledge base to provide a reference for future process design.

[0057] Beneficial Effects

[0058] First, the present invention significantly improves the organization and retrieval efficiency of process information through systematic data classification and ontology construction. This structured method not only makes information storage more orderly, but also strengthens the internal connection between information through the application of ontology technology, making knowledge discovery and innovation easier.

[0059] Second, the invention effectively solves the pain points in existing process resource management by constructing an intelligent management system. In the intelligent production process, the information barrier between the production site and the data management center is broken, the real-time update of the database is realized, all relevant data are integrated into a unified platform, and the optimal allocation of resources is significantly improved.

[0060] Third, the present invention provides strong support for manufacturing scheme design through the construction of an overall database framework and data classification and organization. The system can quickly carry out preliminary planning of manufacturing processes based on product instance feature information, and match similar instances in the database for detailed manufacturing scheme design, thereby greatly improving the efficiency and quality of process design. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0062] Figure 1 Build the overall framework for the database;

[0063] Figure 2 Flowchart of the method for constructing a structured database of resource models for low-cost complex equipment mass production lines;

[0064] Figure 3 Model a framework diagram for product resources;

[0065] Figure 4 Modeling framework diagram for manufacturing resources;

[0066] Figure 5 Modeling framework diagram for process equipment;

[0067] Figure 6 It is a relationship diagram between process ontology information;

[0068] Figure 7 It is the product information ER diagram;

[0069] Figure 8 ER diagram for manufacturing resources;

[0070] Fig. 9 Process resource information ER diagram;

[0071] Fig.10 Database real-time update flow chart;

[0072] Fig.11 Data resource requirement diagram for manufacturing solution generation. DETAILED DESCRIPTION

[0073] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0074] It should be noted that the following embodiments and features in the embodiments may be combined with each other in the absence of conflict; and, based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making any creative work are within the scope of protection of the present disclosure.

[0075] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0076] The present application embodiment solves the pain points in existing process resource management by building a low-cost structured database of complex equipment scale production line resource models. Through systematic data classification, ontology construction and database design, efficient management and optimal configuration of process resources are achieved. The overall content of the complex equipment process resource information database is as follows: Figure 1The main modeling contents of the database include complex equipment product information modeling, process resource information modeling and process information modeling, which include all the information of complex equipment from design to production, with clear classification.

[0077] The traditional process resource management method has problems such as information islands, inconsistent data, and inefficient resource utilization. Therefore, building a low-cost, efficient structured database of complex equipment scale production line resource models is of great significance for improving production management, reducing costs, and improving market competitiveness. In the knowledge association module of the embodiment of the present application, the process module is associated with the product instance module, and the process template module is associated with the product instance. The overall database data is connected as a whole, which is convenient for management and strengthens the knowledge association of complex equipment process information; in the content operation module, it is divided into a model layer and an object layer, and the database data management method is standardized for data operations.

[0078] like Figure 1-2 As shown, the embodiment of the present application is a method for constructing a structured database of a resource model for a low-cost complex equipment large-scale production line, and the specific process is:

[0079] Step 1: Product information modeling: Model product information into three levels: product category, product series, and product instance. Product series are subordinate to product category, and product instance is subordinate to product series.

[0080] Product information is the input of process design. When a process engineer is carrying out process design activities, he or she must first clarify the characteristic information of the target product and make preliminary plans for the manufacturing process based on the product characteristic information. There is often a certain degree of correlation between product characteristics and manufacturing processes. For example, if there is an "insulation layer" in a cable product, the manufacturing process must include the "insulation" process. The complete expression of product information is mainly completed through the coordination of conceptual models at three different levels: product classification, product series, and product instance.

[0081] In the multi-variety and small-batch manufacturing mode, complex equipment product information is diverse and updated quickly. Structuring complex equipment product information can quickly screen target products and put forward reasonable personalized needs; at the same time, it can support process engineers to quickly understand the characteristics of complex equipment products and complete efficient process design tasks. Complex equipment products usually show differences and similarities at different levels in function or structure. Based on this, complex equipment products can be divided into three levels: product classification, product object, and product instance, and a corresponding representation model can be established for each level, such as Figure 3 shown.

[0082] (1) Product classification modeling

[0083] Complex equipment products (finished products, semi-finished products, parts, etc.) are classified according to the similarities in the selected dimensions, forming a product division method with a clear structure and clear boundaries.

[0084] The following is a detailed description of the design process of this step:

[0085] Commonly used classification criteria for product classification include function, usage scenario, material, structure, processing status, etc. For more complex products, multiple classification criteria can be combined to establish enterprise product classification in a hierarchical tree structure. Classification by function means that such products can meet the same functional requirements and are suitable for the manufacture of various product types; classification by scenario means that such products are applicable to the same scenarios, and are usually used in conjunction with functional classification to perform multi-dimensional classification descriptions of products; classification by material is usually a way of dividing parts and blanks, which means that the raw material types and organizational structures of such products are the same; classification by structure means that the geometric features and sizes of such products are similar, which is a classification of local features of products, and usually exists as a lower-level classification basis in multi-layer classification trees; classification by processing status means that the links in the production and manufacturing process of products are similar, and are usually used to divide semi-finished products, parts, etc.

[0086] According to the above analysis, the classification information of complex equipment products can be represented by four features:

[0087] Prod_Cat=(Prod_Cat_ID,Prod_Cat_Parent_ID,Prod_Cat_Name,Prod_Cat_Remarks)

[0088] in,

[0089] Prod_Cat: Product Category, indicating the complex equipment product category;

[0090] Prod_Cat_ID: indicates the number of the complex equipment product classification;

[0091] Prod_Cat_Parent_ID: indicates the parent classification number of the current complex equipment product classification;

[0092] Prod_Cat_Name: indicates the name of the complex equipment product category. In order to distinguish the product category from the product series and product instance names, the category name is recommended to end with "Category";

[0093] Prod_Cat_Remarks: indicates the remark information of the complex equipment product classification.

[0094] (2) Product Series Modeling

[0095] Group products with similar product elements into a product series, where the product elements include: function, structure and process;

[0096] The attribute parameters of complex equipment product series are used as the characteristics to describe the product series. The characteristics of the product series are described using structured attribute and parameter information, and a product series model is established based on this.

[0097] Among them, product series attributes include enumerated attributes and quantitative parameters;

[0098] Enumeration attributes are used to describe the characteristic information of enumerable types in complex equipment products. Each enumeration attribute can be configured with multiple attribute enumeration values ​​at the same time to meet the characteristic description needs of different series of products.

[0099] Quantitative parameters are used to describe characteristic information of non-enumerable types in complex equipment products. The values ​​of quantitative parameters can be recorded as "single value", "interval value" or "deviation value" according to the product characteristic information.

[0100] The following is a detailed description of the design process of this step:

[0101] The purpose of establishing product classification is to quickly locate the target complex equipment and help technicians understand the macro information of the product. Therefore, an overly detailed product classification tree will lose its value and will bring unnecessary difficulties. In order to structure and apply more information describing the characteristics of complex equipment products on the basis of product classification information, a product series model can be established. The complex equipment product series is a general term for a series of products developed by manufacturing companies with basically the same functions, basically similar structures, and highly consistent manufacturing processes. The division of product series adopts the similarity idea of ​​grouping technology, and parts (products) with similar product elements such as functions, structures, and processes are grouped into a part (product) family. For multi-variety small-batch production mode, processing according to the part (product) family design process can expand product batches, reduce product varieties, and reduce production efficiency losses caused by the production and manufacturing mode.

[0102] In order to describe the similarities and differences between these complex equipment products, it is necessary to describe the product characteristics in a structured manner, so the description model of product characteristics is established first. The characteristics of complex equipment products are diverse, including geometric shape characteristics, surface characteristics, size characteristics, environmental adaptability characteristics, structural composition characteristics, material performance characteristics, etc. If the above characteristics are to be distinguished in detail and a representation method that can accurately describe these characteristic information is established, the established method must require the user to have sufficient professional background as support, and most manufacturing companies often only pay attention to a small part of the product characteristic information. Therefore, the attribute parameters of the complex equipment product series can be used as the characteristics to describe the product series.

[0103] Enumeration attributes are used to describe the characteristic information of enumerable types in complex equipment products. Usually, this type of information is a description of the same or similar characteristics of products in the same series during the series division process, that is, the similarity within the product series. Each enumeration attribute can be configured with multiple attribute enumeration values ​​at the same time to meet the needs of feature description of different series of products.

[0104] Quantitative parameters are used to describe the characteristic information of non-enumerable types in complex equipment products. This type of information is usually used to describe the specific parameter differences between products of different specifications in a certain series, that is, the differences within the complex equipment product series. The value of the quantitative parameter can be recorded as "single value", "interval value" or "deviation value" according to the product characteristic information.

