Construction method of multi-granularity process knowledge base and process file configuration type compilation method

Abstract

The invention provides a construction method of a multi-granularity process knowledge base and a process file configuration type compilation method. The method is based on construction of a process model, a process step model and a process group model. A parameterized and structured work step model is formed through element combinations of different attributes; and then the plurality of process step models are combined to form the modular process model, the process content is complete and high flexibility is achieved through the process step selection units in the process step models, and the modularization degree is improved through the process group model formed by combining the process models. According to the process file configuration type compiling method, direct calling of knowledge modules with different granularities can be achieved, a process route can be rapidly formed, compiling of the process file can be rapidly and accurately completed by configuring different parameters, and meanwhile standardization and consistency of the process files compiled by different technicians can be guaranteed. According to the invention, systematic management and application of process knowledge are realized, and the process compiling efficiency and normalization are improved.

Description

Technical Field

[0001] This invention relates to the field of process knowledge management and application technology, specifically to a method for constructing a multi-granularity process knowledge base and a method for configurable compilation of process documents. Background Technology

[0002] Process documents serve as the medium for transforming product design documents into manufacturing process guidelines. Essentially, process documents describe the combination and use of resources, resource behaviors, and the parameters or quantities of resource behavior within different time periods. Therefore, the compilation of process documents can be viewed as the multi-dimensional configuration of capability units at different levels, including their types, quantities, and technical parameters. Currently, on the one hand, as the manufacturing industry shifts from a trend of few varieties and large batches to multiple varieties and small batches of personalized customization, how to quickly and accurately flexibly adapt to the process compilation needs of differentiated products has become an urgent problem to solve. However, for the manufacturing industry, its production capacity is fixed. That is, for process documents, although products may vary greatly, the description of production capacity is fixed and exhaustive. Traditional process compilation methods rely entirely on personal experience and habits. Although there are unified requirements for form and format, the expression of specific process content is inconsistent, especially the mixed use of various terms, which can easily lead to misunderstandings in subsequent work assignment and actual processing. On the other hand, with the advancement of intelligent manufacturing, data traceability throughout the product lifecycle poses a challenge to data consistency at different stages, and the multi-source and heterogeneous nature of data during product manufacturing further increases the difficulty of data consistency.

[0003] Domestic invention patent CN118296165 discloses a method for constructing a dynamic process knowledge base for a production line and a method for generating process schemes, focusing on the construction of a dynamic process knowledge base for a production line; domestic invention patent CN117666497 discloses an automatic programming method for board-type products based on process knowledge, which automatically programs different board types based on fixed product features and processing methods; domestic invention patent CN119357644 discloses a method and system for generating part processes based on a process knowledge base, mainly targeting the automatic generation of part processing processes, matching the feature process chains of processed parts through multi-domain similarity calculation, generating a set of process step sequences, and optimizing the process route through an optimization algorithm; none of these methods cover the various process knowledge required for the entire process of process document preparation. Chinese invention patent CN119917675 discloses a method, system, equipment, and medium for generating process schemes based on a knowledge base. Its process knowledge model includes processing tasks, processing resource models, and process scheme models. It generates process schemes through steps such as parsing and filtering processing task files. However, this method applies only to structural parts, limiting its applicability to certain processing methods. Furthermore, key process parameters (machining allowance for finishing, cutting tools, dimensional accuracy, cutting speed, depth of cut, feed rate, and surface roughness) are intelligently generated using deep learning methods (generative adversarial networks). However, the reliability and generalization of such methods are currently difficult to guarantee. Chinese invention patent CN202210816346 discloses a method, system, device, and computer-readable storage medium for applying process knowledge. It establishes a pre-set process knowledge base with an N-layer storage structure, using process knowledge objects (basic information, object keywords, technical keywords, and hierarchical linking relationships) as basic storage units for layered storage. It allows searching based on production object keywords according to corresponding pre-set execution logic to display the process knowledge required by the user. However, this method primarily focuses on the search and retrieval mechanism of process knowledge.

