Paper Info
Title
Selective maintenance optimization for fuzzy multi-state systems.
Abstract
This paper addresses a selective maintenance optimization problem for a fuzzy multi-state system composed of fuzzy multi-state elements. Due to insufficient data and unpredictable external working conditions, both the performance capacity and states transition intensities of multi-state elements cannot be known precisely, but are represented by fuzzy numbers. Additionally, both the durations of a break and a succeeding mission are also treated as fuzzy values. To maximize the fuzzy probability of a system successfully completing a succeeding mission, a selective maintenance model is proposed to identify an optimal subset of maintenance activities to be performed on some elements in the system. A solution algorithm containing three rules to eliminate inferior solutions and narrow down elements' states combinations is proposed to resolve the new selective maintenance model in a computationally efficient manner. An illustrative example of an archibald is presented to demonstrate the effectiveness of the proposed model.
Year
DOI
Venue
2018
10.3233/JIFS-17031
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Keywords
Field
DocType
Selective maintenance,fuzzy multi-state system (FMSS),fuzzy multi-state element (FMSE),fuzzy mission,fuzzy Markov model (FMM),fuzzy universal generating function (FUGF)
Fuzzy logic,Artificial intelligence,Mathematics,Machine learning
Journal
Volume
Issue
ISSN
34
1
1064-1246
Citations 
PageRank 
References 
1
0.36
20
Authors
4
Name
Order
Citations
PageRank
Wenbin Cao120.71
Xisheng Jia2141.94
Yu Liu319019.09
Qiwei Hu4253.47