Path optimization of CNC PCB drilling using hybrid Taguchi genetic algorithm
Abstract
Purpose
In this study, the hybrid Taguchi genetic algorithm (HTGA) was used to optimize the computer numerical control-printed circuit boards drilling path. The optimization was performed by searching for the shortest route for the drilling path. The number of feasible solutions is exponentially related to the number of hole positions. The paper aims to discuss these issues.
Design/methodology/approach
Therefore, a traveling cutting tool problem (TCP), which is similar to the traveling salesman problem, was used to evaluate the drilling path; this evaluation is considered an NP-hard problem. In this paper, an improved genetic algorithm embedded in the Taguchi method and a neighbor search method are proposed for improving the solution quality. The classical TCP problems proposed by Lim et al. (2014) were used for validating the performance of the proposed algorithm.
Findings
Results showed that the proposed algorithm outperforms a previous study in robustness and convergence speed.
Originality/value
The HTGA has not been used for optimizing the drilling path. This study shows that the HTGA can be applied to complex problems.
Keywords
Acknowledgements
This study was done during doctoral program in National Kaohsiung First University of Science and Technology, Taiwan, ROC, which is supported by Indonesian Government in scheme BPPLN DIKTI 3+1 that began on September 2013.
Citation
Al-Janan, D.H. and Liu, T.-K. (2016), "Path optimization of CNC PCB drilling using hybrid Taguchi genetic algorithm", Kybernetes, Vol. 45 No. 1, pp. 107-125. https://doi.org/10.1108/K-03-2015-0069
Publisher
:Emerald Group Publishing Limited
Copyright © 2016, Emerald Group Publishing Limited