[0105] In the attribute parameters of complex equipment product series, enumeration attributes and quantitative parameters can be distinguished by the value type of the product attribute parameter. For example, if the value type of the attribute parameter is single value, it is an enumeration attribute, and if it is other, it is a quantitative parameter.

[0106] The quantitative parameters of the properties of complex equipment products can be expressed by six characteristics:

[0107] Prod_AP=(Prod_AP_ID,Prod_AP_Name,Prod_AP_Code,Prod_AP_Unit,Prod_AP_Type,Prod_AP_Remarks)

[0108] in,

[0109] Prod_AP: represents product attribute parameters;

[0110] Prod_AP_ID: indicates the product parameter number;

[0111] Prod_AP_Name: indicates the product parameter name;

[0112] Prod_AP_Code: code or abbreviation indicating product parameters;

[0113] Prod_AP_Unit: indicates the unit of product parameters;

[0114] Prod_AP_Type: indicates the value type of the product parameter, including single value, interval value and deviation value;

[0115] Prod_AP_Remarks: indicates the remarks of product parameters.

[0116] After establishing the representation model of product attributes, the structured attribute and parameter information can be used to describe the characteristics of the product series, and thus establish a product series model.

[0117] Complex equipment product line information can be represented by six features:

[0118] Prod_Series=(Prod_Series_ID,Prod_Series_Cat_ID,Prod_Series_Name,Prod_Series_Attr,Prod_Series_AP,Prod_Series_Remarks)

[0119] in,

[0120] Prod_Series: indicates product series;

[0121] Prod_Series_ID: indicates the product series number;

[0122] Prod_Series_Cat_ID: indicates the product category number to which the product series belongs, and establishes the association between the product series and the product category;

[0123] Prod_Series_Name: indicates the product series name;

[0124] Prod_Series_AP: represents the attribute quantization parameter set of the product series;

[0125] Prod_Series_Remarks: indicates the remarks of the product series, which supplements other product information besides the series name, attributes and parameters.

[0126] (3) Product instance modeling

[0127] The product BOM (Bill of Materials), technical requirements and technical features of product parts are used as features of the product instance model.

[0128] The product BOM contains all necessary raw materials and components, including their models, quantities and sources; the technical requirements contain performance standards and test conditions; the product part technical characteristics provide detailed dimensions, shapes and material properties of each component.

[0129] The following is a detailed description of the design process of this step:

[0130] Through variant design, a main product is used to form a group of products with similar product attributes but different specific parameters. These similar products together form a product series, and the product objects with different detailed features under the series are called product instances. Usually these detailed features will contain the specification information of such product objects, so product instances can also be called product specifications. Since product instances belong to a certain product series, they will inherit the attribute information of the product series, including all enumerated attributes and corresponding attribute value selections, as well as all quantitative parameters. In addition, the description content of product instance information has penetrated into the level of product specification data, and the specific detailed features of each instance have been determined.

[0131] Complex equipment product instance information is a key component in the manufacturing and quality control process, which defines the specific composition and characteristics of the product in detail. By combining the three core elements of product BOM (Bill of Materials), technical requirements and product parts technical characteristics, a comprehensive description can be formed to ensure that every detail of the product meets the design and functional standards.

[0132] The product BOM serves as the basis for manufacturing and lists all necessary raw materials and components, including their models, quantities and sources. For example, a complex mechanical device may require hundreds of different parts, each with its own specific specifications and sources, and this information is recorded in detail in the BOM.

[0133] Technical requirements further define the performance standards and test conditions that the product must meet, such as temperature resistance, pressure resistance or specific environmental adaptability. These requirements ensure that the product can perform as expected in actual applications and meet the needs of users.

[0134] Product part technical characteristics provide detailed dimensions, shapes and material properties of each component, including manufacturing tolerances and quality control standards. These characteristics are critical to ensuring component compatibility and overall product performance.

[0135] Combining these three elements, complex equipment product instance information provides production teams, supply chain partners and quality assurance departments with a clear blueprint to guide them on how to manufacture, inspect and deliver high-quality products that meet standards.

[0136] Complex equipment product instance information can be represented by seven features:

[0137] Prod_Inst=(Prod_Inst_ID,Prod_Inst_Series_ID,Prod_Inst_Name,Prod_Inst_BOM,Prod_Inst_Remarks,Prod_Inst_Req,Prod_Inst_Feature)

[0138] in,

[0139] Prod_Inst: Product Instance, indicating a product instance;

[0140] Prod_Inst_ID: indicates the product instance number;

[0141] Prod_Inst_Series_ID: indicates the product series number to which the product instance belongs, thereby establishing an association between the product instance and the product series to inherit the product attribute information owned by the product series;

[0142] Prod_Inst_Name: indicates the product instance name, which can usually be the product specification information;

[0143] Prod_Inst_BOM: represents a collection of bills of materials for a product instance, listing all the parts, raw materials, and subassemblies required to manufacture, assemble, or maintain the product;

[0144] Prod_Inst_Req: represents the set of technical requirements for a product instance, listing the performance standards and test conditions that the product must meet, such as temperature resistance, pressure resistance, or specific environmental adaptability;

[0145] Prod_Inst_Feature: A collection of technical features of product parts that represent a product instance, which provides detailed size, shape, and material properties of each component, including manufacturing tolerances and quality control standards;

[0146] Prod_Inst_Remarks: indicates the remarks of the product instance.

[0147] The BOM information of complex equipment products can be represented by seven features:

[0148] Prod_PART=(Prod_PART_ID,Prod_PART_Name,Prod_PART_Num,Prod_PART_Source,Prod_PART_Material,Prod_PART_Remarks)

[0149] in,

[0150] Prod_PART: indicates the parts required for the product;

[0151] Prod_PART_ID: indicates the product part number;

[0152] Prod_PART_Name: indicates the product part name;

[0153] Prod_PART_Num: indicates the number of parts required for the product;

[0154] Prod_PART_Material: indicates the material of the product part;

[0155] Prod_PART_Source: indicates the source of product parts;

[0156] Prod_PART_Remarks: indicates the remarks of product parts.

[0157] The technical requirements of complex equipment products can be expressed by four characteristics:

[0158] Prod_Req=(Prod_Req_ID,Prod_Req_Name,Prod_Req_Test,Prod_Req_Remarks)

[0159] in,

[0160] Prod_Req: indicates the technical requirements that the product needs to meet;

[0161] Prod_Req_ID: indicates the number of the technical requirement;

[0162] Prod_Req_Name: indicates the name of the technical requirement;

[0163] Prod_Req_Test: indicates the number of conditions required by the technical requirements;

[0164] Prod_Req_Remarks: indicates the remarks of technical requirements.

[0165] The technical characteristics of product parts of complex equipment products can be expressed by four characteristics:

[0166] Prod_Feature=(Prod_Feature_ID,Prod_Feature_Name,Prod_Feature_PART_ID,Prod_Feature_Size,Prod_Feature_Remarks)

[0167] in,

[0168] Prod_Req: indicates the technical requirements that the product needs to meet;

[0169] Prod_Req_ID: indicates the number of the technical requirement;

[0170] Prod_Feature_PART_ID: indicates the number of the product part corresponding to the technical feature of the product part, and establishes the association between the technical feature of the part and the product part;

[0171] Prod_Req_Name: indicates the name of the technical requirement;

[0172] Prod_Req_Test: indicates the number of conditions required by the technical requirements;

[0173] Prod_Req_Remarks: indicates the remarks of technical requirements.

[0174] In this step, the complex equipment product information is divided into three levels: "classification-series-instance". Classification categorizes product information from a macro perspective; series has enumerated attributes, attribute values ​​and unassigned quantitative parameters that describe the characteristics of product information; instances instantiate and supplement the specific characteristics of the product.

[0175] Step 2: Modeling of complex equipment manufacturing resource information: For each manufacturing process, a process resource information database is established, which mainly stores four categories of knowledge: process data, tooling knowledge, auxiliary tooling and process equipment in the process of process processing.

[0176] In this step, to complete the construction of the domain ontology of complex equipment production process resources, it is necessary to abstract its concepts, and the knowledge classification of the contained process knowledge is the basis for constructing the ontology. The complex, messy, disordered, and complex complex equipment processing technology resources are classified into knowledge and constructed into a system of systems. The preliminary classification of knowledge provides a basis for future knowledge management, and is also an important part of establishing the domain ontology. The classification of complex equipment manufacturing process resources is to integrate and classify the relevant process knowledge involved according to the life cycle of complex equipment products, so that the originally chaotic complex equipment manufacturing process resources can be classified, so that the complex equipment manufacturing process resources become organized and systematized, thereby establishing a process resource structure system. Classifying and organizing the contained processes is the starting point for understanding, managing and applying complex equipment manufacturing process resources.

