General assembly technological process planning method based on resource constraint

Abstract

The invention relates to a general assembly technological process planning method based on resource constraint, and solves the problems of high production information collection and analysis requirements, low efficiency, long scheduling period, slow response, no foresight and lagging of a general assembly process in a current mode. Comprising the following steps: step 1, resource statistics; step 2, process carding; the method comprises the following steps: 1) carding resources required by each process; 2) carding the time required by each process; (3) sorting the absolute time sequence between the processes, and drawing a flow chart according to the shortest time logic; step 3, designing station contents; 4, building a system; 5, carrying out digital simulation; 6, collecting and feeding back data; step 7, reserving bottleneck resources; step 8, performing iterative updating; and step 9, system scheduling. According to the method, the waiting time caused by limited production resources is shortened, the existing resources are played to the greatest extent, the production efficiency can be effectively improved, and final assembly technological process planning based on resource constraints is realized.

Description

Technical Field

[0001] The invention belongs to the field of final assembly process flow planning, and in particular relates to a final assembly process flow planning method based on resource constraints. Background Art

[0002] Final assembly is the last link of manufacturing production. Whether the final assembly can be carried out smoothly is related to whether the product can be delivered on time. However, in actual production, the overall progress of final assembly is often restricted by the shortage of production resources. At present, the final assembly plant usually adjusts the production plan and resource allocation artificially and temporarily through the scheduling system to deal with the constraints brought by resource constraints. This mode has high requirements for production information collection and analysis, low efficiency, long scheduling cycle, slow response, and lack of foresight, which lags behind the final assembly process. In this regard, it is very necessary to propose a final assembly process planning method based on resource constraints. Summary of the invention

[0003] The present invention designs a method for planning the final assembly process based on resource constraints, which solves the problems of the current model with high requirements for production information collection and analysis, low efficiency, long scheduling cycle, slow response, lack of foresight, and lagging final assembly process.

[0004] The present invention is achieved by the following technical solutions:

[0005] A method for planning a general assembly process based on resource constraints comprises the following steps:

[0006] Step 1: Resource statistics:

[0007] Sort out the existing production resources in the workshop, including workers, tooling, standard parts, spare parts, finished parts, tools, testing equipment, etc.;

[0008] Step 2: Process sorting:

[0009] 1) Sort out the resources required for each process, including workers, tooling, standard parts, parts, finished parts, tools, testing equipment, etc.;

[0010] 2) Sort out the time required for each process;

[0011] 3) Sort out the absolute time sequence between processes and draw a flow chart based on the shortest time logic;

[0012] The process flow chart drawn according to the shortest time logic is to sort out a process logic diagram with the most parallelism and the least intersection.

[0013] Step 3: Workstation content design:

[0014] According to the content sorted out in step 2, rationally plan the work content of each workstation, and try to ensure that the working time and production resources occupied by each workstation are relatively even;

[0015] Step 4: System construction:

[0016] The production resources counted in step 1, the process information in step 2, the workstation information in step 3, etc. are digitized and uploaded to the scheduling system;

[0017] The scheduling system should also be able to identify and classify the status of existing resources in real time, including: current and expected usage time, idle time, failure time and recovery time;

[0018] Step 5: Digital Simulation:

[0019] According to the process logic in step 2, combined with the production resources in step 1, using the scheduling system built in step 4, under the premise of existing production materials, simulate the process logic sorted out in step 3 to verify whether the workstation content design in step 3 is reasonable, and optimize the process logic and workstation content under the constraints of existing resources according to the simulation results;

[0020] Step 6: Data collection and feedback:

[0021] Carry out a trial run in the workshop according to the optimal process logic and workstation distribution optimized in step 5. Collect production data during the trial run, including the actual time of each process, the actual use time of each tool, tool, equipment, etc. and the number of vacancies at the same time, the actual working time of each workstation, and collect workers' suggestions for improvement of processes, workstations, and production materials;

[0022] Step 7: Bottleneck resource reserve:

[0023] Based on the information collected in step 6 and the feedback from the workers, sort out the bottlenecks that restrict the final assembly process, including tooling, tools, equipment, parts, etc., prepare backups in advance, and develop emergency plans;

[0024] Based on the identified bottlenecks that restrict the final assembly process, the process logic is adjusted again to stagger the processes that use the same scarce resources.

[0025] Step 8: Iterative update: Update the trial operation data obtained in step 6 and the production data supplemented in step 7 to the system built in step 4, and perform step 5 again to iteratively optimize the assembly process flow to obtain the optimal solution;

[0026] Step 9: System Scheduling: Run the optimal solution iterated from step 8, and use the system built in step 4 to conduct real-time digital monitoring of the entire assembly process. According to the real-time production resource situation, pre-simulate the subsequent processes to discover production resource shortages in advance. Automatically give prompts based on the resources required for the subsequent processes sorted out in step 2, and reallocate assembly resources and re-plan the process flow in combination with the existing resource status of the workshop counted in step 4.

[0027] The present invention dynamically adjusts the order of assembly processes through a scheduling system, reduces waiting time caused by limited production resources, maximizes existing resources, effectively improves production efficiency, and realizes assembly process planning based on resource constraints. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 The invention discloses a general assembly process planning flow chart based on resource constraints. DETAILED DESCRIPTION

[0029] In order to more clearly understand the specific implementation process of this achievement, further explanation is given below in combination with production practice and accompanying drawings.

[0030] like Figure 1 As shown, the present invention is a method for planning a general assembly process based on resource constraints, and the specific steps are as follows:

[0031] Step 1: Evaluate the current production data of the workshop, such as the types and number of workers, the work they are capable of doing, the number and range of torque wrenches, the specifications and number of screwdrivers, the range and number of vernier calipers, the specifications and number of standard parts, the types and number of tooling, the number of equipment, and whether it can operate normally, etc.

