Intermittent production workshop management system

Abstract

The invention discloses an intermittent production workshop management system, which comprises the following modules: 1) a basic data module for storing and managing basic data required by an intermittent production workshop; (2) a product dispatching module which is used for distributing intermittent production tasks of sales orders to each piece of production equipment and employees according to the basic data; 3) a work report settlement module which is used for recording intermittent production conditions and carrying out salary settlement; the production condition comprises production quantity, production time and production equipment state; the salary settlement comprises timing settlement and piece counting settlement; and 4) an analysis early warning module which is used for analyzing the production data and discovering potential problems in the production process in time. The intermittent production workshop management system has the advantages of being graphical, intelligent and high in efficiency.

Description

Technical Field

[0001] The invention relates to a management information system, in particular to an intermittent production workshop management system. Background Art

[0002] The continuous production process refers to the continuous conversion of raw materials into products through various special equipment, and each process is in a stable working state. In contrast, the intermittent production process, also known as the batch production process, consists of one or more processes in a certain order. The workshop produces different products, and the processes of different products or each batch of products are different. The production equipment composition and various operating conditions are determined according to the pre-established clear goals and tasks, and the production tasks are allocated, and production arrangements, coordination, and implementation are carried out. Intermittent production workshop management is a core component of the intermittent production manufacturing industry management system. However, there are some problems with the traditional intermittent production workshop management model, including:

[0003] 1) Poor information sharing: Traditional systems mostly rely on paper documents or isolated electronic systems to record various information about equipment, employees and workshops, which greatly hinders the circulation and sharing of information. The lack of effective information integration and sharing mechanisms between departments can easily lead to information gaps, thereby reducing overall work efficiency.

[0004] 2) Decision-making relies on experience: In key links such as process planning and product dispatch, the traditional model often relies too much on the personal experience of managers, while ignoring the widespread application of modern management methods and intelligent technologies. This practice not only limits the improvement of production efficiency, but may also cause unnecessary losses to the company due to wrong decisions.

[0005] 3) Insufficient monitoring capabilities: Traditional systems generally lack real-time monitoring functions and are unable to capture subtle changes in the operating status of equipment and production progress in a timely manner. This leads to delayed problem discovery and makes it difficult for leaders at all levels to quickly grasp the on-site situation, which in turn affects production efficiency and the accuracy of decision-making.

[0006] 4) Lack of early warning mechanism: Due to the lack of an effective early warning mechanism, the traditional workshop management system cannot detect potential production anomalies in advance, such as delayed progress, cost overruns, etc. Once these potential problems break out, they often have a serious impact on the company's production plan and cost control.

[0007] In view of the above problems, an intermittent production workshop management system is needed to comprehensively optimize all aspects of traditional intermittent production workshop management. Summary of the invention

[0008] In order to make full use of modern information technology and intelligent algorithms to achieve comprehensive upgrades in information sharing, decision optimization, real-time monitoring and early warning mechanisms, thereby promoting the development of manufacturing industry in a more efficient and intelligent direction, the present invention provides an intermittent production workshop management system, including the following modules:

[0009] 1) Basic data module, used to store and manage basic data required for intermittent production; the basic data module includes process data, employee data and workshop data;

[0010] 2) A product dispatching module, which is used to allocate intermittent production tasks of sales orders to various production equipment and employees based on the basic data;

[0011] 3) Work report settlement module: used to record intermittent production conditions and perform salary settlement. The production conditions include production quantity, production time, and production equipment status; the salary settlement includes time settlement and piecework settlement;

[0012] 4) Analysis and early warning module: used to analyze production data and promptly identify potential problems in the production process.

[0013] Preferably, the basic data module includes:

[0014] 1) Process data module, used to manage and maintain process data, including process name, number, required equipment, and standard working hours;

[0015] 2) Employee data module, used to manage and maintain employee data, including name, number, position, skills, attendance, working hours, and performance;

[0016] 3) Workshop data module: used to manage and maintain workshop data, which includes workshop name, number, area, equipment configuration, and applicable processes.