[0004] In summary, existing publicly available technologies are all unable to simultaneously satisfy the requirements of multi-dimensional consistent description of process documents, multi-granular modular management, and flexible parameterized configuration for different product characteristics. Summary of the Invention

[0005] The technical problem to be solved by this invention is how to construct a process knowledge base with diverse data information based on existing resource information. The purpose of this invention is to provide a method for constructing a multi-granularity process knowledge base and a method for compiling process documents in a configurational manner, which solves the technical problems in the prior art of difficulty in integrating resource information of different processes and obtaining a process knowledge base with comprehensive and diverse data.

[0006] This invention is achieved through the following technical solution: In a first aspect, the present invention provides a method for constructing a multi-granularity process knowledge base, comprising the following steps: S1, Constructing a process model: The process model includes multiple process step models, process name, process description, process resources, and other process attributes; Obtain and assign values ​​to the process name, process description, and other process attributes based on the current resource information, and construct the process resources according to the current resource information; The process step model includes: the process step model includes a process step name, process step constants, process step resources, a process step control parameter table, a process step evaluation parameter table, and a process step selection unit; and assigning values ​​to the process step name and process step constants based on the current resource information. Constructing a process group model includes: the process group model includes a process group name, a process group description unit, and a process model set; the process model set includes multiple process models with predecessor and successor relationships; and assigning values ​​to the process group name and the process group description unit respectively. S2, repeat step S1 until all step models, process models, and process group models are constructed based on the current resource information; S3. Check all the process step models, process models and process group models constructed in step S2. When the check results meet the preset conditions, obtain the current multi-granularity process knowledge base.

[0007] Based on the first aspect, further, the construction of the process resources according to the current resource information in step S1 includes: The process resources include a first resource table, a second resource table, a third resource table, a fourth resource table, and a fifth resource table. Based on the current resource information, values ​​are assigned to the first information in the first resource table, the second resource table, the third resource table, the fourth resource table, and the fifth resource table to complete the construction of the process resources.

[0008] Based on the first aspect, further, the construction of the process step model in step S1 also includes: The process resources include the sixth resource table that calls the assigned data from the first resource table, the seventh resource table that calls the assigned data from the second resource table, the eighth resource table that calls the assigned data from the third resource table, the ninth resource table that calls the assigned data from the fourth resource table, and the tenth resource table that calls the assigned data from the fifth resource table, in order to complete the assignment of the sixth, seventh, eighth, ninth, and tenth resource tables.

[0009] Based on the first aspect, further, the process control parameter table and the evaluation parameter table in step S1 each include one or more key-value pairs, and the keys of the key-value pairs in the process control parameter table and the evaluation parameter table are assigned values ​​based on the current resource information.

[0010] Based on the first aspect, further, the check of all the process step models, operation models, and operation group models constructed in step S2 in step S3 includes the following steps: When the only inconsistency in the assignment information between any two step models is the value of the step selection unit, the step model with the value of "no" for the step selection unit is retained.

[0011] Based on the first aspect, further, in step S3, the preset condition for the inspection result to meet the preset condition is: The preset condition is met when the assigned values ​​of any process model among all the constructed process models are not completely consistent. The preset condition is met when the assigned values ​​of any process group model among all the constructed process group models are not completely consistent.

[0012] In a second aspect, the present invention provides a method for configuring process documentation using the method described in the first aspect above, comprising the following steps: S71: Based on the current product's process requirements, select the first process model or first process group model required for the current product from the multi-granularity process knowledge base to form a process route; S72: Select the step model whose value is "No" in the step selection unit of the first process model or the first process group model to obtain the first step model required for the current product; S73: Based on the current product's process requirements, select the first data information corresponding to the first process step model, and assign values ​​to the key-value pairs in the process step control parameter table and process step evaluation parameter table in the first process step model; S74: Repeat steps S72 to S73 for the first process model or the first process group model until the current product process document is completed.

[0013] The first process model includes multiple process models; the first process group model includes multiple process group models.

[0014] Furthermore, based on the second aspect, the values ​​of the key-value pairs include numerical values, numerical ranges, strings, and null values.

