Machine group scheduling method based on process capacity characteristic model

Abstract

The invention provides a machine group dispatching method on the basis of a processing capability characteristic model, belonging to the automatic control, information technique and advanced manufacture field. The machine group dispatching method is characterized in that on the basis of the dispatching time machine group information and the information of the dispatched workpiece which are obtained by a dispatching information hardware collecting system, the machine group dispatching software on the basis of processing capability characteristic model establishes a machine group dispatching model based on the processing capability characteristic model by taking the total minimum workpiece delay time as a dispatching object, further, a genetic algorithm based on the workpiece characteristic is adopted to carry out the optimum machine group dispatching and obtain a optimum machine group dispatching proposal based on the workpiece group sorting, and dynamically correct the original optimum machine group dispatching proposal on the basis of the workpiece releasing time disturbance information so as to deal with the problems that the original optimum machine group dispatching proposal performance is reduced or non-feasible due to workpiece releasing time disturbance. The dispatching method of the invention can carry out effective integrated optimum dispatching to the machine group of the traditional dispatching mode, which is difficult to directly assign the workpiece to the specific machines.

Description

technical field [0001] The invention belongs to the fields of automatic control, information technology and advanced manufacturing, and mainly relates to a method for optimal scheduling of a machine group including multiple machines but difficult to directly adopt the traditional scheduling mode of assigning workpieces to specific machines in a complex production process. Background technique [0002] In the production process of discrete / semi-continuous large and medium-sized manufacturing enterprises such as machinery, electronics, and textiles in my country, there are several processes with the following characteristics: the process is composed of multiple machines with similar processing capabilities; the number of machines and workpieces to be processed is large; due to There are uncertain factors such as quality accidents or machine failures in the previous process or this process, and changes in transportation time between processes. There are usually random disturbance...

AI Technical Summary

Problems solved by technology

This method first establishes a processing capability characteristic model for the machine group scheduling problem, and then uses the genetic algorithm based on workpiece characteristics to obtain the optimal scheduling scheme of the machine group based on the sorting of the workpiece group, and dynamically optimizes the scheduling scheme of the original machine group based on the disturbance information of the workpiece release time. Corrected to deal with the problem that the performance of the original machine group optimization scheduling scheme is degraded or even infeasible due to the disturbance of the workpiece release time

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