Abstract
Computer-aided process planning (CAPP) plays an important role in integrated manufacturing system and it can serve as a bridge between CAD and CAM. As a crucial part of CAPP, setup planning is a multi-constraint problem, in which the precision takes priority over efficiency. However, instead of precision constraints, traditional optimization methods have paid much more attention to efficiency requirements. This leads to the reduction in the precision of the final parts. This paper develops an optimization approach for solving computer-aided setup planning problem, which takes into account various constraints, especially the precision requirements specified by designers. First, objective function of the optimization model is formulated and a series of constraints, including feature precedence, tool approaching direction (TAD), and precision requirements are systematically created. Next, the model is solved by using a hybrid particle swarm optimization algorithm. In order to overcome the local optimum trap, mutation and exchange operations are adopted from the genetic algorithm. Finally, a part is tested in the case study and the validation of this method is proved.
Highlights
A Computer-aided process planning (CAPP) system is usually composed of three consecutive activities: (1) recognize features from given CAD models; (2) determine machining resources according to recognized machining features; (3) select an appropriate setup plan to make the parts machined accurately and efficiently [1]
In 1998, Huang built a mathematical model for lathe machining automation setup [2], in which geometry, precedence, force and tolerance constraints are taken into consideration
The third term in the objective function is the summarization for the precision requirements value (SPR) whose related machining features are separated into different setups
Summary
A CAPP system is usually composed of three consecutive activities: (1) recognize features from given CAD models; (2) determine machining resources according to recognized machining features; (3) select an appropriate setup plan to make the parts machined accurately and efficiently [1]. Graph-based methods select the setup solution that affects the machining accuracy as little as possible. The machining quality lacks of further investigation in the optimization models For this reason, the proposed research findings can be well applied in solving scheduling problems, instead of obtaining high precision manufacturing quality in practical processing. Since the model in this paper involves large amount of constraints, in order to obtain the global optimal solution in a reasonable time, a hybrid PSO-GA algorithm is proposed to solve the setup planning mathematical model
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