[0015] Thirdly, the present invention provides an electronic device, including a memory, a processor, and a computer program, wherein the processor executes the program to implement the steps of any of the methods for constructing a multi-granularity process knowledge base in the first aspect and any of the methods for configurable compilation of process documents in the second aspect.

[0016] Fourthly, the present invention provides a storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of the method for constructing a multi-granularity process knowledge base as described in any of the first aspects and the method for configurable compilation of process documents as described in any of the second aspects.

[0017] Compared with the prior art, the present invention has the following advantages and beneficial effects: 1. The multi-granularity process knowledge base constructed by this invention can integrate current resource information. By inputting the current resource information into the corresponding process model, step model and process group model, a complete and diversified process knowledge base can be constructed.

[0018] 2. Based on the multi-granularity process knowledge base of the present invention, the present invention also constructs a configuration-based process document compilation method. During the compilation of process documents, data information in the multi-granularity process knowledge base can be quickly called up according to the data requirements of different process products. Only the data parameters related to the process products need to be selected or assigned values, which can quickly realize the personalized customization requirements of various batches of current process products, and greatly improve the compilation efficiency of process documents. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 This is a flowchart of the method for constructing a multi-granularity process knowledge base in an embodiment of the present invention; Figure 2 This is a flowchart of the process document configuration compilation method in an embodiment of the present invention. Figure 3 This is a schematic diagram illustrating the construction of the process model and the step model in an embodiment of the present invention; Figure 4 This is a schematic diagram illustrating examples of process models and step models in embodiments of the present invention; Figure 5 This is a schematic diagram of the process group model construction in an embodiment of the present invention; Figure 6 This is a schematic diagram of a process group model example in an embodiment of the present invention; Figure 7 This is a schematic diagram of the process document configuration in an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0021] Example 1 See Figure 1 This invention provides a method for constructing a multi-granularity process knowledge base, comprising the following steps: S1, Constructing a process model: The process model includes multiple process step models, process name, process description, process resources, and other process attributes; Obtain and assign values ​​to the process name, process description, and other process attributes based on the current resource information, and construct the process resources according to the current resource information; The process step model includes: the process step model includes a process step name, process step constants, process step resources, a process step control parameter table, a process step evaluation parameter table, and a process step selection unit; and assigning values ​​to the process step name and process step constants based on the current resource information. Constructing a process group model includes: the process group model includes a process group name, a process group description unit, and a process model set; the process model set includes multiple process models with predecessor and successor relationships; and assigning values ​​to the process group name and the process group description unit respectively. S2, repeat step S1 until all step models, process models, and process group models are constructed based on the current resource information; S3. Check all the process step models, process models and process group models constructed in step S2. When the check results meet the preset conditions, obtain the current multi-granularity process knowledge base.

[0022] The current resource information refers to the resources owned by the subject of this invention; this invention provides tables and fields for various resources, and during database construction, this information is maintained according to the actual resource situation of the subject.

[0023] The process constant is a textual description of the human-computer interaction process or manual operation action.

[0024] Other attributes of the process include whether it is a special process and whether it is a quality control point; the process step model set is composed of the multiple process step models; The process group description unit is the process group description.

[0025] The process name, process group description unit, and other process attributes are assigned values ​​based on the current resource information. The assignment method is as follows: the process name and process description are assigned values ​​by inputting strings, and other process attributes are assigned values ​​by checking boxes.

[0026] The step selection unit determines whether a step is mandatory. The step selection unit is assigned a value, either "yes" or "no," and cannot be empty. During the construction of the step model, if the step selection unit is "yes," the corresponding step model is invoked along with the selected process model and cannot be cancelled. If the step selection unit is "no," the corresponding step model can be selectively invoked. The step selection unit maximizes the description and scalability of the process model, reducing redundant management of similar processes.

[0027] The process control parameter table for each work step contains process parameters that can be controlled during the process, including numerical values, Boolean values, or strings; the evaluation parameter table for each work step evaluates the accuracy of the operation process and the quality of the results, including numerical values, Boolean values, or strings.

