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A Comparative Analysis of Different Algorithms for Optimizing Cutting Force Components in Turning Stainless Steel

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Advances in Mechanical and Materials Technology (EMSME 2020)

Abstract

Improved turning performance is critical for higher-quality goods to be manufactured and costs to be reduced. The aim of this paper is to determine the optimal cutting parameters that minimize the net force in turning AISI 201 stainless steel using different mathematical optimization algorithms. Spindle speed, feed, depth of cut, and workpiece diameter were selected as machining parameters. L16 Taguchi design of experiments was employed which include four factors and four levels. In addition, regression models were developed to estimate cutting forces. Then, several mathematical optimization algorithms were used to find the optimal parameters that minimize the net force. The algorithms employed in this paper were brute–force algorithm, genetic algorithm, SHGO algorithm, and basin-hopping algorithm. These algorithms were able to find optimal solutions to a set of equations with bounds and constraints. Both deterministic and non-deterministic techniques were used in these algorithms to achieve the optimized value. The optimal parameters in this investigation were cutting speed 245 rpm, feed 0.17 mm/rev, depth of cut 0.2 mm. and workpiece diameter 19.1 mm.

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Correspondence to Toukir Ahmed .

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Ahmed, T., Al Rafi, F., Mahmud, S. (2022). A Comparative Analysis of Different Algorithms for Optimizing Cutting Force Components in Turning Stainless Steel. In: Govindan, K., Kumar, H., Yadav, S. (eds) Advances in Mechanical and Materials Technology . EMSME 2020. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-2794-1_107

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  • DOI: https://doi.org/10.1007/978-981-16-2794-1_107

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