Genetic algorithms solution to the single-objective machining process optimization time model
Abstract
Minimum Production Time model of the machining process optimization problem comprising seven lathe machining operations were developed using Genetic Algorithms solution method. The various cost and time components involved in the minimum production cost and minimum production time criteria respectively, as well as all relevant technological/practical constraints were determined. An interactive, user-friendly computer package was then developed in Microsoft Visual Basic.Net environment to implement the developed models. The package was used to determine optimal machining parameters of cutting speed, feed rate and depth of cut for the seven machining operations with twenty-three technological constraints in the conversion of a cylindrical metal bar stock into a finished machined profile. The result of the single-objective machining process optimization models shows that the minimum production time is 21.84 min.
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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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