[0028] In one embodiment of this application, the step S1 of constructing the process resources based on the current resource information includes: The process resources include a first resource table, a second resource table, a third resource table, a fourth resource table, and a fifth resource table. Based on the current resource information, values ​​are assigned to the first information in the first resource table, the second resource table, the third resource table, the fourth resource table, and the fifth resource table to complete the construction of the process resources.

[0029] The first information includes the model and the corresponding name in the first resource table, the second resource table, the third resource table, and the fourth resource table, and the model, the corresponding name, and the specification information in the fifth resource table.

[0030] The first resource table is the process equipment resource table; the second resource table is the process tool resource table; the third resource table is the process fixture and jig resource table; the fourth resource table is the process gauge and measuring tool resource table; and the fifth resource table is the process auxiliary material resource table. The values ​​in the first, second, third, fourth, and fifth resource tables include multiple rows of values ​​or empty values. The specification information values ​​in the fifth resource table include multiple rows of values ​​or empty values. When multiple resources exist, the values ​​in the first, second, third, fourth, and fifth resource tables are multiple rows of values. When a certain type of resource is temporarily unavailable, the values ​​in the first, second, third, fourth, and fifth resource tables are empty values.

[0031] In one embodiment of this application, the step S1 of constructing the process model further includes: The process resources include the sixth resource table that calls the assigned data from the first resource table, the seventh resource table that calls the assigned data from the second resource table, the eighth resource table that calls the assigned data from the third resource table, the ninth resource table that calls the assigned data from the fourth resource table, and the tenth resource table that calls the assigned data from the fifth resource table, in order to complete the assignment of the sixth, seventh, eighth, ninth, and tenth resource tables.

[0032] The sixth resource table is the equipment resource table called by the work step; the seventh resource table is the tool resource table called by the work step; the eighth resource table is the tooling and fixture resource table called by the work step; the ninth resource table is the inspection and measuring tool resource table called by the work step; and the tenth resource table is the auxiliary material resource table called by the work step. The values ​​assigned to the sixth, seventh, eighth, ninth, and tenth resource tables include multiple rows of values ​​or null values. When multiple resources of the same type are required, the values ​​of the sixth, seventh, eighth, ninth, and tenth resource tables are multiple rows of values. When a certain type of resource is not required, the values ​​of the sixth, seventh, eighth, ninth, and tenth resource tables are null values.

[0033] In one embodiment of this application, the process control parameter table and the process evaluation parameter table in step S1 each include one or more key-value pairs, and the keys of the key-value pairs in the process control parameter table and the process evaluation parameter table are assigned values ​​based on the current resource information.

[0034] The values ​​in the process control parameter table and the evaluation parameter table for each work step include multiple rows of values ​​or empty values, respectively.

[0035] The values ​​of the key-value pairs include numbers, ranges of numbers, strings, and null values.

[0036] In one embodiment of this application, the step S3 of checking all the process step models, operation models, and operation group models constructed in step S2 includes the following steps: When the only inconsistency in the assignment information between any two step models is the value of the step selection unit, the step model with the value of "no" for the step selection unit is retained.

[0037] The process model check includes ensuring that the names, constants, resources, process control parameters, evaluation parameters, and selection units of any completed process model are not completely consistent. When the only inconsistency between the step models within any completed process model is the value of the selection unit, only the step model with the value of "No" for the selection unit is retained. If the values ​​of the selection units are inconsistent, i.e., one selection unit is "Yes" and the other is "No", the step model with the value of "No" for the selection unit is retained. The more non-mandatory steps are retained, the greater the flexibility of the process.

[0038] In one embodiment of this application, the preset condition for the inspection result to meet the preset condition in step S3 is: The preset condition is met when the assigned values ​​of any process model among all the constructed process models are not completely consistent. The preset condition is met when the assigned values ​​of any process group model among all the constructed process group models are not completely consistent.