[0017] Preferably, the product dispatching module includes:

[0018] 1) Finished product process planning module: used to determine the process flow of finished product production, which includes design requirements, production materials, process steps and quality standards;

[0019] 2) Process dispatch module: used to decompose production tasks into specific processes and assign them to appropriate workshops and equipment based on the information provided by the finished product process planning module;

[0020] 3) Employee dispatch module: used to assign process tasks to appropriate employees based on the process allocation information provided by the process dispatch module.

[0021] Preferably, the working steps of the finished product process planning module include:

[0022] 1) Conduct process analysis on the finished product produced intermittently to determine all the steps required to produce the finished product;

[0023] 2) Determine the process connection relationship and construct the adjacency matrix;

[0024] 3) Establishing a process planning diagram based on the adjacency matrix; the process planning diagram is a bar chart or a double-code network diagram.

[0025] Preferably, the process planning diagram includes establishing a bar chart using a critical path algorithm and a precedence diagram algorithm, the steps comprising:

[0026] 1) Determine the nodes representing the process and their logical relationships;

[0027] 2) Determine the dependencies between processes based on the logical relationships in the adjacency matrix;

[0028] 3) Calculate the process time parameters; the time parameters include the earliest start time, the earliest end time, the latest start time and the latest end time;

[0029] 4) Compare the earliest and latest time parameters of each process to find the critical path without floating time;

[0030] 5) Draw a Gantt chart on the Gantt chart template.

[0031] Preferably, the process planning diagram is established by using a depth-first search algorithm or a breadth-first search algorithm to establish a dual-code network diagram; the steps of using the depth-first search algorithm include:

[0032] 1) Set a flag for each vertex to indicate whether it has been visited, and then set up a recursive stack to track the currently visited path;

[0033] 2) Select the starting vertex, mark it as visited, traverse the adjacency matrix, and find the vertices connected to the starting vertex that have not been visited;

[0034] 3) For each vertex found, recursively execute the previous step, that is, use it as the new starting vertex for depth-first search; when the current vertex has no more unvisited adjacent points, backtrack to the previous vertex and continue to search for other unvisited adjacent points;

[0035] 4) Map each visited vertex as a node, and map the connection relationship between vertices as arrows, annotate the process information and duration to establish a double-code network diagram.

[0036] Preferably, the process dispatching module uses a scheduling algorithm based on priorities and constraints for calculation, and the steps include:

[0037] 1) Read basic data and determine priorities and constraints;

[0038] 2) Generate an initial process dispatching plan using a heuristic algorithm based on priorities and constraints; the heuristic algorithm includes a greedy algorithm and a simulated annealing algorithm;

[0039] 3) Using an optimization algorithm to optimize the initial process dispatching plan; the optimization algorithm is a genetic algorithm or a linear programming algorithm.

[0040] Preferably, the work reporting and settlement module includes:

[0041] 1) Production progress recording module: used to fill in progress information according to the requirements of the production work order and the actual production situation; the progress information includes production quantity, production time, and production equipment used;

[0042] 2) Salary settlement module: used for time-based settlement or piece-rate settlement based on progress information.

[0043] Preferably, the analysis and early warning module includes:

[0044] 1) Data collection and analysis module: used to collect data from the basic data module, product dispatch module and work report and settlement module and conduct statistical analysis;

[0045] 2) Abnormal detection and early warning module: used to identify abnormal situations in intermittent production processes and trigger early warning mechanisms based on the results of data analysis;

[0046] 3) Trend forecasting and optimization suggestion module: used to predict future production trends based on historical data, help enterprises formulate response strategies in advance, and make optimization suggestions.

[0047] The present invention has the following beneficial effects:

[0048] 1) Create a process planning diagram, use the critical path algorithm and the precedence diagram algorithm to create a bar chart, or use the depth-first search algorithm or the breadth-first search algorithm to create a double-code network diagram.

[0049] 2) Using a priority and constraint-based scheduling algorithm, the production tasks are broken down into specific processes and assigned to appropriate workshops and equipment based on the information provided by the finished product process planning module.

[0050] 3) Integrate various information of intermittent production workshops, scientifically manage and make decisions, and issue early warnings for risks.

