Tool Routing Path Optimization for Multi-Hole Drilling Based on Ant Colony Optimization

Abstract

Currently, most companies that conduct business in both domestic and global markets are facing growing international competition and recognize the importance of reducing manufacturing lead time, for example, companies in the machining industry. In general, machining can be performed manually, automatically or by Computer Numerical Control (CNC). The optimization of tool routing path operation in machining can lead to significant reduction in non-productive machining time. This paper focuses on the development of the Ant Colony Optimization (ACO) algorithm for use in searching for the optimal tool routing path and the relationship with its control parameter values. The simulation of a machining operation is conducted in MATLAB with incremental positioning axis movement based on the Travelling Salesman Problem (TSP). The results indicate that the relationship between the travelled distance of the ant and the ant's control parameters are significant in increasing the hole drilling operation efficiencies. This result indicates that ACO algorithm programming can be used to optimize the tool routing path.