[0039] In one embodiment of this application, the specific construction content of the process model and the process step model is as follows: See Figure 3 Create a new process model, fill in the process name and process description for the current process; select other attributes of the process; fill in the model, corresponding name, and specification information of the first, second, third, fourth, and fifth resource tables corresponding to the process resources; construct the step model under the current process one by one, fill in the key in the key-value pair of step name, step constant, step process control parameter, and step evaluation parameter, and confirm the value of the step selection unit; select the sixth, seventh, eighth, ninth, and tenth resource tables in the step resource tables (the selectable content in each table comes from the assignment information corresponding to the first, second, third, fourth, and fifth resource tables in the process resources).

[0040] See Figure 4 This is an instance of the completed process model and the corresponding process step model.

[0041] In one embodiment of this application, the process of constructing the process group model is as follows: See Figure 5 Create a new process group model, fill in the process group name and process group description unit for the current process group; select and combine the existing process models to form a process model set.

[0042] See Figure 6 This is to construct a complete process group model.

[0043] See Figure 2 This invention provides a method for configurable preparation of process documents, comprising the following steps: S71: Based on the current product's process requirements, select the first process model or first process group model required for the current product from the multi-granularity process knowledge base to form a process route; S72: Select the step model whose value is "No" in the step selection unit of the first process model or the first process group model to obtain the first step model required for the current product; S73: Based on the current product's process requirements, select the first data information corresponding to the first process step model, and assign values ​​to the key-value pairs in the process step control parameter table and process step evaluation parameter table in the first process step model; S74: Repeat steps S72 to S73 for the first process model or the first process group model until the current product process document is completed.

[0044] The process requirements of the current product refer to the product design information (including drawings and special performance requirements, or other design data that can reflect the product structure and special performance). For example, if the current product is a mechanical structural component, then it can be a two-dimensional or three-dimensional design file containing information such as dimensions, precision markings and special process requirements (annealing).

[0045] The first data information includes data information in the sixth, seventh, eighth, ninth, and tenth resource tables under the process resources corresponding to the first process model.

[0046] In one embodiment of this application, the value of the key-value pair includes a number, a range of numbers, a string, and a null value.

[0047] In one embodiment of this application, the process document preparation process is as follows: See Figure 7 Enter the product drawing number corresponding to the current process document; build the process route by selecting the required process model or process group model from the established multi-granularity process knowledge base, and sort the process model and process group model. Configure the parameters of each step model under the selected process model or process group model, including selecting the value of the step selection unit, and entering the values ​​in the key-value pairs of the step process control parameters and step evaluation parameters (which can be empty). Make the final selection of step resources based on the actual product; steps that need to be reused can be copied, but other content outside the step selection unit must be changed.

[0048] In one embodiment of this application, during the configuration of the process document, the step model whose step selection unit value is "yes" in the selected process model and process group model cannot be deleted; the called step model can be copied within the selected process model, but at least one of the following must be modified in the copied step model: step name, step constant, step resource, step process control parameter table, step evaluation parameter table, and step selection unit value.

[0049] This invention provides a method for constructing a multi-granularity process knowledge base and a configurable process document compilation method. It integrates current resource information by establishing step models, process models, and process group models. Through the combination of elements with different attributes, a parameterized and structured step model is formed. Multiple step models are then combined to form a modular process model. The mandatory / non-mandatory attribute of the step model ensures the completeness and high flexibility of the process content. The fixed combination of process models to form process group models further enhances the degree of modularity. The proposed configurable process document compilation method enables direct access to knowledge modules of different granularities, quickly forming process routes. By configuring different parameters, process document compilation can be completed quickly and accurately, while ensuring the standardization and consistency of process documents compiled by different process engineers. This method achieves systematic management and application of process knowledge, improving the efficiency and standardization of process compilation.

[0050] Thirdly, embodiments of the present invention provide an electronic device, including a memory, a processor, and a computer program, wherein the processor executes the program to implement the steps of any of the methods for constructing a multi-granularity process knowledge base in the first aspect and any of the methods for configurable compilation of process documents in the second aspect.

[0051] Fourthly, embodiments of the present invention provide a storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of any of the methods for constructing a multi-granularity process knowledge base in the first aspect and any of the methods for configuring process documents in the second aspect.