[0051] The intermittent production workshop management system of the present invention has the characteristics of being graphical, intelligent and highly efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a module block diagram of an intermittent production workshop management system according to an embodiment of the present invention;

[0053] Figure 2 This is an example of inputting a process data module of an intermittent production workshop management system according to an embodiment of the present invention;

[0054] Figure 3 This is an example of inputting employee data module of an intermittent production workshop management system according to an embodiment of the present invention;

[0055] Figure 4 This is an input example of a finished product process planning module of an intermittent production workshop management system according to an embodiment of the present invention;

[0056] Figure 5 This is an example of a work order dispatching system for an intermittent production workshop according to an embodiment of the present invention;

[0057] Figure 6 This is an example of a work report on a computer terminal of an intermittent production workshop management system according to an embodiment of the present invention;

[0058] Figure 7 This is an example of a mobile terminal reporting work in an intermittent production workshop management system according to an embodiment of the present invention;

[0059] Figure 8 This is an example of piecework settlement in an intermittent production workshop management system according to an embodiment of the present invention;

[0060] Fig. 9 This is an output example of an analysis and warning module of an intermittent production workshop management system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0061] In order to further understand the present invention, preferred embodiments of the present invention are described below in conjunction with examples. However, it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, rather than limiting the claims of the present invention.

[0062] The present invention provides an intermittent production workshop management system, such as Figure 1 As shown, it includes basic data module, product dispatch module, work reporting and settlement module, analysis and early warning module, etc. Each module is further explained below.

[0063] The basic data module of the embodiment of the present invention is the support of the intelligent intermittent production workshop management system, including:

[0064] 1) Process data module. Manage and maintain detailed data of each process, including process name, number, required equipment, standard working hours, etc. It supports the import, export and modification of process data, and facilitates data update and maintenance. Figure 2 shown.

[0065] 2) Employee data module. Store and manage employee personal information, such as name, number, position, skills, etc. It can also record employee attendance, working hours, performance and other data to provide a basis for human resource management. It supports the query and statistics of employee data, making it easier for management to understand employee situations. The input of the employee data module is as follows: Figure 3 Shown

[0066] 3) Workshop data module. Collect and manage the overall information of the workshop, including the workshop name, number, area, equipment configuration, applicable processes, etc., and monitor the production status of the workshop, such as output, quality, efficiency, etc. Provide a visual display of the workshop to facilitate the management to intuitively understand the production status of the workshop.

[0067] The product dispatching module of the embodiment of the present invention dispatches the sales orders of intermittent production to specific workshops and processes, and further to specific employees, to ensure the smooth implementation of the production plan. The product dispatching module includes:

[0068] 1) Finished product process planning module.

[0069] The finished product process planning module is mainly responsible for the process design and planning of the product to ensure that the product can be produced according to the predetermined process and quality standards. According to the product characteristics and production requirements, a detailed process route and operation process are formulated. The sequence of each process, the required equipment and working hours, etc. are determined. The query and modification functions of process data are provided to facilitate process personnel to adjust and optimize according to actual conditions. The input example of the finished product process planning module is as follows: Figure 4 As shown, the working steps of the post-input module include:

[0070] a) Determine the processes required for the finished product. Conduct a detailed process analysis of the finished product produced intermittently to determine all the processes required to produce the finished product. Each process should clearly define its specific operation content, required equipment, tools, materials and quality standards. This is the basis for formulating the production process flow to ensure the integrity and continuity of the production process. It helps to determine the connection relationship between subsequent processes and the effective allocation of resources.

[0071] b) Determine the connection relationship between processes and construct an adjacency matrix. Analyze the sequence and logical relationship between processes to determine which processes are the previous processes and which are the next processes. Construct an adjacency matrix based on the connection relationship between processes. An adjacency matrix is ​​a matrix that represents the relationship between processes, where rows and columns represent different processes, and the elements in the matrix represent the connection relationship between processes. The adjacency matrix is ​​the basis for developing a production process flow chart and conducting network planning analysis. It helps to clarify the dependency relationship between processes and provides important data support for the subsequent establishment of a process planning chart.

[0072] c) Establish process planning diagram.

