Rollingstock Maintenance Strategy Selection by Application of the Analytic Network Process Algorithm
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Date
2019-07-04
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Abstract
Industries are facing a lot of challenges such as the optimization of operation and maintenance function
due to the continually evolving world of technologies, global competitiveness, environmental and safety
requirements. Thus, this study sets out to select an appropriate maintenance strategy with the use of one
of the various Multi-Criteria Decision Making (MCDM) methods known as Analytic Network Process
(ANP). This study is aimed at selecting an appropriate maintenance strategy to be adopted at AALRTS.
This consists of determination of evaluating criteria and maintenance strategies to be used in the study.
Thereafter, there is formation of a model, pairwise comparisons based on the model formulated and
validation of a model and to achieve this, a survey is carried out in three phases using questionnaires to
be filled by a group of experts from the Addis Ababa University, Ethiopian Railway Corporation and
Addis Ababa Light Rail Transit depot maintenance and management personnel to narrow down the
evaluating criteria that were gotten from the literature review. The model used to analyze and evaluate
the data is Analytic Network Process (ANP) and a software, SUPERDECISION is used to assist with
the analysis. The results obtained is Total Productive Maintenance as the most recommended suitable
maintenance strategies and Corrective maintenance as the least recommended alternative. The strategies
currently being utilized at AALRT are preventive maintenance and corrective maintenance. Application
of the new recommended strategy (CBM & TPM) can improve company operations, improve the whole
system safety, improve company profitability and hence competitiveness.
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Keywords
ANP, Maintenance, strategy selection, super-decision