[0032] Step 2: Sort out the number of people required for each process, the specifications and quantity of tooling and tools, etc., sort out the time required for each process, sort out the absolute time logical sequence between processes, and compile a process logic diagram with the most parallelism and the least intersection.

[0033] Step 3: Based on the logic and time between processes sorted out in Step 2, reasonably arrange the workstation content under the existing resource constraints to make the working time of each workstation as consistent as possible, avoiding a workstation occupying a production resource for too long and limiting the progress of the entire assembly.

[0034] Step 4: Digitize the information from step 1 to step 3 and input it into the scheduling system for real-time monitoring to facilitate subsequent digital simulation, process iteration and system scheduling.

[0035] Step 5: Based on the existing resources sorted out in step 1, verify the process of step 2 and the workstation content of step 3, determine their rationality, and optimize them according to the simulation results.

[0036] Step 6: Actually run the best solution simulated in step 5, and collect various data generated in the production process in real time, such as the actual time taken for each process, the actual time the tooling and tools are occupied, etc. In addition, pay attention to collecting workers' feedback on process logic and workstation distribution.

[0037] Step 7: Based on the actual operation situation, sort out the bottlenecks that currently restrict the entire assembly process, such as a certain tool, tooling, equipment, etc., and prepare stocks in advance or strengthen maintenance for the scarce production resources to ensure the maximum operation of the bottleneck resources. According to the sorted out scarce resources, adjust the process logic again to stagger the processes that use the same scarce resources.

[0038] Step 8: Supplement the data obtained in steps 6 and 7 into the scheduling system, and perform step 5 again to iteratively optimize the process flow to obtain the optimal process under resource-constrained conditions.

[0039] Step 9: Actually run the optimal process iterated from step 8, and detect the operation status of production materials such as equipment, tooling, tools, and personnel at the workstation in real time. If there are any problems or occupancy, the scheduling system will give prompts in advance and dynamically adjust the assembly process according to the currently available production materials to ensure a smooth assembly process.

[0040] The present invention can dynamically, automatically, quickly and prospectively reallocate production resources according to subsequent production procedures and re-plan the final assembly process flow in response to different resource constraints that occur, which can greatly improve the utilization rate of production resources, improve production efficiency and realize final assembly process flow planning under resource constraints.

Claims

1. A method for planning a general assembly process based on resource constraints, characterized by: The following steps are involved: Step 1: Resource statistics: Sort out the existing production resources in the workshop; Step 2: Process sorting: 1) Sort out the resources required for each process; 2) Sort out the time required for each process; 3) Sort out the absolute time sequence between processes and draw a flow chart based on the shortest time logic; Step 3: Workstation content design: According to the content sorted out in step 2, rationally plan the work content of each workstation to ensure that the working time and production resources occupied by each workstation are relatively even; Step 4: System construction: The production resources counted in step 1, the process information in step 2, and the workstation information in step 3 are digitized and uploaded to the scheduling system; the scheduling system realizes real-time identification and classification of the status of existing resources; Step 5: Digital Simulation: According to the process logic in step 2, combined with the production resources in step 1, using the scheduling system built in step 4, under the premise of existing production materials, simulate the process logic sorted out in step 3 to verify whether the workstation content design in step 3 is reasonable, and optimize the process logic and workstation content under the constraints of existing resources according to the simulation results; Step 6: Data collection and feedback: Carry out a trial run in the workshop according to the optimal process logic and workstation distribution optimized in step 5. Collect production data during the trial run, including the actual time of each process, the actual use time of each tool, tool, and equipment and the number of vacancies at the same time, and the actual working time of each workstation. In addition, collect workers' suggestions for improvement of processes, workstations, and production materials; Step 7: Bottleneck resource reserve: Based on the information collected in step 6 and the feedback from the workers, sort out the bottlenecks that restrict the final assembly process, including tooling, tools, equipment, and parts, prepare backups in advance, and develop emergency plans; Step 8: Iterative update: Update the trial operation data obtained in step 6 and the production data supplemented in step 7 to the system built in step 4, and perform step 5 again to iteratively optimize the assembly process flow to obtain the optimal solution; Step 9: System Scheduling: Run the optimal solution iterated from step 8, and use the system built in step 4 to conduct real-time digital monitoring of the entire assembly process. According to the real-time production resource situation, pre-simulate the subsequent processes to discover production resource shortages in advance. Automatically give prompts based on the resources required for the subsequent processes sorted out in step 2, and reallocate assembly resources and re-plan the process flow in combination with the existing resource status of the workshop counted in step 4.

2. The method for planning assembly process flow based on resource constraints according to claim 1 is characterized by: In step 1, the existing production resources of the workshop are sorted out, including workers, tooling, standard parts, parts, finished parts, tools, and testing equipment.

3. The method for planning assembly process flow based on resource constraints according to claim 1 is characterized by: In step 2, the resources required for each process include workers, tooling, standard parts, parts, finished products, tools, and testing equipment.

4. The method for planning assembly process flow based on resource constraints according to claim 1 is characterized by: In step 2, drawing the flow chart according to the shortest time logic is to sort out the process logic diagram with the most parallelism and the least intersection.

5. The method for planning assembly process flow based on resource constraints according to claim 1 is characterized by: In step 4, the scheduling system identifies and classifies the status of existing resources in real time, including: current and expected usage time, idle, failure, and recovery time.

6. The method for planning assembly process flow based on resource constraints according to claim 1 is characterized by: In step 7, based on the identified bottlenecks that restrict the final assembly process, the process logic is adjusted again to stagger the processes that use the same scarce resources.

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