[0073] According to the determined processes and their connection relationships, select appropriate graphical representation methods, such as bar charts or double-code network diagrams, to establish process planning diagrams. Bar charts use horizontal bars to represent the start time, end time, and duration of each process. It is intuitive and easy to understand, allowing project team members to quickly understand the project progress. Double-code network diagrams use nodes to represent processes and arrows to represent the logical relationship between processes. It can clearly show the sequence and dependency between processes, which is helpful for network planning analysis and optimization. In the process planning diagram, the name, start time, end time, duration, and connection relationship of each process can be clearly marked.

[0074] The embodiment of the present invention uses the critical path algorithm and the predecessor graph algorithm to establish a bar graph based on the adjacency matrix. The steps include:

[0075] i) Determine nodes and logical relationships. Use nodes to represent processes, and arrows to represent logical relationships between processes. Based on the adjacency matrix, generate processes as nodes in the graph, use arrows to connect nodes with logical relationships, and mark the duration of the processes to form a precedence graph.

[0076] ii) Determine the dependencies. Determine the dependencies between processes based on the logical relationships in the adjacency matrix and represent them with arrows in the precedence diagram. Dependencies include finish-start (FS), finish-finish (FF), start-start (SS) and start-finish (SF).

[0077] iii) Calculate time parameters: Calculate the earliest start time (ES), earliest end time (EF), latest start time (LS) and latest end time (LF) of each process.

[0078] ⅳ) Identify the critical path. The critical path is the longest path from the beginning to the end of the project, which determines the shortest completion time of the project. In the precedence diagram, by calculating and comparing the earliest and latest time parameters of each process, find the process sequence without floating time, that is, the critical path.

[0079] ⅴ) Draw a bar chart. Prepare a bar chart template. The horizontal axis represents time, usually using calendar days or working days. List all the processes on the vertical axis, arranged in the logical order of their use in the finished product process planning. Draw a corresponding bar chart on the horizontal axis according to the start and end time of each process. The length of the bar chart represents the duration of the activity. Different colors or markers can be used to distinguish between activities on the critical path and activities on the non-critical path.

[0080] The embodiment of the present invention can also use a depth-first search algorithm or a breadth-first search algorithm to establish a dual-code network graph based on the adjacency matrix. For example, the steps of using the depth-first search algorithm include:

[0081] i) Initialize the search state. Set a visit flag for each vertex to record whether the vertex has been visited. For the depth-first search algorithm, set a recursive stack or recursive function to track the currently visited path.

[0082] ii) Select vertex 0 as the starting point, visit the starting vertex, and mark it as visited. Traverse the adjacency matrix to find the vertices connected to the starting vertex that have not been visited.

[0083] ⅲ) For each vertex found, recursively perform the above steps, i.e., use it as the new starting vertex for depth-first search. When the current vertex has no more unvisited adjacent points, backtrack to the previous vertex and continue to search for other unvisited adjacent points. During the search, record the order of the visited vertices to form a path.

[0084] iv) Each visited vertex can be mapped as a node, and the connection relationship between vertices can be mapped as arrows. The process information, duration and other information can be marked to establish a double-code network diagram.

[0085] The process planning chart is an important basis for production progress control and resource allocation. It helps project managers and team members to intuitively understand the progress of the entire production process and the dependencies between various processes. Through the process planning chart, potential problems in the production process can be discovered and solved in a timely manner, ensuring that the project can proceed smoothly as planned, and providing strong support for production progress control and optimization.

[0086] The finished product process planning module completes the above work, ensures the integrity and continuity of the production process, clarifies the dependencies between processes, and provides important data support and graphical representation methods for production progress control and resource allocation.

[0087] 2) Process dispatching module: This module is responsible for allocating production tasks to specific workshops and processes according to the requirements and connection sequence of the processes.

[0088] The process dispatch module first receives the production task information from the product dispatch module, which already includes the required processes and their sequence. Based on the workshop data in the basic data module, including the workshop's production capacity, equipment configuration, available time, etc., the process dispatch module matches each process in the production task with the appropriate workshop.

