Optimization of cutting parameters with a sustainable consideration of electrical energy and embodied energy of materials

Xingzheng Chen, Congbo Li, Yan Jin, Li Li

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)
291 Downloads (Pure)

Abstract

In a milling process, proper selection of cutting parameters can significantly reduce the electrical energy consumption. Many researchers have conducted cutting parameter optimization of the milling process for electrical energy saving during the past several years. However, in the milling process, a large amount of auxiliary materials such as cutting tools and cutting fluids are consumed. The production process of these materials is energy-intensive and a lot of energy are consumed. Optimizing cutting parameters considering both the electrical energy consumption and embodied energy consumption of auxiliary materials can further reduce the environmental impact of the milling process. In this paper, an approach of cutting parameter optimization is proposed to maximize energy efficiency and machining efficiency for milling operation. Firstly, an energy consumption model of milling operation considering both the electrical energy consumption and embodied energy consumption of cutting tools and cutting fluids is proposed. Then a multi-objective optimization model is established to achieve maximizing energy efficiency and machining efficiency. Finally, to verify the proposed multi-objective model, case studies are carried out and the results indicate that (i) the optimum cutting parameters of milling process vary with the energy boundaries whether considering the embodied energy of the auxiliary materials or not; (ii) the optimum cutting parameter schemes for maximum machining efficiency do not ensure maximum energy efficiency; (iii) multi-objective optimization is an effective method to address the conflicts of the two
objectives.
Original languageEnglish
Pages (from-to)1-14
JournalInternational Journal of Advanced Manufacturing Technology
Early online date29 Jan 2018
DOIs
Publication statusEarly online date - 29 Jan 2018

Keywords

  • Parameter optimization
  • Energy efficiency
  • Milling
  • Machining efficiency

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