Tool Path Optimization of Drilling Sequence Using an ACO Algorithm

Noor Hatem, Yusri Yusof , AiniZuhra A. Kadir, Kamran Latif, Mohammed M. A

Among the machining processes used most extensively is drilling. Reducing as much as possible the overall auxiliary time of the machining process, including airtime and tool changing time, is the goal of optimization. Previous studies have employed a number of heuristic optimization algorithms for TSP more or less successfully. Replicating the manner in which ants behave naturally, the ant colony optimization (ACO) algorithm is one algorithm that has been applied effectively to TSP. This algorithm is used in the present study to decrease tool retraction as much as possible within a novel optimization technique of non-productive tool path length in the context of contour parallel offset machining. The existing blocks in LabVIEW were employed for optimization of the input data and the results showed that, by comparison to the shortest tool path produced by Solid Work software, a 10.55% improvement was achieved in the overall length of the drilling tool path.

Volume 12 | Issue 6

Pages: 3124-3130

DOI: 10.5373/JARDCS/V12I6/S20201277