[0089] The process dispatch module can use an optimization algorithm to dispatch orders, and the algorithm used can also be used in the subsequent employee dispatch module. For example, a scheduling algorithm based on priority and constraints is used to comprehensively consider the priority of production tasks, the connection relationship between processes, equipment capabilities, employee skills and other constraints, and an optimization algorithm is used to generate an optimal or approximately optimal process dispatch plan. The steps include:

[0090] 1) Read basic data and determine priorities and constraints. Obtain process data, employee data, and workshop data from the basic data module. Set priorities for each production task based on factors such as order urgency, customer demand, and production cycle. Priorities can be numerical, with smaller values ​​indicating higher priorities. Identify and list all constraints that may affect process dispatch, such as equipment capacity, employee skills, and the connection between processes.

[0091] 2) Use heuristic algorithms to generate the initial process dispatch plan. Create a schedule to record when each production task is completed, by which workshop and process. Calculate the time required for each process based on the information in the process data module. Consider the impact of factors such as equipment efficiency and employee proficiency on process time. Based on priorities and constraints, use heuristic algorithms, such as greedy algorithms, simulated annealing algorithms, etc., to quickly generate an initial process dispatch plan.

[0092] 3) Use optimization algorithms to optimize the initial process dispatch plan. The optimization algorithm can use genetic algorithms or linear programming to optimize the initial process dispatch plan. The goal of optimization is to maximize production efficiency, minimize production costs, or meet the production goals of special orders. Output the optimized process plan to the schedule.

[0093] The process dispatch module will assign production tasks to specific workshops and processes and generate corresponding dispatch orders. Figure 5 These dispatch orders contain detailed information about the finished products to be produced and their quantity, process information, production requirements, expected completion time, etc., providing clear guidance for the production activities of the workshop.

[0094] The process dispatch module can ensure that production tasks are completed efficiently through intelligent matching and sorting. This reduces waiting time and resource waste in the production process and improves overall production efficiency. The process dispatch module can make full use of workshop resources, such as equipment, manpower, etc. Through reasonable task allocation and process connection, the module can ensure the effective use of resources and maximize output. The process dispatch module can ensure that production tasks are carried out in accordance with the established process plan and process sequence, which helps to reduce errors and defects in the production process and improve the quality stability and consistency of products.

[0095] 3) Employee dispatch module. Responsible for further dispatching processes to employees based on process requirements and employee skills. Work performed by the employee dispatch module includes:

[0096] a) Employee skills matching:

[0097] The employee dispatch module will first retrieve the information of employees with corresponding skills from the employee data module according to the requirements of the process. Through intelligent algorithms, the module will conduct a comprehensive assessment of factors such as employee skill level, work experience, and work efficiency to ensure that the process is assigned to the most suitable employee.

[0098] b) Process allocation and scheduling:

[0099] After the appropriate employees are identified, the employee dispatch module will assign specific process tasks to the corresponding employees according to the process connection sequence and production plan. The module will generate a detailed dispatch sheet, including key information such as process name, task description, completion time requirements, etc., so that employees can clearly understand their work tasks.

[0100] c) Real-time monitoring and adjustment:

[0101] During the production process, the employee dispatch module will monitor the employee's task completion status in real time, including progress, quality, etc. If an abnormal situation is found, such as employees failing to complete tasks on time or quality not meeting standards, the module will make timely adjustments, such as reallocating tasks, providing technical support, etc., to ensure the smooth progress of the production plan.

[0102] The employee dispatch module can ensure that each employee can play the greatest role in the field he or she is good at through matching and scheduling, thereby improving overall production efficiency. The employee dispatch module can optimize the allocation of human resources, reduce the waste of human resources, and improve resource utilization and output efficiency.

[0103] The work report settlement module of the embodiment of the present invention is responsible for recording the working hours and output of employees, and making settlements based on the working hours and output. Employees can report work and record working hours and output through mobile devices or terminals. The system automatically calculates settlement data such as employees' wages and bonuses. It provides query and statistics functions for report data, which facilitates management to understand employees' production conditions and settlement data. The input of the work report settlement module can be through the computer terminal and mobile terminal, and the interface is as follows: Figure 6 and Figure 7 shown.

[0104] The work report and settlement module includes:

[0105] 1) Production progress recording module.

