Abstract
Modern machining processes such as abrasive waterjet (AWJ) are widely used in manufacturing industries nowadays. Optimizing the machining control parameters are essential in order to provide a better quality and economics machining. It was reported by previous researches that artificial bee colony (ABC) algorithm has less computation time requirement and offered optimal solution due to its excellent global and local search capability compared to the other optimization soft computing techniques. This research employed ABC algorithm to optimize the machining control parameters that lead to a minimum surface roughness (R\(_{a})\) value for AWJ machining. Five machining control parameters that are optimized using ABC algorithm include traverse speed (V), waterjet pressure (P), standoff distance (h), abrasive grit size (d) and abrasive flow rate (m). From the experimental results, the performance of ABC was much superior where the estimated minimum R\(_{a }\) value was 28, 42, 45, 2 and 0.9 % lower compared to actual machining, regression, artificial neural network (ANN), genetic algorithm (GA) and simulated annealing (SA) respectively.
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Special appreciative to reviewers for useful advices and comments. The authors greatly acknowledge the Research Management Centre, UTM and Ministry of Higher Education Malaysia (MOHE) for financial support through the Exploratory Research Grant Scheme (ERGS) No.Q.J13000078284L003.
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Yusup, N., Sarkheyli, A., Zain, A.M. et al. Estimation of optimal machining control parameters using artificial bee colony. J Intell Manuf 25, 1463–1472 (2014). https://doi.org/10.1007/s10845-013-0753-y
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DOI: https://doi.org/10.1007/s10845-013-0753-y