Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/10389
Title: Optimization of the maintenance process using genetic algorithms
Authors: Nestic, Snezana
Djordjevic, Aleksandar
Aleksic, Aleksandar
Macuzic, Ivan
Stefanovic, Miladin
Issue Date: 2013
Abstract: In this paper, we will present an approach for assessment and ranking of maintenance process performance indicators using the fuzzy set approach and genetic algorithms. Weight values of maintenance process indicators are defined using the experience of decision makers from analysed SMEs and calculated using the fuzzy set approach. In the second step, a model for ranking and optimization of maintenance process performance indicators and SMEs is presented. Based on this, each SME can identify their maintenance process weaknesses and gaps, and improve maintenance process performance. The presented model quantifies maintenance process performances, ranks the indicators and provides a basis for successful improvement of the quality of the maintenance process. Copyright © 2013, AIDIC Servizi S.r.l.
URI: https://scidar.kg.ac.rs/handle/123456789/10389
Type: conferenceObject
DOI: 10.3303/CET1333054
ISSN: 2283-9216
SCOPUS: 2-s2.0-84883746007
Appears in Collections:Faculty of Engineering, Kragujevac

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