A method for managing trial-manufacturing assembly data of a shovel

Abstract

The application discloses a kind of excavator trial production assembly data management methods, one trial production task is decomposed into multiple standard operation tasks, each operation task contains multiple standard subtasks;All subtasks of each operation task are completed, and the operation task is completed;All operation tasks of each trial production task are completed, and the trial production task is completed;For non-standard operation task, fixed data format is specified, and later algorithm is converted into standard operation task, to realize the standardized management of operation task;The key data of the application is configured in structure, and the structure data can be screened and analyzed according to the demand, the statistical law behind mining data is improved, and the data use value is improved.

Description

Technical Field

[0001] This invention relates to an assembly data management method, specifically to a method for managing assembly data during the trial production of an excavator. Background Technology

[0002] The excavator trial production and assembly process requires unified management of data such as tasks, manpower, production materials, production auxiliary materials, process and result documents, and the data must be correlated to facilitate data analysis. A large number of approval processes need to be executed throughout the entire excavator trial production and assembly process.

[0003] The existing methods for storing trial assembly data are electronic documents and paper documents. The approval process for the trial assembly process is mostly conducted offline, which has the following disadvantages:

[0004] (1) Various trial production data were not stored in a structured and information-based manner, making it impossible to conduct flexible and large-scale data analysis and mining;

[0005] (2) It is not conducive to long-term data storage and retrieval;

[0006] (3) It requires a lot of manual operation for data archiving, which is inefficient;

[0007] (4) The approval process is inefficient and information feedback is not timely. Summary of the Invention

[0008] To address the problems existing in the prior art, this invention provides a data management method for excavator trial production and assembly. A trial production task is decomposed into multiple standard work tasks, each containing various standard sub-tasks. The work task is completed when all sub-tasks of each work task are completed. For non-standard work tasks, a fixed data format is defined, and algorithms are used to convert it into standard work tasks, thus achieving standardized management of all work tasks.

[0009] To achieve the above objectives, the technical solution adopted by the present invention is: a method for managing excavator trial production and assembly data, comprising the following methods:

[0010] Step 1: First, establish the trial production master file. The master file information in the trial production master file is key structured information, which is the basic information collection of the entire trial production data.

[0011] Step 2: After the trial production master file is completed, proceed to the production material BOM import and task release stage;

[0012] Step 3: After the task is released, the task allocation stage begins. Part of the task allocation data comes from the job content data dictionary, which defines and stores job content in a standardized way. The standard job content in the job content data dictionary is selected, and the operator for each standard job content is assigned to execute the task allocation.

[0013] Step 4: When assigning tasks, you can also assign custom tasks. The format of the custom tasks should be consistent with the format of the standard tasks.

[0014] Step 5: After the task allocation is completed, the standard work content task processing and custom work content processing will begin. Each task processing includes 4 sub-processes: production log process processing, assembly record process processing, BOM usage process processing, and process exception process processing. Once all sub-processes of a standard or custom work content task processing are completed, the task processing for that work content is completed. Once all standard or custom work content task processing is completed, the trial production task is completed.

[0015] Step Six: For the customized task content, standard task content can be generated and associated later.

[0016] Furthermore, in step one, the master file information includes: the model, model type, design department, emission standard, trial production quantity, complete machine number, and trial production plan node.

[0017] Furthermore, in step two, specifically, the production material BOM is imported to generate production material BOM data. The production material BOM data originates from an existing data management system. Here, cross-platform data synchronization processing is performed. The production material BOM data has been structured and includes key structured data such as trial production section, material number, received quantity, used quantity, and adjustment quantity. The task release sends the master file information to the next stage.

[0018] Furthermore, in step three, the work content data dictionary contains two levels of nodes. The first level node is the trial production section, in string format, and the second level node is the standard work content, which is formatted as: current trial production section (first level node content) + component description (description of a component included in the current trial production section) + operation description (description of the operation action performed on the component). This dictionary can be manually expanded and maintained. One or more standard work contents can be selected from the work content data dictionary, and the operators for each standard work content can be assigned to perform task allocation.

[0019] Furthermore, in step 4, the format of the custom job content is consistent with the format of the standard job content. The custom job content contains key information blocks such as the description of the trial production section, the description of the component, and the description of the operation. The purpose of keeping the custom job content consistent with the standard custom content is to convert the large amount of accumulated custom job content into standard job content later through a text similarity algorithm.