[0177] Manufacturing process resources are a collection of physical or conceptual objects required to complete a certain process design task in the field of manufacturing process design. Manufacturing process resources include equipment, process equipment tools, gauges, fixtures, auxiliary tools, etc. in process design, process design data such as materials, feed rate, cutting depth, cutting speed, design calculation, etc., and process resources are the most basic components in collaborative process design. In order to facilitate resource management, it is an important part of information management to first classify complex equipment manufacturing resources.

[0178] According to the national standard JB / T5992-92 "Classification of process methods and their codes", manufacturing processes can be divided into 9 categories, including casting, pressure processing, welding, cutting processing, special processing, heat treatment, covering, assembly and packaging, and others. Each process category can be further divided into middle categories and small categories. For example, casting includes two middle categories, sand casting and special casting. The middle category of sand casting is divided into wet casting, dry casting, surface dry casting, self-hardening casting and other process small categories. Even the process small categories can be divided into many types of process types in actual process. At present, the description of these process methods only has technical performance data, and lacks data or knowledge description on green characteristics.

[0179] In view of this, in this step, a process resource information library is established for each manufacturing process, which mainly stores four categories of knowledge in the process of process processing: process data, tooling knowledge, auxiliary tooling and process equipment, such as Figure 4 Shown

[0180] (1) Process data modeling

[0181] Process data include engineering materials, cutting parameters, labor quotas, tolerances and other data as well as various process terms, so that process designers can retrieve the required data quickly and easily.

[0182] Classify process data according to its type and purpose, and define a unified data model for each type of data. During the modeling process, a series of key attributes are defined for process data, including the data's unique identifier, name, type, specific value, unit, source, and validity conditions. During the modeling process, special attention should also be paid to the source and validity of the data, as this information is crucial to ensuring the accuracy and applicability of process data.

[0183] The following is a detailed description of the design process of this step:

[0184] The core goal of process data modeling is to provide process designers with a comprehensive and structured database that can quickly respond to their needs for key process parameters during the design process to support decision-making during the process design process. To this end, the process data is first carefully classified and systematically managed to ensure that each type of data can be accurately identified and retrieved according to its characteristics and application scenarios, so that process designers can quickly and accurately obtain the required process parameters and information.

[0185] Process data modeling adopts a structured approach to classify process data according to its type and purpose, and defines a unified data model for each type of data. During the modeling process, a series of key attributes are defined for process data, including the data's unique identifier, name, type, specific value, unit, source, and validity conditions. These attributes together constitute a comprehensive description of the process data, allowing each piece of data to play its due role in design decisions. During the modeling process, special attention should also be paid to the source and validity of the data, as this information is crucial to ensuring the accuracy and applicability of process data. By clarifying the source of the data, it can be traced back to the original reference standard or authoritative literature, thereby ensuring the authority of the data. At the same time, by recording the validity conditions of the data, it can be ensured that the data is reliable within a specific application range.

[0186] The application scope of process data modeling is very wide. It can not only support process design and provide necessary parameters and reference data, but also play an important role in quality control, cost estimation and employee training. Through this structured process data model, we can significantly improve the efficiency of process design and ensure product quality, while also providing strong support for knowledge management and technology inheritance of manufacturing enterprises.

[0187] The process data model can be represented by eight features:

[0188] Process_Data=(Process_Data_ID,Process_Data_Name,Process_Data_Type,Process_Data_Value,Process_Data_Unit,Process_Data_Source,Process_Data_Validity,Process_Data_Remarks)

[0189] in,

[0190] Process_Data_ID: Unique identifier of process data, used to uniquely identify a process data record in the database.

[0191] Process_Data_Name: The name of the process data, used to describe the main characteristics or purpose of the data.

[0192] Process_Data_Type: The type of process data, such as cutting amount, working time quota, tolerance and so on.

[0193] Process_Data_Value: The specific value or description of the process data, which can be a number, text, or a more complex data structure.

[0194] Process_Data_Unit: The unit of the data value, such as millimeter, hour, revolution per minute, etc.

[0195] Process_Data_Source: Data source, which can be internal enterprise standards, industry specifications or authoritative documents.

[0196] Process_Data_Validity: The validity or applicable conditions of the data, such as temperature range, material type, etc.

[0197] Process_Data_Remarks: Additional descriptions or comments on the data, such as usage precautions, data update records, etc.

[0198] (2) Auxiliary tooling modeling

[0199] Auxiliary tooling modeling process: First, identify and classify the various tools and equipment used in the manufacturing process, and determine the functions and application scenarios of each type of tooling; second, establish a detailed classification system to group the tooling according to its function, purpose and design standards; third, define a series of key attributes for auxiliary tooling to comprehensively describe its characteristics and application conditions.

[0200] The following is a detailed description of the design process of this step:

[0201] Including various tool resources used in the product manufacturing process, including cutting tools, fixtures, gauges, molds, gauges, auxiliary tools, pliers and workstations. The resource information involved in tooling design is very complicated, with various contents and forms, mainly including various tooling design standards, standard parts information, general parts information, three-dimensional models, calculation methods, parts design process information and design technical documentation and other resource information. Tooling resources are an important part of manufacturing process resources. From the perspective of resource management, in order to fully and consistently represent the resources of the analysis object at a higher level and comprehensively describe the various types of resources involved in each analysis object and the relationship between resources.

[0202] Auxiliary tooling modeling is a key step in ensuring that tools and equipment in the manufacturing process can effectively support production activities. Auxiliary tooling modeling aims to provide a systematic management framework for the various tools and equipment used in the manufacturing process. Through this framework, it can ensure that process designers and operators can quickly find the right tooling to support specific processing tasks. In addition, this modeling process can also help optimize the use and maintenance of tooling, reducing delays and costs in production.

[0203] Auxiliary tooling modeling first involves the identification and classification of various tools and equipment used in the manufacturing process. This includes tools, fixtures, gauges, molds, etc. Each type of tooling has its specific function and application scenario. To achieve this goal, a detailed classification system was established to group tooling according to its function, purpose and design standards to ensure that each tooling can be accurately identified and retrieved.

[0204] In model construction, a series of key attributes are defined for auxiliary tooling to fully describe its characteristics and application conditions. These attributes include the unique identifier, type, specification, 3D model, instructions, design standards, and notes of the tooling. For example, Tooling_Resource_ID provides a unique reference number for each tooling, while Tooling_Resource_Type clarifies the classification of the tooling, such as a milling cutter or fixture. Tooling_Resource_Spec describes the specific specifications and dimensions of the tooling in detail, which is crucial to ensure that the tooling matches the processing task.

[0205] The 3D model is an important component in auxiliary tooling modeling. It provides process designers with an intuitive visual reference and helps to foresee possible compatibility issues during the design phase. In addition, by integrating design standards and instructions, the correct selection and application of tooling is ensured, thus avoiding errors and delays in the production process.

[0206] The application value of auxiliary tooling modeling is reflected in many aspects. It can not only improve the efficiency of process design and reduce design errors, but also optimize the production process, improve processing accuracy and production efficiency. In addition, through structured tooling data, enterprises can better plan and manage resources, achieve cost control and quality assurance.

[0207] Auxiliary tooling modeling is a complex but crucial process, which involves multiple links such as detailed classification of tooling, attribute definition, data entry and application implementation. Through this process, a powerful tooling resource management platform can be provided for manufacturing companies to support the continuous improvement and innovation of their process design and production manufacturing.

[0208] The auxiliary tooling model can be represented by eight features:

[0209] Tooling_Resource=(Tooling_Resource_ID,Tooling_Resource_Name,Tooling_Resource_Type,Tooling_Resource_Spec,Tooling_Resource_Model,Tooling_Resource_Usage,Tooling_Resource_Standard,Tooling_Resource_Remarks)

[0210] in,

[0211] Tooling_Resource_ID: A unique identifier for auxiliary tooling, used to uniquely identify a tooling in the database.

[0212] Tooling_Resource_Name: The name of the auxiliary tooling, used to describe the main features or uses of the tooling.

[0213] Tooling_Resource_Type: The type of auxiliary tooling, such as tools, fixtures, measuring tools, etc.

[0214] Tooling_Resource_Spec: The specific specifications or dimensions of the auxiliary tooling, which is critical to ensure that the tooling matches the processing task.

[0215] Tooling_Resource_Model: A three-dimensional model or design drawing of auxiliary tooling, providing intuitive visual reference.

[0216] Tooling_Resource_Usage: Instructions for use or application scenarios of auxiliary tooling to guide process designers and operators in their correct use.

[0217] Tooling_Resource_Standard: The standard on which tooling design and application are based, such as international standards or internal company standards.

[0218] Tooling_Resource_Remarks: Additional instructions or remarks on tooling, such as usage precautions, maintenance requirements, etc.

[0219] (3) Process knowledge modeling

[0220] The process knowledge is summarized into three types: process decision knowledge, process instance knowledge, and auxiliary process resources. In the process of process knowledge modeling, the expert experience, factual knowledge, and procedural knowledge accumulated in the process of process design are systematically organized and digitally expressed.

