Sustainable Machining Process: Qualitative Analysis and Energy Efficiency Optimization

  • L. C. Moreira
  • W. D. LiEmail author
  • X. Lu
  • M. E. Fitzpatrick


Computer numerical control (CNC) machining is one of the major manufacturing activities. It is imperative to develop energy-efficient CNC machining processes to achieve the overall goal of sustainable manufacturing. Due to the complexity of machining parameters, it is challenging to develop effective energy consumption modelling and optimization approaches to implement energy-efficient CNC machining. In this chapter, via experiments and qualitative analysis, the impact that key cutting parameters generates on energy consumption of milling processes on BS EN24T alloy (AISI 4340) has been conducted in detail. This facilitates machining process planners to choose suitable scopes of machining parameters, (e.g. cutting speed, feed per tooth, engagement depth) to improve energy efficiency. Based on the above, optimization has been carried out to formulate a multi-objective optimization model, and a novel-improved multi-swarm fruit fly optimization algorithm (iMFOA) has been developed to identify optimal solutions. Case studies and algorithm benchmarking have been conducted to validate the effectiveness of the optimization approach. The characteristics and novelty of the research include: (1) the relationships between energy consumption and key machining parameters have been analysed to support process planners in implementing energy saving measures efficiently; and (2) the optimization approach is effective in fine-tuning the key parameters for enhancing energy efficiency while meeting the dynamic production requirements.


CNC machining Energy saving Optimization Sustainable manufacturing 



The authors would acknowledge Mr G. Booth for the support and knowledge transferred during the machining experiments.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • L. C. Moreira
    • 1
  • W. D. Li
    • 1
    Email author
  • X. Lu
    • 1
  • M. E. Fitzpatrick
    • 1
  1. 1.Faculty of Engineering, Environment and ComputingCoventry UniversityCoventryUK

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