Optimal Process Planning for Compound Laser Cutting and Punching Using Genetic Algorithms

Abstract

This paper investigates the nesting issue and the machining path planning issue for improving the sheet metal machining efficiency. The nesting issue is to maximise sheet metal material utilisation ratio by nesting parts of various shapes into the sheet. The path planning issue is to optimise machining sequence so that the total machining path distance and machining time are minimised. This work investigates the two issues by using Genetic Algorithms (GA). The proposed GA approach uses a genetic encoding scheme and a genetic reproduction strategy to reach an optimum solution. Case studies are carried out to test the GAs. The effectiveness of the GA path planning approach is compared with the Ant Colony (AC) algorithm (Wang and Xie, 2005). The results show that GA achieves better performances in path planning than the AC algorithm.