[0221] The following is a detailed description of the design process of this step:

[0222] Process resources belong to professional knowledge, including experts' heuristic experience, factual knowledge and process knowledge. These knowledge are used comprehensively at every moment in process design. For example, the selection of process methods, the determination of clamping schemes, the arrangement of process routes, etc. The decision-making process contains heuristic knowledge of decision rules, factual knowledge, and problem analysis, understanding, and optimization knowledge. These knowledge can be summarized into three types: process decision knowledge, process example knowledge, and auxiliary process resources.

[0223] 1. Process decision-making knowledge is composed of empirical rules, process decision logic, procedural algorithms, decision habits, etc., such as processing method selection rules, process sequence rules, machine tool, tool, fixture, measuring tool selection rules, processing parameter decision knowledge, process route decision knowledge, processing method decision knowledge, etc.

[0224] 2. Process example knowledge. Knowledge about process example, typical process data, etc. A process example is a combination of part information and process information that already exists in the process system. It is a mature process that has been proven to be correct in advance; a typical process is a set of standard processes for parts and components obtained after normalizing and standardizing the process.

[0225] 3. Auxiliary process resources are mainly used to support various auxiliary prompts in the process design process, and provide fast and practical information services to process personnel in real time. Decision-making work is left to process personnel. Including process dictionaries, common process elements, common processes, etc. obtained from process data in an automated way. Under certain conditions, process dictionaries, common process elements, and common processes can be converted into standard processes, typical processes, or used as components of standard processes and typical processes, improving the ability of derivative systems based on group technology to adapt to the environment.

[0226] The core of process knowledge modeling is to systematically organize and digitally express the expert experience, factual knowledge, and procedural knowledge accumulated during the process design, so that they can be quickly accessed and effectively applied by process personnel, thereby improving the accuracy and efficiency of process design. This process not only involves the collection and organization of expert experience, factual knowledge, and procedural knowledge, but also includes the careful design of the knowledge structure to ensure the retrievability and practicality of knowledge, aiming to build a knowledge base that supports process decision-making, optimization, and innovation.

[0227] Process knowledge modeling adopts a structured and semantic approach to transform process knowledge into a queryable and analyzable data model by defining knowledge classification, attributes and relationships, thereby achieving accurate description and effective organization of knowledge. The key features of the process knowledge model include the unique identifier, type, specific content, source, application scenario and other associated knowledge or resources of the knowledge. These features together form the basis of the process knowledge model, enabling knowledge to play the greatest role in process design.

[0228] The process of process knowledge modeling includes steps such as knowledge identification, classification, attribute definition, data modeling, data entry, verification and update. Through this process, a knowledge base that supports process decision-making, optimization and innovation can be built, providing a powerful knowledge support platform for process designers.

[0229] The application range of process knowledge model is wide. It can not only serve as a support tool for process decision-making to help designers choose appropriate process methods and parameters, but also promote the optimization of process flow and improve production efficiency. In addition, process knowledge model also helps to share and inherit knowledge, accelerate the training process of new employees, and inspire new process design ideas and solutions. Through process knowledge modeling, we can significantly improve the efficiency and quality of process design and enhance the competitiveness and innovation ability of the entire manufacturing process.

[0230] The process knowledge model can be represented by seven features:

[0231] Process_Knowledge=(Process_Knowledge_ID,Process_Knowledge_Type,Process_Knowledge_Content,Process_Knowledge_Source,Process_Knowledge_Application,Process_Knowledge_Related,Process_Knowledge_Remarks)

[0232] in,

[0233] Process_Knowledge_ID: The unique identifier of process knowledge, used to uniquely identify a process knowledge record in the database.

[0234] Process_Knowledge_Type: process knowledge type, such as decision-making knowledge, instance knowledge, auxiliary resources, etc.

[0235] Process_Knowledge_Content: The specific content of process knowledge, including rules, parameters, methods, etc.

[0236] Process_Knowledge_Source: The source of knowledge, which may come from expert experience, historical data or literature.

[0237] Process_Knowledge_Application: Application scenarios and conditions of knowledge, guiding when and how to use this knowledge in process design.

[0238] Process_Knowledge_Related: Other knowledge or resources related to this knowledge, supporting the comprehensive application of knowledge.

[0239] Process_Knowledge_Remarks: Additional explanations or comments on the knowledge, providing further background information or usage suggestions.

[0240] (4) Equipment resource modeling

[0241] When modeling process equipment, the model not only contains the basic information of the equipment, but also covers the operating status, capacity parameters and remarks of the equipment.

[0242] The following is a detailed description of the design process of this step:

[0243] According to their functions, they are divided into motor equipment, instruments and auxiliary equipment, power, electrical appliances, conduction and mechanical equipment. Mechanical equipment can be derived into lathes, milling machines, etc. Whether it is a lathe, milling machine or drilling machine, there is also a description of its structure, capacity and status in the object class organization management. The resource structure form is the carrier of resource capacity. Its structured representation of the object hierarchy helps to analyze resource capacity at different levels. Resource capacity is mainly used to describe the manufacturing capacity of manufacturing resources at different levels; resource status is used to describe the performance status and dynamic characteristics of resources, such as resource status changes, load conditions and production conditions. It determines whether the manufacturing capacity of resources can be realized under the existing conditions.

[0244] The core of equipment resource modeling is to establish a detailed equipment information database, which not only contains basic information about the equipment, but also covers the equipment's operating status, capacity parameters and notes. Such a model helps process designers, equipment maintenance engineers and production managers quickly obtain the required information during the decision-making process, thereby improving production efficiency and equipment utilization.

[0245] Equipment resource modeling adopts a structured approach to classify equipment resources and describe their structure, capabilities, and status by defining a series of equipment attributes to build models. These attributes include not only static information about the equipment, such as number, name, model, and manufacturer, but also dynamic information, such as the equipment's status and capabilities. In addition, for the equipment's status and capabilities, sub-attributes are further defined to provide more detailed information, such as Figure 5 shown.

[0246] The device resource model consists of the following key characteristics:

[0247] Equipment=(Equipment_ID,Equipment_Name,Equipment_Manufacturer,Equipment_Model,Equipment_Status,Equipment_Ability,Equipment_Remarks)

[0248] in,

[0249] Equipment_ID: The unique identifier of the process equipment, used to uniquely identify a piece of equipment in the database.

[0250] Equipment_Name: The name of the process equipment, used to describe the main function or purpose of the equipment.

[0251] Equipment_Manufacturer: Manufacturer, providing the manufacturer information of the equipment.

[0252] Equipment_Model: The model and 3D model of the process equipment, providing the physical specifications of the equipment.

[0253] Equipment_Status: A collection of equipment statuses, including multiple status elements, each of which consists of the following sub-attributes:

[0254] Equipment_Ability: A collection of equipment capabilities, including multiple capability elements, each of which consists of the following sub-attributes:

[0255] Equipment_Remarks: Additional instructions or comments about the equipment, which may include specific operating requirements for the equipment, historical maintenance records, or other relevant information.

[0256] The device status can be represented by the following five characteristics:

[0257] Equipment_Status=(Equipment_Status_ID, Equipment_Status_Name, Equipment_Status_Parameter, Equipment_Status_Normal_Parameter_Range, Equipment_Status_Remarks)

[0258] in,

[0259] Equipment_Status_ID: Unique identifier for the status.

[0260] Equipment_Status_Name: The name of the status, such as "in operation", "under maintenance", etc.

[0261] Equipment_Status_Parameter: Status parameter, which describes the specific indicators of the equipment status.

[0262] Equipment_Status_Normal_Parameter_Range: Normal parameter range, which defines the expected value range of the status parameter when the equipment is operating normally.

[0263] Equipment_Status_Remarks: Remarks information, providing additional descriptions or notes about the status.

[0264] Device capabilities can also be expressed using the following five characteristics:

[0265] Equipment_Ability=(Equipment_Ability_ID,Equipment_Ability_Name,Equipment_Ability_Parameter,Equipment_Ability_Normal_Parameter_Range,Equipment_Ability_Remarks)

[0266] in,

[0267] Equipment_Ability_ID: Unique identifier of the capability.

[0268] Equipment_Ability_Name: The name of the ability, such as "maximum processing size", "work efficiency", etc.

[0269] Equipment_Ability_Parameter: capability parameter, which is a quantitative indicator describing the equipment capability.

[0270] Equipment_Ability_Normal_Parameter_Range: Normal parameter range, which defines the normal value range of equipment capability.

[0271] Equipment_Ability_Remarks: Remarks information, providing additional descriptions or notes about the ability.

