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Multi-state decision of unreliable machines for energy-efficient production considering work-in-process inventory

  • Junfeng Wang
  • Zicheng Fei
  • Qing Chang
  • Shiqi Li
  • Yan FuEmail author
Open Access
ORIGINAL ARTICLE
  • 28 Downloads

Abstract

Energy-efficient operation of manufacturing systems is critical for industrial enterprises in current environmentally conscious society. Decreasing the idle time of a machine is one of the main methods to achieve energy-efficient production. From the system level, when and how long a machine can be turned into standby state with lower energy consumption is still a difficult problem for unreliable manufacturing systems considering less throughput loss. In this paper, a novel multi-state decision method based on fuzzy logic is proposed to switch a machine into different sleep states considering real-time work in process inventory of buffers. Three basic modules and their corresponding fuzzy controllers are presented to construct complex manufacturing systems with disassembly and assembly workstations. The fuzzy rules for machine state decision are generated based on the expert/production knowledge. By means of simulation experiments, the effectiveness of the proposed method is illustrated for an unreliable complex manufacturing system.

Keywords

Machine state decision Fuzzy logic Energy-efficient production Unreliable manufacturing system 

Notes

Funding information

This work is supported by the National Natural Science Foundation of China (Grant number 71571075).

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Copyright information

© The Author(s) 2018

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Junfeng Wang
    • 1
  • Zicheng Fei
    • 1
  • Qing Chang
    • 2
  • Shiqi Li
    • 1
  • Yan Fu
    • 1
    Email author
  1. 1.Department of Industrial and Manufacturing System EngineeringHuazhong University of Science and TechnologyWuhanChina
  2. 2.Department of Mechanical EngineeringStony Brook UniversityStony BrookUSA

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