In previous work, for the automotive industry, the use of a fuzzy logic rule-based system in the field of maintenance decision making was presented. The implemented system required the user to acquire a sense of 'scale' as a by-product of applying a multiple criteria decision making system based on the Analytic Hierarchy Process (AHP). The user then defined membership functions manually. In this paper an adaptable algorithm, incorporating possibility theory generates membership functions from historical data. The objective of this work is to develop a dynamic and an adaptable maintenance system that utilises existing data and supports decisions accordingly. One of the major problems in maintenance is the lack of a systematically focused approach in setting preventive maintenance instructions. Hence, preventive maintenance might be efficient but not effective. The methodology carried out in this paper is concerned with the development of a systematic, and an adaptable, approach that will determine what specific actions to perform given current working conditions.
An adaptable maintenance model using a fuzzy system and possibility theory
Ein adaptives Wartungsmodell mit einem wahrscheinlichkeitsorientierten Fuzzy-Controller
1998
4 Seiten, 2 Bilder, 1 Tabelle, 5 Quellen
Conference paper
English
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