[0272] In step 2 of the embodiment of this application, four key components of manufacturing resource modeling are given: process data, auxiliary tooling, process knowledge, and equipment resources. Through the comprehensive modeling of these four parts, a comprehensive resource management framework is provided for manufacturing companies, aiming to improve the efficiency and quality of process design, production scheduling, and equipment maintenance.

[0273] Process data modeling provides a structured database that enables process designers to quickly retrieve key data such as required engineering materials and cutting amounts, thereby accelerating the process design process and improving the accuracy of decision-making. Auxiliary tooling modeling covers various tool resources used in the manufacturing process, such as cutting tools and fixtures. By describing the specifications and usage conditions of these tools in detail, the accuracy of process design and the efficiency of production are ensured. Process knowledge modeling integrates expert experience, factual knowledge and procedural knowledge to form a knowledge base that supports process decision-making and optimization, and promotes knowledge sharing and inheritance. Finally, equipment resource modeling provides data support for the effective use and maintenance of equipment by recording the specifications, performance and status of the equipment in detail.

[0274] The integration of the modeling work of these four parts presents a comprehensive view of manufacturing resource management, which not only improves the efficiency of resource utilization but also enhances the transparency and controllability of the production process.

[0275] Step 3: Modeling of complex equipment process information:

[0276] The process ontology information includes process composition information and process requirement information. Modeling also includes establishing the composition relationship between process composition information, the top-down hierarchical relationship between process requirement information, and the association relationship between process composition information and process requirement information.

[0277] The following is a detailed description of the design process of this step:

[0278] In order to support the process design of low-cost large-scale production lines, it is necessary to model and describe the production process of complex equipment to support process resource design and process resource reuse. This step introduces the modeling method of process composition information and process requirement information, and then proposes a process template model representation method that integrates various types of process ontology information.

[0279] Process ontology information is the basic information that describes the manufacturing process of a product. Process ontology information plays the role of a design information carrier in the process design process. All contents describing the manufacturing process and requirements are represented by process ontology information. Therefore, the inductive representation of process ontology information is a necessary prerequisite for realizing complex equipment process design activities. Process ontology information can be divided into process composition information and process requirement information. The two complement each other and jointly realize the structured expression of process design activities. There is a composition relationship between process composition information such as process routes, procedures, and steps; there is a top-down decomposition between process requirement information such as process route requirements, procedure requirements, and step requirements. In addition, there is an association relationship between process composition information and process requirement information. The process template contains process routes, procedures, steps, and all process requirements at the same time, and is a phased integrated carrier of process ontology information. The relationship between process ontology information is as follows: Figure 6 shown.

[0280] (1) Process composition information modeling

[0281] In order to realize the effective utilization of process design knowledge, it is necessary to first establish a structured process composition information representation model, summarize and divide the process composition information of complex equipment, form standardized terminology and unified cognition to improve communication efficiency; at the same time, consider the processing method of the computer system to facilitate computer processing and utilization, and improve the storage and management of process resources.

[0282] 1. Work step information modeling

[0283] A work step is an independent operation process in the manufacturing process. The division of work steps is conducive to more detailed control and optimization of complex process activities. Therefore, the work step should be used as the basic unit of process composition information to represent the unit information of the processing technology.

[0284] When designing a product process, the product's characteristic requirements are usually first converted into macro process requirements, and then a series of processes and corresponding process requirements are designed according to the process requirements. Finally, detailed work steps and work step requirements are planned for each process. In the above process design process, the work step is the carrier for the final implementation of various process requirement information: the overall process requirements and the process requirements of each stage must eventually be implemented as specific work step requirements to truly achieve direct guidance of the production process. Therefore, the work step can be represented by the following seven characteristics:

[0285] Step=(Step_ID,Step_Name,Step_Req,Step_Equipment,Step_Quality_Control,Step_Material,Step_Remarks)

[0286] in,

[0287] Step: indicates the working step.

[0288] Step ID: indicates the work step number.

[0289] Step Name: indicates the name of the work step.

[0290] Step Req: Indicates the process step requirements. The specific information is introduced in the process requirement information modeling section.

[0291] Step_Equipment: Specifies the key equipment required for the process step.

[0292] Step_Quality_Control: Defines the quality control standards and inspection methods for the process steps.

[0293] Step_Material: List the raw materials or auxiliary materials used in the process step.

[0294] Step Remarks: Indicates the remarks of the work step.

[0295] 2. Process attribute information modeling

[0296] A process refers to a manufacturing process that is continuously performed by an operator at the same work location on one or more processed materials. In the above definition, the same "operator", "work location", "processed material" and "continuous" manufacturing process are the main basis for process division. A process consists of a series of steps, which work together to achieve changes in the characteristics of the processed materials. The composition of the steps of the process that achieves the same characteristic change will change depending on the manufacturing resources used. Each process must have corresponding manufacturing resources to realize it. The realization process can be completed by the same manufacturing resource alone or by the cooperation of multiple manufacturing resources. In order to improve production efficiency, it is often necessary to plan the space and logistics of the manufacturing resources that cooperate with each other in the same process.

[0297] Based on the above analysis, the process can be represented by the following seven characteristics:

[0298] Process=(Process_ID,Process_Name,Process_Comp,Process_Duration,Process_Manures_Inst_Set,Process_Reg,Process_Remarks)

[0299] in,

[0300] Process: indicates the process.

[0301] Process_ID: indicates the process number.

[0302] Process_Name: indicates the process name.

[0303] Process_Comp: represents the composition of the process, which is an ordered combination of multiple steps and can be expressed as:

[0304] Proc Comp= <stepi>,i=1,2,3…。

[0305] Process_Duration: The estimated duration of the process.

[0306] Process_Manures_Inst_Set:Process Manufacturing Resource Instance Set, represents the manufacturing resource instance set corresponding to the process.

[0307] Process_Reg: represents the process requirements, which will be introduced in detail in the process requirement information modeling section.

[0308] Process_Remarks: indicates the remarks of the process.

[0309] 3. Process route information modeling

[0310] The process route is a summary of all the process methods experienced by complex equipment during its production and manufacturing process, and is composed of a series of processes in the order of their implementation. At the same time, the process route can also be divided into stages according to the process specialty, workshop, etc., such as heat treatment process route, machining process route, etc. In order to improve production efficiency, enterprises usually plan the configuration of manufacturing resources according to typical process routes, including the quantity ratio, spatial arrangement, logistics mode, etc. between different equipment. A well-designed process route can not only improve production efficiency and reduce manufacturing costs, but also ensure the processing quality of products. In the manufacturing process of complex equipment, the completion of a process will lead to changes in some characteristics of the processed material (including material, structure, properties, etc.), and the implementation of a process route will lead to a series of characteristic changes that cooperate with each other to finally form the required product characteristics. There are usually mutual constraints on processing characteristics between the processes included in the process route. For example, the first process provides the necessary characteristic basis for the subsequent process, and the subsequent process generally cannot damage the characteristics that need to be retained formed by all previous processes. Therefore, the processes in the process route and their sequential arrangement are the basic elements for evaluating the rationality of the process route.

[0311] To a certain extent, similar parts require the same processing procedures and process sequence, and the only difference is that they have different requirements for certain steps in certain processes. By establishing a typical process route for such products or parts, it can be applied to the entire category of products or parts. Establishing a typical process route and a series of derived process routes generated by it can provide important help for enterprise process design activities.

[0312] According to the above analysis, the process route can be represented by the following seven characteristics:

[0313] Proc_Route=(Proc_Route_ID,Proc_Route_Name,Proc_Route_Comp,Proc_Route_Req,Proc_Route_Variants,Proc_Route_Optimization,Proc_Route Remarks)

[0314] in,

[0315] Proc_Route: represents the process route.

[0316] Proc_Route_ID: indicates the process route number.

[0317] Proc_Route_Name: indicates the process route name.

[0318] Poc Route Comp: represents the composition of the process route, which is an ordered combination of multiple processes and can be expressed as:

[0319] Route Comp= <processi>,i=1,2.3…

[0320] Proc_Route_Req: represents the process route requirements, which will be introduced in detail in the process requirement information modeling section.

[0321] Proc_Route_Variants: Records variations of process routes to handle different production situations.

[0322] Proc_Route_Optimization: records the optimization history and improvement measures of the process route.

[0323] Proc_Route Remarks: Indicates the remarks of the process route.

[0324] (2) Process requirement information modeling

[0325] Process requirements are constraints on the process methods used in the product manufacturing process formed by the enterprise based on product requirements, enterprise hardware and software conditions, industry standards and other information. The previous article divides the process component information into three levels: work step, process, and process route. Correspondingly, process requirement information can also be divided into work step requirements, process requirements, and process route requirements.

[0326] Process route requirements are a description of the overall process requirements of the material being processed at this stage of the process route. They usually only focus on the goals of the process route, without constraining the specific methods used to achieve these goals. Process route requirements are usually associated with product requirements during the process design process and play a role in the selection of process routes and process templates. Such requirements need to be determined by the process engineer to determine the composition of the process route and further converted into process and step requirements before they can guide production.

