Multiobjective optimization of multipass turning machining process using the genetic algorithms solution
Abstract
The study involves the development of multi-objective optimization model for turning machining process. This model was developed using a GA - based weighted-sum of minimum production cost and time criteria of multipass turning machining process subject to relevant technological/practical constraints. The results of the single-objective machining process optimization models for the multipass turning machining process when compared with those of multi-objective machining process model yielded the minimum production cost and minimum production time as $5.775 and 8.320 min respectively (and the corresponding production time and production cost as 12.996min and $6.992, respectively), while those of the multi-objective machining process optimization model were $5.841and 9.097 min. Thus, the multi-objective machining process optimization model performed better than each of the single-objective model for the two criteria of minimum production cost and minimum production time respectively. The results also show that minimum production time model performs better than the minimum production cost model. For the example considered, the multi-objective model gave a lower production time of 30.0% than the corresponding production time obtained from the minimum production cost model, while it gave a lower production cost of 16.46% than the corresponding cost obtained by the minimum production time model.
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Author Biographies
Patrick Amiolemhen is an Associate Professor in the Department of Production Engineering, University of Benin, Benin City. He holds a Bachelor of Engineering (B. Eng.) in Mechanical Engineering from the University of Benin, Benin City in 1991 and M. Eng. and PhD degrees in Production Engineering (Manufacturing Option from the University of Benin, Benin City in 2003 and 2009 respectively. He is a certified mechanical engineer; a member of the Nigerian Society of Engineers as well as a member of the Nigerian Institution of Production Engineers. He has published both national and international journal articles. Since 2006 he has been a researcher in the Department of Production Engineering, University of Benin, where he teaches machines design; engineering mathematics; machine tool technology; operations & production management at the undergraduate levels; while at the postgraduate level he teaches machines design; machine tool design; metal machining process optimization and human resources management. His present research areas focus on design and manufacture of engineering machineries and application of computational algorithms to multi-objectives optimization in engineering.
Joshua Eseigbe received his Bachelor’s degree in Production Engineering from the University of Benin, Benin City Nigeria in 2012, and master’s degree in industrial engineering from the same university in 2017. He is currently undergoing his doctorate degree in the Department of Production, University of Benin, Benin City. His research interests include; engineering design, optimization and industrial engineering.
Copyright (c) 2019 Patrick Ejebheare Amiolemhen, Joshua Ahurome Eseigbe
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