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A welding production line work class assignment system and method based on particle swarm optimization algorithm

A technology of welding production line and particle swarm algorithm, which is applied in the direction of manufacturing computing system, computing, computing model, etc., can solve the problems of robots reducing resource utilization, job backlog, and production link impact

Inactive Publication Date: 2019-01-22
CHINA UNIV OF MINING & TECH
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The transfer method of the workpiece is generally selected as the assembly line, which requires that the workpieces move synchronously during the processing, so the working rhythm of each station must be consistent, so as not to cause too much work in some stations and cannot be completed on time, while some stations are not. No work, leaving the robot idle to reduce resource usage
The unbalanced workload among the stations sometimes causes a backlog of jobs, which not only prevents the smooth completion of the functions in the current cycle, but also affects the subsequent production links, and even causes the entire production line to fail to run smoothly.

Method used

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  • A welding production line work class assignment system and method based on particle swarm optimization algorithm
  • A welding production line work class assignment system and method based on particle swarm optimization algorithm
  • A welding production line work class assignment system and method based on particle swarm optimization algorithm

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Embodiment Construction

[0016] Step 1: Obtain the information of multi-station balance planning model

[0017] The assembly line balancing problem is a decision-making problem considering the optimization goal, assigning operations / jobs to various stations or workstations. According to the objective function, the station balance planning problem can be divided into four categories:

[0018] (1) Knowing the production beat c, minimize the number of chemical digits (SALBP-1).

[0019] (2) Knowing the number of stations, minimize the production beat c(SALBP-2).

[0020] (3) Both the number of stations and the tact of production are variable, maximizing the line efficiency E=t sum / (c m)(SALBP-3).

[0021] (4) Find a set of feasible equilibrium solutions (SALBP-4).

[0022] The first type of problem (SALBP-1) is studied, which is to minimize the number of workstations under the constraints of fixed production nodes, balance the production time of each workstation, reduce idle waiting time, and improv...

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Abstract

The invention relates to a welding production line work class assignment system and method based on a particle swarm optimization algorithm, which relates to a particle swarm algorithm and a balance programming solving algorithm. The invention solves a multi-station balance programming problem by using the particle swarm optimization algorithm and completes the reasonable arrangement of the multi-station, and belongs to the technical field of artificial intelligence and control. The invention mainly comprises the following contents: step 1: acquiring multi-station balance planning model information; 2, representing the welding sequence by a precursor diagram and storing in an adjacency table; 3, solving that multi-station balance programming problem by using the particle swarm optimizationalgorithm to obtain the minimum work number under a given beat; 4: According to the optimization process and result of step 3, obtaining the feasible scheme, and then obtaining the final scheme according to the man-hour standard deviation. From the results, it can be seen that the welding task assignment of each station is relatively balanced, which maximizes the utilization rate of each weldingrobot, shortens the man-hour of the station and meets the requirements of the production rhythm.

Description

technical field [0001] The invention relates to a particle swarm optimization algorithm-based welding production line work category allocation system and method, which involves a particle swarm optimization algorithm and a balance programming algorithm. By using the particle swarm optimization algorithm to solve the multi-station balance programming problem, the reasonable allocation of multi-stations is completed. The arrangement belongs to the field of artificial intelligence and control technology. Background technique [0002] The welding robot production line is a production line that connects multiple work units with a workpiece conveying line. When designing and planning a welding production line, usually multiple stations are arranged in sequence along the welding production line. Fast and sequential welding of all components. The transfer method of the workpiece is generally selected as the assembly line, which requires that the workpieces move synchronously during...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06N3/00G06Q50/04
CPCG06N3/006G06Q10/04G06Q10/06312G06Q10/06313G06Q50/04Y02P90/30
Inventor 丁世飞李景灿史颂辉
Owner CHINA UNIV OF MINING & TECH
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