[0327] The process requirements are the staged process requirements formulated by the process engineer for each process in the process route according to the requirements of the overall process route, and also involve the process objectives and process operations of the process stage. In the process design process, the process requirements are usually decomposed and derived by the process engineer according to the process route requirements, and the requirements on the processing capabilities of the manufacturing resources to realize the process are put forward, thereby affecting the manufacturing resource selection process. As mentioned earlier, the process is composed of a series of steps in the order of their implementation, so the realization of the process requirements also requires the cooperation of a series of step requirements.

[0328] The process step requirements are specific process requirements that can directly guide the production process, designed by the process engineer after determining the process and the manufacturing resources used to implement the process, based on the actual production of the enterprise. They also involve the process goal of the process step and the process operations required to achieve the goal. The determination of the process step requirements is the core and difficulty of the process design process.

[0329] The above three types of process requirements can be summarized as target requirements and operation requirements. Target requirements refer to the requirements for the process goals expected to be achieved in the corresponding process stage, and operation requirements refer to the operating elements that need to be followed when using designated manufacturing resources (manufacturing equipment, sites, personnel, etc.) in order to achieve the target requirements, such as the operating parameters of various equipment, site environmental parameters, etc. Since the corresponding manufacturing resources have not yet been determined in the process route stage, the process route requirements usually only include target requirements but not operation requirements.

[0330] Both target requirements and operation requirements can be further expressed by process attributes and process parameters. Similar to the enumerated attributes and quantitative parameters of the product information series, process attributes are usually used to describe enumerable process requirements, such as insulation materials, number of braiding machine spindles, etc., while process parameters are used to describe process requirements that are not suitable for enumeration, such as material usage, wire feeding speed, etc.

[0331] 1. Process attribute feature representation

[0332] The process attribute Proc_Attr can be represented by the following seven features:

[0333] Proc_Attr=(Proc_Attr_ID,Proc_Attr_Name,Proc_Attr_Code,Proc_Attr_Unit,Proc_Attr_Enum,Proc_Attr_Dependencies,Proc_Attr_Remarks)

[0334] in,

[0335] Proc_Attr_ID: indicates the process attribute number.

[0336] Proc_Attr_Name: indicates the process attribute name.

[0337] Proc_Attr_Code: Code or abbreviation representing process attributes.

[0338] Proc_Attr_Unit: represents the unit of process attributes.

[0339] Proc_Attr_Enum: Represents an enumeration value list of process attributes.

[0340] Proc_Attr_Dependencies: describes the dependencies between process attributes.

[0341] Proc_Attr_Remarks: indicates the remarks of process attributes.

[0342] 2. Process parameter characteristics

[0343] The process parameter Proc_Param can be represented by the following six characteristics:

[0344] Proc_Param=(Proc_Param_ID,Proc_Param_Name,Proc_Param_Code,Proc_Param_Unit,Proc_Param_Type,Proc_Param_Calculations,Proc_Param_Remarks)

[0345] in,

[0346] Proc_Param_ID: indicates the process parameter number.

[0347] Proc_Param_Name: indicates the process parameter name.

[0348] Proc_Param_Code: The code or abbreviation of the process parameter.

[0349] Proc_Param_Unit: Indicates the unit of process parameters.

[0350] Proc_Param_Type: Indicates the value type of the process parameter, including single value, interval value and deviation value.

[0351] Proc_Param_Calculations: Defines the calculation method or formula for process parameters.

[0352] Proc_Param_Remarks: indicates the remarks of process parameters.

[0353] 3. Process ontology information representation

[0354] Products or parts in the same series have similar characteristic structures, and the processes used in their manufacturing process are basically similar. When designing the process of such products or parts, process engineers usually refer to the historical process design results of similar products to design new process routes and determine process properties and parameters. In multi-variety and small-batch manufacturing companies, process design activities for similar products are extremely frequent. Such activities require repeating some design processes that have been carried out once or even multiple times before, resulting in a waste of human resources. And due to human errors, errors may occur during the repetitive process, resulting in the design results being unable to correctly guide the manufacturing process. In order to improve the efficiency and accuracy of process design for such typical products, process engineers can integrate process routes, processes, steps, and related process requirements to form a process ontology information framework and establish process templates.

[0355] A process template can be represented by eight features:

[0356] Proc_Temp=(Proc_Temp_ID,Proc_Temp_Name,Proc_Temp_Prod_Series,Proc_Temp_Comp_Tree,Proc_Temp_Reg_Set,Proc_Temp_Conditions,Proc_Temp_Modifications,Proc_Temp_Remarks)

[0357] in,

[0358] Proc_Temp: represents the process template.

[0359] Proc_Temp_ID: indicates the process template number.

[0360] Proc_Temp_Name: indicates the name of the process template, which is usually represented by the "product series name + product instance name" corresponding to the process template, so that the technician can obtain rich information from it.

[0361] Proc_Temp_Prod_Series: represents the typical product series targeted by the process template.

[0362] Proc_Temp_Comp_Tree: represents the process composition tree of the process template, and represents the process route, process steps and working steps in the form of a tree according to the relationship between them.

[0363] Proc_Temp_Reg_Set: represents the process requirement set of the process template, which comes from the process route, process, and step contained in the process composition tree.

[0364] Proc_Temp_Conditions: Defines the specific conditions and environments in which the process template applies.

[0365] Proc_Temp_Modifications: records the modification history and reasons for changes of process templates.

[0366] Proc_Temp_Remarks: indicates the remarks of the process template.

[0367] The process template is the carrier of all the process information of the product or component to be processed at a certain production stage. The process route requirements are often generated according to the product requirements, and there is a direct relationship between the process and the manufacturing resources. Therefore, the process template is a staged integration of product information, manufacturing resource information and process information. Establishing a process template based on the typical products of the enterprise can lay the foundation for establishing a composite model of process resources.

[0368] This step describes the modeling content of complex equipment process information. The modeling and integration methods of process ontology information are introduced from the two perspectives of process composition information and process requirement information. The modeling representation of process ontology information is divided into three levels: process steps, procedures, and process routes, and is finally integrated through process templates to form a process ontology information framework for typical products, providing a carrier for realizing intelligent process design.

[0369] Step 4: Build the process resource database management module

[0370] The requirement of process resource management is to ensure that users can manage process resource data conveniently and quickly, can quickly find and apply process resources, and can modify, delete and add new process resources. Since there are many types of process resources and various types of process resources are interrelated. In the process resource management system, users need the attribute characteristics of a specific process resource object. To achieve comprehensive management of process resources, it is necessary to extract the characteristics of all process resource objects. The above describes the modeling content of various types of process resources. Each type of process resource is a model, and the management of knowledge models is the management of process resource classes. After each type of process resource is assigned an attribute value, it becomes a process resource object. The management of process objects is the management of process resource attribute values. At the same time, process resources must also support the import and export of models, realize the interaction of knowledge models with other systems, and ensure the consistency of knowledge structure attributes.

[0371] Process Resource Model Management

[0372] The process resource model can be expressed as a tree, and there are classes with different hierarchical structures in the whole tree. Each type of knowledge has its own unique attributes, and the models of knowledge objects of the same category are consistent and have the same attributes. Managing the process resource model is conducive to reducing the data redundancy of the system and improving the utilization of data. This module can also define the attribute value and attribute type of each type of knowledge. It specifically implements the functions of adding, deleting and modifying attributes. When the attributes of a certain class are edited, the attributes of its subclasses will also change with the changes of the parent class attributes. This is conducive to using the database to build a relationship model between different process resource categories and improve the application efficiency of process resources.

[0373] Process Resource Object Management

[0374] The process resource object management module is aimed at each node in the process resource structure tree. This module implements the functions of adding, editing, and deleting knowledge objects, and provides a quick data query function. When you need to edit a process resource object, you can directly modify its process resource object feature value. When adding a new process resource object, you can directly use the features of existing similar process resources and only need to enter the corresponding feature value.

[0375] (1) Database storage tools

[0376] Database selection is the basis for data storage and management. As a relational database, MySQL can be implemented with different compilers, thus ensuring the portability of its source code. It supports multi-system and multi-threaded operation, making the maximum use of the CPU. It can be used as a standalone application or as a database embedded in other software. It provides multi-language support, and common codes, such as GB2312 and BIG5 in Chinese, can be used as data table names and data column names. At the same time, it provides a variety of database interfaces, such as TCP / IP, ODBC, JDBC, etc., as well as support for large databases, and can operate large-scale data with millions of records.

[0377] (2) Complex equipment product resource management module

[0378] The modeling representation of product information includes three levels: product classification, product series and product instance. Therefore, the product information management module in the prototype system is divided into three parts: product classification management, product series management and product specification management.

