Multi-objective optimization of machining parameters in multi-pass turning operations for low-carbon manufacturing

Abstract

Most recent studies on machining parameter optimization in machining operations focused on reducing machining cost and energy consumption. However, environmental impacts caused by manufacturing activities were not involved in those studies, which can be quantified by equivalent carbon dioxide emissions. In this study, a direct method was proposed to quantify the carbon emissions generated during multi-pass turning operations. Moreover, machining parameter optimization models of multi-pass turning operations in dry and wet cut environments were established using an experimental design method. Three objectives were considered in both models: carbon emissions, operation time, and machining cost. Furthermore, a multi-objective teaching–learning-based optimization algorithm was used to deal with the models. The optimization results indicated that the use of cutting fluids could significantly reduce carbon emissions and machining cost and improve production efficiency in multi-pass turning operations.