Energy efficient cutting parameter optimization

Abstract

Mechanical manufacturing industry consumes substantial energy with low energy efficiency. Increasing pressures from energy price and environmental directive force mechanical manufacturing industries to implement energy efficient technologies for reducing energy consumption and improving energy efficiency of their machining processes. In a practical machining process, cutting parameters are vital variables set by manufacturers in accordance with machining requirements of workpiece and machining condition. Proper selection of cutting parameters with energy consideration can effectively reduce energy consumption and improve energy efficiency of the machining process. Over the past 10 years, many researchers have been engaged in energy efficient cutting parameter optimization, and a large amount of literature have been published. This paper conducts a comprehensive literature review of current studies on energy efficient cutting parameter optimization to fully understand the recent advances in this research area. The energy consumption characteristics of machining process are analyzed by decomposing total energy consumption into electrical energy consumption of machine tool and embodied energy of cutting tool and cutting fluid. Current studies on energy efficient cutting parameter optimization by using experimental design method and energy models are reviewed in a comprehensive manner. Combined with the current status, future research directions of energy efficient cutting parameter optimization are presented.

Graphical abstract

Keywords

energy efficiency / cutting parameter / optimization / machining process

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (Grant No. 51905448), the Fundamental Research Funds for the Central Universities of China (Grant No. SWU119060), the Natural Science Foundation of Chongqing, China (Grant No. cstc2018jcyjAX0579), and the Technological Innovation and Application Development of Chongqing, China (Grant No. cstc2019jscx-mbdx0118).

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