[0020] Furthermore, in step five, the production log processing, assembly record processing, and BOM usage processing each have only one process, while the process exception processing has one or more processes with the same pattern. The production log contains key structured information such as quality control points, measuring instruments, testing standards, measurement results, and personnel working hours; the assembly record contains important structured information such as work steps and change content; the BOM usage process filters and calls production material BOM data generated from the production material BOM import stage and records the material usage; the process exception process contains key structured information such as exception type, exception component classification, exception component number, complete machine number, trial production section, work content (standard and custom), and exception system classification.

[0021] Furthermore, in step six, the custom job content in all trial production tasks forms a custom job content set. Each custom job content contains key information blocks such as trial production section description, component description, and operation description. For the custom job content set, the key information blocks are calculated and analyzed using a text similarity matching algorithm to generate one or more similar job content sets. After standard job content recommendation, each similar job content set can generate a new standard job content. After confirmation, the new standard job content is stored in the job content data dictionary. The new standard job content has an association relationship with the similar job content sets. As needed, custom job content can be replaced with standard job content.

[0022] The beneficial effects of this invention are: the key data of the trial production are configured in a structured manner, and the structured data can be filtered and analyzed according to needs to uncover the statistical patterns behind the data and improve the value of data use. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the process of the present invention;

[0024] Figure 2 This is a flowchart illustrating the data dictionary process for job content.

[0025] Figure 3 This is a flowchart illustrating a customized task. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. However, it should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of the invention.

[0027] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention.

[0028] like Figure 1 As shown, a method for managing excavator trial production and assembly data includes the following methods:

[0029] Step 1: The overall process of the data management method is as follows Figure 1 As shown, the first step is to establish the trial production master file. The master file information includes key structured information such as the model, model type, design department, emission standard, trial production quantity, complete machine number, and trial production plan nodes. It is the basic information collection of the entire trial production data.

[0030] Step 2, as follows Figure 1 As shown, after the master file for trial production is established, the process enters the stage of importing the production material BOM and issuing tasks. The production material BOM import produces production material BOM data, which comes from the existing data management system. Cross-platform data synchronization is performed here. The production material BOM data has been structured and contains key structured data such as trial production section, material number, received quantity, used quantity, and adjustment quantity. Task issuance sends the master file information to the next stage.

[0031] Step 3: After the task is published, the task allocation phase begins. Part of the task allocation data comes from the job content data dictionary, which provides standardized definitions and storage of job content. For example... Figure 2 As shown, the job content data dictionary contains two levels of nodes. The first-level nodes are the trial production sections, in string format. The second-level nodes are standard job content, formatted as: current trial production section (first-level node content) + component description (description of a component included in the current trial production section) + operation description (description of the operation actions performed on that component). This dictionary can be manually expanded and maintained. Select one or more standard job contents from the job content data dictionary, and assign personnel to each standard job content to perform task allocation.

[0032] Job Content: The smallest unit that a trial production task can be broken down into. Typically, a trial production task contains multiple job contents. Job contents are text descriptions in a fixed format. Job Content Data Dictionary: A collection of data used to store standard-format job contents. Publishing a trial production task involves selecting one or more existing standard-format job contents from this data table and publishing them.

[0033] Step 4: When assigning tasks, you can also customize the assignment of tasks. The format of the customized task content should be consistent with the format of the standard task content, such as... Figure 3 As shown: Custom job content contains key information blocks such as trial production section description, component description, and operation description. The purpose of keeping custom job content consistent with standard custom content is to later convert the large amount of accumulated custom job content into standard job content using a text similarity algorithm.

[0034] Step 5: After task allocation, proceed to standard work content task processing and custom work content processing (if custom work content has been assigned). Each task processing includes four sub-processes: production log processing, assembly record processing, BOM usage processing, and process exception processing. The first three processes have only one sub-process, while the last process has one or more sub-processes with the same pattern. The production log contains key structured information such as quality control points, measuring instruments, testing standards, measurement results, and personnel work hours; the assembly record contains important structured information such as work steps and change details; the BOM usage process filters and calls production material BOM data generated during the production material BOM import phase and records material usage; the process exception process contains key structured information such as exception type, exception component classification, exception component number, complete machine number, trial production section, work content (standard and custom), and exception system classification. Figure 1 As shown, once all sub-processes in a standard or custom job content task are completed, the job content task is completed; once all standard or custom job content tasks are completed, the trial production task is completed.

