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Optimization Parameters for Energy Efficiency in End milling

  • Lirong Zhou
  • , Jianfeng Li
  • , Fangyi Li
  • , Gamini Mendis
  • , John W. Sutherland

Research output: Contribution to journalConference articlepeer-review

Abstract

One way to manage the modern challenges of global resource depletion and climate change is to reduce energy consumption. The use stage of machines in manufacturing operations consumes the majority of energy and brings serious emissions over a machine's life cycle. With this in mind, a multi-objective cutting parameter optimization model is proposed, focusing on minimizing the process time and energy consumption per unit of removed material. Constraint conditions, such as the processing capacity of the machine tool, the tool life, the surface roughness of the part, and wasted ploughing energy are considered. A genetic algorithm is used to solve the optimization model and the effects of the parameters on the energy consumption of the machine are discussed. To verify the proposed method, experiments were designed for an end milling operation, using Taguchi design principles.

Original languageEnglish (US)
Pages (from-to)312-317
Number of pages6
JournalProcedia CIRP
Volume69
DOIs
StatePublished - 2018
Event25th CIRP Conference on Life Cycle Engineering, , CIRP LCE 2018 - Copenhagen, Denmark
Duration: Apr 30 2018May 2 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 13 - Climate Action
    SDG 13 Climate Action

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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