Research on dynamic process planning system considering decision about machines

The traditional CAPP systems can generate process plans based on the two assumptions: that the job-shop remains static and there are unlimited resources available. Under these assumptions, when the process plans for the workpieces were finally, sent to the job-shop, process bottlenecks normally arose, making the generated process plans ineffective. In order to improve the validity of the process plans, a kind of dynamic CAPP system integration model was introduced, and machine decision-making was carried out based on BP neural network and relevant algorithm. As a result, the process plans which CAPP system generates can accord with the production situation and the requirements of the job-shop scheduling. Based on an illustrative example, the process of the decision-making for the machines was described in detail by using BP neural network and relevant algorithm.