Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/42936
Title: A fuzzy logic approach to forecast energy consumption change in a manufacturing system
Authors: Lau, HCW
Cheng, ENM
Lee, CKM
Ho, GTS
Keywords: Fuzzy logic
Manufacturing system
Rule based reasoning mechanism
Energy consumption
Issue Date: 2008
Publisher: Pergamon Press
Source: Expert systems with applications, 2008, v. 34, no. 3, p. 1813-1824 How to cite?
Journal: Expert systems with applications 
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.
URI: http://hdl.handle.net/10397/42936
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2007.02.015
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