[0035] Step Six: For customized task content, standard task content can be generated and linked later. The principle is as follows... Figure 3As shown, all custom job content in the trial production tasks constitutes a custom job content set. Each custom job content contains key information blocks including a trial production section description, component description, and operation description. For each custom job content set, a text similarity matching algorithm is used to calculate and analyze the key information blocks, generating one or more similar job content sets. After standard job content recommendation, each similar job content set can generate a new standard job content. After confirmation, the new standard job content is stored in the job content data dictionary. The new standard job content has an association relationship with the similar job content sets. As needed, custom job content can be replaced with standard job content.

[0036] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions or improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for managing excavator trial production and assembly data, characterized in that, Including the following methods: Step 1: First, establish the trial production master file. The master file information in the trial production master file is key structured information, which is the basic information collection of the entire trial production data. Step 2: After the trial production master file is completed, proceed to the production material BOM import and task release stage; Step 3: After the task is released, the task allocation stage begins. Part of the task allocation data comes from the job content data dictionary, which defines and stores job content in a standardized way. The standard job content in the job content data dictionary is selected, and the operator for each standard job content is assigned to execute the task allocation. Step 4: When assigning tasks, you can also assign custom tasks. The format of the custom tasks should be consistent with the format of the standard tasks. Step 5: After the task allocation is completed, the standard work content task processing and custom work content processing will begin. Each task processing includes 4 sub-processes: production log process processing, assembly record process processing, BOM usage process processing, and process exception process processing. Once all sub-processes of a standard or custom work content task processing are completed, the task processing for that work content is completed. Once all standard or custom work content task processing is completed, the trial production task is completed. Step Six: For the custom job content, standard job content can be generated and associated later. All custom job content in the trial production tasks forms a custom job content set. Each custom job content contains key information blocks such as trial production section description, component description, and operation description. For the custom job content set, the key information blocks are calculated and analyzed using a text similarity matching algorithm to generate one or more similar job content sets. After standard job content recommendation, each similar job content set can generate a new standard job content. After confirmation, the new standard job content is stored in the job content data dictionary. The new standard job content is associated with the similar job content sets. As needed, custom job content can be replaced with standard job content.

2. The excavator trial assembly data management method according to claim 1, characterized in that, In step one, the master file information includes: model, model type, design department, emission standard, trial production quantity, complete machine number, and trial production plan milestones.

3. The excavator trial assembly data management method according to claim 1, characterized in that, In step two, specifically, the production material BOM is imported to generate production material BOM data. The production material BOM data originates from an existing data management system. Cross-platform data synchronization is performed here. The production material BOM data has been structured and includes key structured data such as trial production section, material number, received quantity, used quantity, and adjustment quantity. The task release sends the master file information to the next stage.

4. The excavator trial assembly data management method according to claim 1, characterized in that, In step three, the work content data dictionary contains two levels of nodes. The first level node is the trial production section, in string format, and the second level node is the standard work content, in the format of current trial production section + component description + operation description. This dictionary can be manually expanded and maintained. One or more standard work contents can be selected from the work content data dictionary, and the operators for each standard work content can be assigned to perform task allocation.

5. A method for managing excavator trial assembly data according to claim 1 or 4, characterized in that, In step four, the format of the custom job content is consistent with that of the standard job content. The custom job content contains key information blocks such as the description of the trial production section, the description of the component, and the description of the operation. The purpose of keeping the custom job content consistent with the standard job content is to convert the large amount of accumulated custom job content into standard job content later through a text similarity algorithm.

6. The excavator trial assembly data management method according to claim 1, characterized in that, In step five, the production log processing, assembly record processing, and BOM usage processing each have only one process, while the process exception processing has one or more processes with the same pattern. The production log contains key structured information such as quality control points, measuring instruments, testing standards, measurement results, and personnel working hours; the assembly record contains important structured information such as work steps and change content. The BOM uses filtering to retrieve production material BOM data generated during the production material BOM import phase and records material usage. Process anomalies include key structured information such as anomaly type, anomaly component classification, anomaly component number, complete machine number, trial production section, work content, and anomaly system classification.

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