Optimizing cutting parameters in process planning of prismatic parts by using genetic algorithms

Abstract

The determination of optimal cutting parameters, such as the number of passes, depth of cut for each pass, cutting speed and feed, which are applicable for assigned cutting tools, is one of the vital modules in process planning of metal parts, since the economy of machining operations plays an important role in increasing productivity and competitiveness. The present paper introduces a 'system software' developed to optimize the cutting parameters for prismatic parts. The system is mainly based on a powerful artificial intelligence (AI) tool, called genetic algorithms (GAs). It is implemented using C programming language and on a PC. It can be used as standalone system or as the integrated module of a process planning system called OPPS-PRI (Optimized Process Planning System for PRIsmatic parts) that was also developed for prismatic parts and implemented on a vertical machining centre (VMC). With the use of GAs, the impact and power of AI techniques have been reflected on the performance of the optimization system. The methodology of the developed optimization system is illustrated with practical examples throughout the paper.