Study on optimal path changing tools in CNC turret typing machine based on genetic algorithm

Abstract

This paper is aimed to find the optimum path of CNC turret typing system to reduce the changing tools times and optimize tool movement routes to make up for the deficiency of CNC Turret Typing machine production efficiency. An uncertainty polynomial model is raised based on the asymmetric traveling salesman problem. And genetic algorithm (GA) is used to solve the path optimization problem. The optimization of path can minimize the moving tools times. Furthermore, the optimization problem is simplified to shortest distance between points. Fitness function, selection operator, crossover operator, mutation operator and other genetic operations are studied in this paper. In addition, the greedy crossover operator, the elite preservation strategy and the self-adaption strategy are imported in GA, which enhance the ability of finding the optimum and speed the efficiency. Finally, MATLAB simulation testifies that the algorithm is valid. The experiment result shows that the GA can shorten processing time and can reduce the air travel effectively without changing the machine's hardware through reasonable arrangement of the changing and moving tools path. As a result, the efficiency and precision of CNC turret typing system was improved availably. © 2011 IFIP International Federation for Information Processing.