[0106] The workshop manager fills in relevant information such as production quantity, production time, production equipment status, etc. according to the requirements of the production work order and the actual production situation.

[0107] 2)Salary settlement module.

[0108] There may be different types of work and tasks of different nature and difficulty in the workshop, so salary settlement can be divided into time-based settlement and piece-rate settlement. In the time-based settlement mode, the system will calculate the salary based on the employee's actual working time, including overtime, rest and other time periods. In the piece-rate settlement mode, employees will receive corresponding piece-rate wages for each qualified product they complete. When approving, the quality inspector will select the wage type according to the actual situation and enter the number of unqualified products to ensure the accuracy of the salary settlement. An example of piece-rate settlement is shown in Figure 8.

[0109] The work report and settlement module updates the progress of production orders in real time, so that managers can clearly understand the completion of production tasks, discover potential production bottlenecks in time, and make targeted adjustments. The timeliness of salary settlement can motivate employees to work harder and improve production efficiency. The work report and settlement module provides various data in the production process, such as output, quality, cost, etc., which can provide decision support for managers. Managers can optimize resource allocation such as production planning, staffing and equipment use based on these data to improve the overall efficiency of the enterprise.

[0110] The analysis and early warning module of the embodiment of the present invention conducts in-depth analysis of production data, timely discovers potential problems and risks, and provides early warning information. Real-time monitoring and analysis of production data, such as output, quality, efficiency, etc. Based on the analysis results, problems and risks in the production process are discovered in a timely manner, and early warning information, such as progress warning, cost warning, etc., is provided, so that the management can take timely measures to deal with them. Fig. 9 is an example of a warning.

[0111] The analysis and warning module of the embodiment of the present invention includes:

[0112] 1) Data collection and analysis module.

[0113] The analysis and early warning module collects a large amount of production data from the basic data module, product dispatch module, and work report and settlement module. These data include process progress, employee work efficiency, equipment operation status, production quality indicators, etc. The module conducts in-depth analysis of these data to identify potential problems and optimization space in the production process.

[0114] 2) Abnormal detection and early warning module.

[0115] Based on the results of data analysis, the analysis and early warning module can identify abnormal situations in the production process, such as production schedule delays, cost overruns, etc. Once an abnormal situation is detected, the module will immediately trigger the early warning mechanism and send early warning information to relevant personnel through a visual interface, SMS, email, etc.

[0116] 3) Trend prediction and optimization suggestion module.

[0117] In addition to real-time anomaly detection, the analysis and early warning module can also predict future production trends based on historical data. These prediction results help companies formulate response strategies in advance to avoid potential production risks. At the same time, the module will also make optimization suggestions based on the analysis results, such as adjusting production plans, optimizing resource allocation, etc., to further improve production efficiency and quality.

[0118] The analysis and early warning module uses real-time data analysis and early warning to enable enterprises to promptly discover and solve problems in the production process, avoiding production delays and waste of resources. This helps to improve overall production efficiency and reduce production costs. Through data analysis, enterprises can more accurately understand the resource requirements in the production process, thereby making more reasonable resource allocation. The data and analysis results provided by the analysis and early warning module can provide strong support for the decision-making of enterprises. Enterprises can formulate more scientific production plans, sales strategies, etc. based on these data to improve overall operational efficiency and market response speed.

[0119] To sum up, the various modules of the intelligent intermittent production workshop management system cooperate with each other to jointly realize the comprehensive monitoring and management of the production process of the intermittent production workshop, which can improve production efficiency, reduce costs and improve product quality.

[0120] The above embodiments are only used to help understand the method and core idea of ​​the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

Claims

1. An intermittent production workshop management system, characterized in that: Includes the following modules: 1) Basic data module, used to store and manage basic data required for intermittent production; the basic data module includes process data, employee data and workshop data; 2) A product dispatching module, which is used to allocate intermittent production tasks of sales orders to various production equipment and employees based on the basic data; 3) Work report settlement module: used to record intermittent production conditions and perform salary settlement. The production conditions include production quantity, production time, and production equipment status; the salary settlement includes time settlement and piecework settlement; 4) Analysis and early warning module: used to analyze production data and promptly identify potential problems in the production process.

