A comprehensive approach to parameters optimization of energy-aware CNC milling

Congbo Li, Lingling Li, Ying Tang, Yantao Zhu, Li Li

Research output: Contribution to journalArticlepeer-review

47 Scopus citations

Abstract

Cutting parameters are important components in the process of computer numerical control (CNC) machining, and reasonable choice of cutting parameters can significantly affect the energy efficiency. This paper presents a multi-objective parameter optimization method for energy efficiency in CNC milling process. Firstly, the energy consumption composition characteristics and temporal characteristics in CNC milling are analyzed, respectively. The energy model of CNC milling is then established, of which the correlation coefficient is obtained through nonlinear regression fitting. Then a multi-objective optimization model is proposed to take the highest energy efficiency and the minimum production time as the optimization objectives, which is solved based on Tabu search algorithm. Finally, a case study is conducted to validate the proposed multi-objective optimization model and the optimal parameter solutions of maximum energy efficiency and minimum production time is obtained. Moreover, the parametric influence on specific energy consumption and production time are explicitly analyzed. The experiment results show that cutting depth and width are the most influential parameters for specific energy consumption, and spindle speed ranks the first for the production time.

Original languageEnglish (US)
Pages (from-to)123-138
Number of pages16
JournalJournal of Intelligent Manufacturing
Volume30
Issue number1
DOIs
StatePublished - Jan 31 2019

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence
  • Industrial and Manufacturing Engineering

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