[0052] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for constructing a multi-granularity process knowledge base, characterized in that, Includes the following steps: S1, Constructing a process model: The process model includes multiple process step models, process name, process description, process resources, and other process attributes; Obtain and assign values ​​to the process name, process description, and other process attributes based on the current resource information, and construct the process resources according to the current resource information; The process step model includes: the process step model includes a process step name, process step constants, process step resources, a process step control parameter table, a process step evaluation parameter table, and a process step selection unit; and assigning values ​​to the process step name and process step constants based on the current resource information. Constructing a process group model includes: the process group model includes a process group name, a process group description unit, and a process model set; the process model set includes multiple process models with predecessor and successor relationships; and assigning values ​​to the process group name and the process group description unit respectively. S2, repeat step S1 until all step models, process models, and process group models are constructed based on the current resource information; S3. Check all the process step models, process models and process group models constructed in step S2. When the check results meet the preset conditions, obtain the current multi-granularity process knowledge base.

2. The method for constructing a multi-granularity process knowledge base according to claim 1, characterized in that, The step S1 of constructing the process resources based on the current resource information includes: The process resources include a first resource table, a second resource table, a third resource table, a fourth resource table, and a fifth resource table. Based on the current resource information, values ​​are assigned to the first information in the first resource table, the second resource table, the third resource table, the fourth resource table, and the fifth resource table to complete the construction of the process resources.

3. The method for constructing a multi-granularity process knowledge base according to claim 2, characterized in that, The construction of the process model in step S1 also includes: The process resources include the sixth resource table that calls the assigned data from the first resource table, the seventh resource table that calls the assigned data from the second resource table, the eighth resource table that calls the assigned data from the third resource table, the ninth resource table that calls the assigned data from the fourth resource table, and the tenth resource table that calls the assigned data from the fifth resource table, in order to complete the assignment of the sixth, seventh, eighth, ninth, and tenth resource tables.

4. The method for constructing a multi-granularity process knowledge base according to claim 1, characterized in that, The process control parameter table and the process evaluation parameter table in step S1 each include one or more key-value pairs. The keys of the key-value pairs in the process control parameter table and the process evaluation parameter table are assigned values ​​based on the current resource information.

5. The method for constructing a multi-granularity process knowledge base according to claim 1, characterized in that, The step S3, which checks all the process step models, operation models, and operation group models constructed in step S2, includes the following steps: When the only inconsistency in the assignment information between any two step models is the value of the step selection unit, the step model with the value of "no" for the step selection unit is retained.

6. The method for constructing a multi-granularity process knowledge base according to claim 1, characterized in that, In step S3, the preset condition for the inspection result to meet the preset condition is: The preset condition is met when the assigned values ​​of any process model among all the constructed process models are not completely consistent. The preset condition is met when the assigned values ​​of any process group model among all the constructed process group models are not completely consistent.

7. A method for preparing process documents using the method described in any one of claims 1-6, characterized in that, Includes the following steps: S71: Based on the current product's process requirements, select the first process model or first process group model required for the current product from the multi-granularity process knowledge base to form a process route; S72: Select the step model whose value is "No" in the step selection unit of the first process model or the first process group model to obtain the first step model required for the current product. S73: Based on the current product's process requirements, select the first data information corresponding to the first process step model, and assign values ​​to the key-value pairs in the process step control parameter table and process step evaluation parameter table in the first process step model; S74: Repeat steps S72 to S73 for the first process model or the first process group model until the current product process document is completed.

8. The method for configuring process documents according to claim 7, characterized in that, The values ​​of the key-value pairs include numbers, ranges of numbers, strings, and null values.

9. An electronic device, comprising a memory, a processor, and a computer program, characterized in that, When the processor executes the program, it implements the steps of the method for constructing a multi-granularity process knowledge base as described in any one of claims 1 to 6 and the method for configurable compilation of process documents as described in any one of claims 7 to 8.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for constructing a multi-granularity process knowledge base as described in any one of claims 1 to 6 and the method for configurable compilation of process documents as described in any one of claims 7 to 8.

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