2. The intermittent production workshop management system according to claim 1, characterized in that: The basic data module includes: 1) Process data module, used to manage and maintain process data, including process name, number, required equipment, and standard working hours; 2) Employee data module, used to manage and maintain employee data, including name, number, position, skills, attendance, working hours, and performance; 3) Workshop data module: used to manage and maintain workshop data, which includes workshop name, number, area, equipment configuration, and applicable processes.

3. The intermittent production workshop management system according to claim 1 is characterized in that: The product dispatching module includes: 1) Finished product process planning module: used to determine the process flow of finished product production, which includes design requirements, production materials, process steps and quality standards; 2) Process dispatch module: used to decompose production tasks into specific processes and assign them to appropriate workshops and equipment based on the information provided by the finished product process planning module; 3) Employee dispatch module: used to assign process tasks to appropriate employees based on the process allocation information provided by the process dispatch module.

4. The intermittent production workshop management system according to claim 3 is characterized in that: The working steps of the finished product process planning module include: 1) Conduct process analysis on the finished product produced intermittently to determine all the steps required to produce the finished product; 2) Determine the process connection relationship and construct the adjacency matrix; 3) Establishing a process planning diagram based on the adjacency matrix; the process planning diagram is a bar chart or a double-code network diagram.

5. The intermittent production workshop management system according to claim 4 is characterized in that: The process planning diagram is established by using a critical path algorithm and a precedence diagram algorithm to establish a bar chart, and the steps include: 1) Determine the nodes representing the process and their logical relationships; 2) Determine the dependencies between processes based on the logical relationships in the adjacency matrix; 3) Calculate the process time parameters; the time parameters include the earliest start time, the earliest end time, the latest start time and the latest end time; 4) Compare the earliest and latest time parameters of each process to find the critical path without floating time; 5) Draw a Gantt chart on the Gantt chart template.

6. An intermittent production workshop management system according to any one of claim 4, characterized in that: The process planning diagram is established by using a depth-first search algorithm or a breadth-first search algorithm to establish a dual-code network diagram; the depth-first search algorithm includes: 1) Set a flag for each vertex to indicate whether it has been visited, and then set up a recursive stack to track the currently visited path; 2) Select the starting vertex, mark it as visited, traverse the adjacency matrix, and find the vertices connected to the starting vertex that have not been visited; 3) For each vertex found, recursively execute the previous step, that is, use it as the new starting vertex for depth-first search; when the current vertex has no more unvisited adjacent points, backtrack to the previous vertex and continue to search for other unvisited adjacent points; 4) Map each visited vertex as a node, and map the connection relationship between vertices as arrows, annotate the process information and duration to establish a double-code network diagram.

7. The intermittent production workshop management system according to claim 3 is characterized in that: The process dispatching module uses a scheduling algorithm based on priorities and constraints for calculation, and the steps include: 1) Read basic data and determine priorities and constraints; 2) Generate an initial process dispatching plan using a heuristic algorithm based on priorities and constraints; the heuristic algorithm includes a greedy algorithm and a simulated annealing algorithm; 3) Using an optimization algorithm to optimize the initial process dispatching plan; the optimization algorithm is a genetic algorithm or a linear programming algorithm.

8. The intermittent production workshop management system according to claim 1, characterized in that: The work reporting and settlement module includes: 1) Production progress recording module: used to fill in progress information according to the requirements of the production work order and the actual production situation; the progress information includes production quantity, production time, and production equipment used; 2) Salary settlement module: used for time-based settlement or piece-rate settlement based on progress information.

9. An intermittent production workshop management system according to any one of claims 1 to 8, characterized in that: The analysis and early warning module includes: 1) Data collection and analysis module: used to collect data from the basic data module, product dispatch module and work report and settlement module and conduct statistical analysis; 2) Abnormal detection and early warning module: used to identify abnormal situations in intermittent production processes and trigger early warning mechanisms based on the results of data analysis; 3) Trend forecasting and optimization suggestion module: used to predict future production trends based on historical data, help enterprises formulate response strategies in advance, and make optimization suggestions.

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