[0379] Product classification management uses a tree structure to divide the products of manufacturing companies based on macro characteristics, such as function, process status, usage scenario, etc. The main functional logic of this module includes basic functions such as adding, deleting, modifying, and checking classification tree nodes.

[0380] Product series management is the management of grouping similar products. The elements of establishing a product series correspond to the model, including series name, series category, and series description. To improve the product series information, it is necessary to first establish a product attribute library and parameter library that describe product characteristics, and on this basis, configure attributes and parameters for the product series. Product specifications are instantiations of product series. The product specification management submodule is responsible for assigning values ​​to the product parameters contained in the product series to form product specification information containing a complete description of product characteristics.

[0381] The data relationship between the concepts in the above product information management module can be represented by an ER diagram (Entity Relationship Diagram), such as Figure 7 As shown in the figure. In order to more clearly show the relationship between the conceptual entities, some unimportant entity attributes are removed from the entity relationship diagram given in this article, such as the code and unit of product attributes and product parameters. The entity relationship diagram can be converted into a relational model through a formulaic method to establish a table in a relational database. This conversion process has a detailed method in the field of software engineering, which will not be repeated in this article.

[0382] The concepts of ER diagram mainly refer to entities, attributes and relationships. In ER diagram, entities are represented by rectangular boxes with the names of entities written inside the boxes. For example, in the product information management module, entities may include "product categories", "product series" and "product specifications". Attributes are represented by ellipses and connected to the corresponding entities. In the product information management module, attributes may include the name of product categories, descriptions of product series, specific parameters of product specifications, etc. In ER diagram, relationships are represented by diamonds and connected to related entities. Relationships can also have attributes to describe information related to the relationship. For example, in the product information management module, there may be relationships such as "belongs to" (product specifications belong to product series) or "contains" (product series contains product specifications).

[0383] (3) Complex equipment manufacturing resource management module

[0384] The modeling representation of manufacturing resource information includes three levels: resource classification, resource series and manufacturing resource instances. Therefore, the manufacturing resource information management module in the prototype system is divided into three parts: manufacturing resource classification management, manufacturing resource series management, and manufacturing resource specification management.

[0385] Manufacturing resource classification management uses a tree structure to divide the products of manufacturing enterprises based on macro characteristics, such as function, process status, usage scenario, etc. The main functional logic of this module includes basic functions such as adding, deleting, modifying, and checking classification tree nodes.

[0386] Manufacturing resource series management is the management of grouping similar resources. The elements of establishing a manufacturing resource series correspond to the model, including the series name, the series category, and the series description. To improve the resource series information, it is necessary to first establish a resource attribute library and parameter library that describe product characteristics, and on this basis, configure attributes and parameters for the resource series.

[0387] Manufacturing resource specifications are instantiations of resource series. The resource specification management submodule is responsible for assigning values ​​to resource parameters contained in the resource series to form resource specification information containing a complete description of resource characteristics.

[0388] The data relationship between the concepts in the above manufacturing resource information management module can be represented by an ER diagram (Entity Relationship Diagram), such as Figure 7 As shown in the figure. In order to more clearly show the relationship between the conceptual entities, some unimportant entity attributes are removed from the entity relationship diagram given in this article, such as the code and unit of manufacturing resource attributes and manufacturing resource parameters. The entity relationship diagram can be converted into a relational model through a formulaic method to establish a table in a relational database. This conversion process has a detailed method in the field of software engineering, which will not be repeated in this article.

[0389] (4) Complex equipment process information management module

[0390] The process (entity) information management module realizes the establishment and integrated application functions of the process composition information and process requirement information related models. This module mainly includes sub-modules such as process step management, process management, process route management, and process requirement management.

[0391] In the process requirement management submodule, process requirements are divided into two categories: target requirements and operation requirements, and both types of process requirements are represented by process attributes and process parameters. Since it is difficult to define whether many process requirements belong to target requirements or operation requirements, one type can be specified when creating process requirements in the system, or they can be established as general requirements. The prototype system does not distinguish between process steps, processes, and process routes for the process requirements themselves. When a process requirement is associated with a type of process component information, the process requirement under this association relationship represents the requirements of the corresponding level. During the configuration process, you can specify whether each process requirement is displayed in the final process design result, so as to take into account both the integrity of the process design and the simplicity of the design results.

[0392] After the process requirement management submodule is established, the work step management submodule can be implemented on its basis. The work step management submodule mainly includes the creation and maintenance of work steps, and the configuration management functions of work steps and work step requirements.

[0393] On the basis of the work step management submodule, the process management submodule can be further established. Since there are obvious differences in process expertise (types of work) between the processes of complex equipment, in order to further clarify the division of process types, the process management submodule needs to add a process classification function based on the process content (clamping positioning reference, processed surface and processing requirements, etc.) so that the processes can be classified and managed according to needs.

[0394] In addition to basic information such as process classification and process name, the elements for establishing process information also include process requirements, process manufacturing resources, process composition, and other elements that are linked to other types of information. The configuration of process requirements is consistent with the process step requirements and will not be repeated here. The configuration of process manufacturing resources needs to select the manufacturing resource instance suitable for implementing the process based on the actual situation. Because the specific steps used by different manufacturing resource instances to implement a certain process may be different, the process composition may be affected by the configuration of process manufacturing resources. Depending on the configuration of manufacturing resources, each process may have a series of process entities in the system.

[0395] The functions of the process route management submodule are basically the same as those of the process management submodule, except that there is no classification and manufacturing resource allocation. I will not go into details here.

[0396] The process template is an integration of process (entity) information, which includes a process route and all its processes and steps, as well as various related process requirements. The establishment of a process template needs to be associated with a typical product series.

[0397] The entity relationship diagram corresponding to the data relationship between the conceptual entities in the process information management module is as follows: Figure 8 As shown in the figure. There is a layer-by-layer relationship between process routes, processes, and steps, and the process template contains these three types of model information at the same time. Since the prototype system does not forcibly distinguish between target requirements and operation requirements, the three types of process requirements are not further divided in the figure.

[0398] If the relationship between the process template and the typical product object (series) and the relationship between the process and the manufacturing resource instance is also reflected in the ER diagram, the ER diagram of the integrated information is as follows: Fig. 9 As shown in the figure, product information is integrated with process information through the association between product series and process templates, and manufacturing resource information is integrated with process information through the association between instances and processes.

[0399] Another embodiment of the present application further includes the step of updating the database in real time:

[0400] With the development of industrial automation and intelligence, the amount of data generated in the production process has increased dramatically. This data is essential for monitoring production lines, optimizing production processes, preventing equipment failures, and improving resource utilization. In the field of industrial databases, real-time update technology mainly solves the problems of data immediacy and accuracy. Real-time update technology can ensure that these key data are reflected in the database in the latest and accurate manner, thereby providing reliable information support for decision makers. This technology can quickly respond to changes in the production site and achieve instant data writing and updating to keep the database status synchronized with the actual production status.

[0401] Industrial databases need to be updated immediately when data changes to ensure data consistency and real-time performance. This involves using triggers, event-driven architectures, and efficient data synchronization mechanisms to achieve real-time data updates. Due to the design of the database structure in this study, the data that needs to be updated in real time on the production line mainly exists in the manufacturing resource module, such as Fig.10 shown.

[0402] First, real-time update technology relies on efficient data collection mechanisms. In industrial environments, this usually involves direct integration with sensors, controllers, and other data sources. These devices monitor various parameters on the production line in real time, such as temperature, pressure, speed, etc., and send this data to the database system in the form of a stream.

[0403] Next, the data stream processing component processes these continuous data streams. This may include data cleaning, transformation, and aggregation operations to transform the corresponding data changes into feature changes in the manufacturing resource model to ensure that only relevant and accurate data is written to the database. In this step, the system listens to data change events (such as insert, update, or delete operations) through a data-driven architecture to identify and respond to specific events or data patterns, and immediately takes corresponding update actions when events occur, thereby achieving real-time updates.

[0404] Subsequently, after receiving the update request, the database management system will detect the parent category of the updated feature, determine the update location according to "process type-resource type-feature type", and handle multiple simultaneous update operations through the concurrency control mechanism to ensure data consistency and integrity, and maintain data accuracy even in a high-concurrency environment.

[0405] Finally, after the data is successfully written to the database, in order to ensure the robustness of the system and the persistence of the data, the real-time update technology also includes a data backup and recovery strategy. This means that even in the event of a system failure, the submitted updates must be permanently saved and the system can be quickly restored to the state before the failure.

[0406] In another embodiment of the present application, the process of generating a manufacturing plan based on the above database is as follows:

[0407] The ultimate goal of building a structured database is to reduce the production cost of the entire production line. In order to achieve this goal, the overall construction framework of the structured database is set for generating manufacturing solutions. In the process of determining the manufacturing solution, not only the product manufacturing demand information requirements and various types of knowledge describing the process ontology concepts are required, but also the demand for manufacturing resources for generating manufacturing solutions needs to be clarified. Connect and integrate "product-process-manufacturing resources" to provide a feasible manufacturing solution, such as Fig.11 shown.

