Comprehensive effects of tool paths on energy consumption, machining efficiency, and surface integrity in the milling of alloy cast Iron

Xiaona Luan, Song Zhang, Jianfeng Li, Gang Li, Jie Chen, Gamini Mendis

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Strategies to reduce energy consumption in manufacturing processes are necessary due to growing concerns about carbon emissions and environmental impacts. In this paper, the energy consumption in a machining process was studied and the effects of tool path were investigated. The optimization of the tool pathing was shown to offer significant opportunities to reduce energy consumption (by up to 50%) during the machining process. First, an improved energy consumption model was developed that included the effects of the tool path. Secondly, the proposed method was verified through machining experiments. Six milling tool paths were used to machine workpieces and the surface integrity of the machined surface was evaluated using X-ray diffraction and optical surface profiler. Finally, mathematical and experimental methods were used to analyze the trade-offs between energy consumption and relevant factors during the removal of a constant volume of material, confirming that optimization of the cutting tool path can be achieved by balancing the tradeoffs between machining time, cutting power, and surface integrity. The results indicate that the proposed tool-path energy model can accurately predict energy consumption of different tool paths. High machining efficiency (as reflected by low cutting time), excellent surface finish, and low energy consumption can be obtained using the proposed trade-off analysis.

Original languageEnglish (US)
Pages (from-to)1847-1860
Number of pages14
JournalInternational Journal of Advanced Manufacturing Technology
Volume98
Issue number5-8
DOIs
StatePublished - Sep 1 2018

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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