Sustainable Optimization of Dry Turning of Stainless Steel based on Energy Consumption and Machining Cost

Reducing energy consumption and machining cost under dry conditions should be considered for sustainable machining. The selection of cutting parameters is an important task for dry turning steel and has a significant influence on energy consumption and operation cost. In this work, the influence of cutting parameters, namely, cutting speed, feed rate, and depth of cut, on energy, cost, and tool wear are first analyzed. A multi-response parameter is then optimized to minimize energy and machining cost, and this parameter is solved using the NSGA II algorithm. Finally, a confirmation validation test is conducted to validate the proposed model. This method also effectively reduces environmental effects by using noncutting fluid and requiring less energy than other methods, and this reduction results in sustainable machining. (C) 2018 The Authors. Published by Elsevier Ltd.