[0408] (1) For the production and manufacturing of a specific product, first list the manufacturing solution requirements based on the bill of materials characteristics and parts characteristics of the product instance.

[0409] (2) Based on the manufacturing solution requirements, search the process ontology information database to find similar process instances. If exactly the same instance is retrieved, it can be directly borrowed. If there is a similar instance, it can be used as a reference for manufacturing solution design.

[0410] (3) During the production process analysis and manufacturing plan determination stage, in addition to considering part information and process constraints, process data and process knowledge information are considered, and more auxiliary tooling and equipment resource information is used to select idle equipment and tooling resources.

[0411] (4) During the manufacturing plan verification stage, it is necessary to consider process data and process knowledge in more detail to ensure the safe production of the manufacturing plan. After the manufacturing plan is roughly determined, it should be inspected according to the technical requirements of the product example, such as temperature adaptability.

[0412] (5) Finally, a complete process document is compiled, including process flow charts, operating procedures, and quality control plans. New process knowledge is fed back to the knowledge base to provide reference for future process design.

[0413] This application describes the modeling content of complex equipment process information. The modeling and integration methods of process ontology information are introduced from the two perspectives of process composition information and process requirement information. The modeling representation of process ontology information is divided into three levels: process steps, processes, and process routes, and is finally integrated through process templates to form a process ontology information framework for typical products, providing a carrier for realizing intelligent process design.

[0414] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.< / processi> < / stepi>

Claims

1. A method for constructing a structured database of resource models for large-scale production lines of complex equipment, characterized in that: The specific process is: Step 1: Product information modeling: Model product information into three levels: product category, product series and product instance. Product series is subordinate to product category, and product instance is subordinate to product series. Step 2: Complex equipment manufacturing resource information modeling: For each manufacturing process, a process resource information database is established to store four categories of knowledge in the process of process processing: process data, tooling knowledge, auxiliary tooling and process equipment; Step 3: Modeling of complex equipment process information: The process ontology information includes process composition information and process requirement information. When modeling, it also includes establishing the composition relationship between process composition information, the top-down hierarchical relationship between process requirement information, and the association relationship between process composition information and process requirement information. Step 4: Build the process resource database management module: The process resource database management module establishes process resource model management and process resource object management.

2. The method for constructing a structured database of a resource model for a large-scale production line of complex equipment according to claim 1, characterized in that: The step 1 includes product classification modeling, product series modeling and product instance modeling, wherein: Product classification modeling: complex equipment products are classified according to similarities in selected dimensions, forming a product classification method with clear structure and clear boundaries; Product series modeling: Group products with similar product elements into a product series. The product elements include: function, structure and process; Product instance modeling: The product BOM material list, technical requirements and product parts technical characteristics are used as features of the product instance model, where the product BOM contains all necessary raw materials and components, including their models, quantities and sources; the technical requirements contain performance standards and test conditions; the product parts technical characteristics provide detailed size, shape and material properties of each component.

3. According to the method for constructing a structured database of a resource model for a large-scale production line of complex equipment in claim 1, the second step comprises: Process data modeling, auxiliary tooling modeling, process knowledge modeling, and equipment resource modeling; Process data modeling: classify process data according to its type and purpose, and define a unified data model for each type of data. During the modeling process, define multiple key attributes, data sources and validity for the process data; Auxiliary tooling modeling: First, identify and classify the various tools and equipment used in the manufacturing process, and determine the functions and application scenarios of each type of tooling; Secondly, establish a detailed classification system to group tooling according to its function, purpose and design standards; Again, a series of key properties are defined for auxiliary tooling to fully describe its characteristics and application conditions. Process knowledge modeling: The process knowledge is summarized into three types: process decision knowledge, process instance knowledge, and auxiliary process resources. In the process of process knowledge modeling, the expert experience, factual knowledge, and procedural knowledge accumulated in the process of process design are systematically organized and digitally expressed. Equipment resource modeling: The model not only contains the basic information of the equipment, but also covers the equipment's operating status, capability parameters and remarks.

4. According to the method for constructing a structured database of a resource model for a large-scale production line of complex equipment in claim 1, the step three comprises: Process composition information modeling and process requirement information modeling; Process component information modeling includes process step information modeling, process attribute information modeling and process route information modeling; Process requirement information modeling includes process attribute feature representation, process parameter feature representation and process ontology information representation.

5. According to the method for constructing a structured database of a resource model for a large-scale production line of complex equipment in claim 1, the process resource database management module comprises: Database storage tools, complex equipment product resource management module, complex equipment manufacturing resource management module and complex equipment process information management module.

6. According to the method for constructing a structured database of a resource model for a large-scale production line of complex equipment in claim 5, the complex equipment product resource management module is used for product classification management, product series management, and product specification management; Product classification management uses a tree structure to divide the products of manufacturing companies based on macro characteristics, and is used for the basic functions of adding, deleting, modifying, and checking classification tree nodes. Product series management includes: establishing a product attribute library and parameter library that describe product features, configuring attributes and parameters for product series, assigning values ​​to product parameters included in the product series, and forming product specification information that contains complete product feature descriptions; Product specification management uses ER diagrams to represent the data relationships between concepts. Entity relationship diagrams can be converted into relational models through a formulaic method to establish tables in relational databases.

7. According to the resource model structured database construction method for complex equipment scale production line according to claim 5, the complex equipment manufacturing resource management module includes three levels: resource classification, resource series and manufacturing resource instance, which are used for manufacturing resource classification management, manufacturing resource series management and manufacturing resource specification management; Manufacturing resource classification management uses a tree structure to divide the products of manufacturing enterprises based on macro characteristics. The functional logic includes adding, deleting, modifying and checking classification tree nodes. The establishment elements of the manufacturing resource series correspond to the model, including the series name, series category, and series description. A resource attribute library and parameter library that describe product characteristics are established to configure attributes and parameters for the resource series. The resource parameters included in the manufacturing resource specification management are assigned values ​​to form resource specification information containing a complete resource feature description.

8. According to the method for constructing a structured database of a resource model for a large-scale production line of complex equipment in claim 5, the complex equipment process information management module realizes the establishment and integrated application functions of models related to process composition information and process requirement information, including work step management, process management, process route management and process requirement management submodules; In the process requirement management submodule, process requirements are divided into two categories: target requirements and operation requirements. The process requirements are associated with which type of process component information, and the process requirements under the associated relationship represent the requirements of the corresponding level. During the configuration process, it is specified whether each process requirement is displayed in the final process design result; The work step management submodule includes the creation and maintenance of work steps, and the configuration management functions of work steps and work step requirements; The process management submodule adds a process classification function based on the process content, so that the processes can be classified and managed according to needs; The functions of the process route management submodule are basically the same as those of the process management submodule, except that there is no classification and manufacturing resource allocation.

9. The method for constructing a structured database of a resource model for a large-scale production line of complex equipment according to claim 1 further comprises a database updating step, the specific process of which is: First, various parameters on the real-time monitoring production line equipment are sent to the database system in the form of streams; Secondly, the data stream is processed to convert the corresponding data changes into feature changes in the manufacturing resource model and written into the database. By monitoring data change events, specific events or data patterns are identified and responded to, and corresponding update operations are taken immediately when events occur, thereby achieving real-time updates. Thirdly, after receiving the update request, the database management system will detect the parent category of the update feature and handle multiple simultaneous update operations through the concurrency control mechanism; Finally, after the data is successfully written to the database, the data backup and recovery strategy is further updated.

10. A process design method based on the resource model structured database of any one of claims 1 to 9 for a large-scale production line of complex cost equipment, the specific process being: (1) For the production and manufacturing of a specific product, obtain the bill of materials characteristics and parts characteristics of the product instance based on the product classification information, and list the manufacturing solution requirements; (2) Based on the manufacturing solution requirements, search the process ontology information database to find similar process examples. If the same examples are found, they can be directly borrowed. If there are similar examples, they can be used as references to design manufacturing solutions. (3) In the production process analysis and manufacturing plan determination stage, on the basis of considering part information and process constraints, the process data and process knowledge in the manufacturing resource information are considered, and more auxiliary tooling and equipment resource information is applied to select idle equipment and tooling resources; (4) During the manufacturing plan verification phase, it is necessary to consider process data and process knowledge in more detail to ensure the safe production of the manufacturing plan, and after the manufacturing plan is roughly determined, it should be inspected according to the technical requirements of the product instance in the product information database; (5) Finally, a complete set of process documentation is compiled, including process flow charts, operating procedures, and quality control plans, and new process knowledge is fed back into the knowledge base to provide a reference for future process design.

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