A fuzzy logic approach to forecast energy consumption change in a manufacturing system

H. C W Lau, E. N M Cheng, Ka Man Lee, G. T S Ho

Research output: Journal article publicationJournal articleAcademic researchpeer-review

65 Citations (Scopus)

Abstract

This paper proposes an energy consumption change forecasting system using fuzzy logic to reduce the uncertainty, inconvenience and inefficiency resulting from variations in the production factors. The proposed fuzzy logic approach helps the manufacturer forecast the energy consumption change in the plant when certain production input factors are varied. Predictions given by the proposed system adopts the fuzzy rule reasoning mechanism so that any changes in the overall energy consumption will neither violate the stable power supply and production schedules nor result in energy wastage. To demonstrate how the fuzzy logic approach is applied to a manufacturing system, a case study of the energy consumption forecast in a clothing manufacturing plant has been conducted in an emulated environment. The result of the case indicates a percentage change in the plant's energy consumption after analyzing three input parameters. This finding is able to provide a solid foundation on which decision makers and systems analysts can base suitable strategies for ensuring the efficiency and stability of a manufacturing system.
Original languageEnglish
Pages (from-to)1813-1824
Number of pages12
JournalExpert Systems with Applications
Volume34
Issue number3
DOIs
Publication statusPublished - 1 Apr 2008

Keywords

  • Energy consumption
  • Fuzzy logic
  • Manufacturing system
  • Rule based reasoning mechanism

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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