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Title: Criticality strategic decision making model for maintenance and asset management
Author: Moghaddaszadeh Kermani, Mohammad
ISNI:       0000 0004 6425 5299
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2016
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Over the last century, there has been growing interest in changing the approach to maintenance management. The current practice for selecting critical equipment and making a decision on the most appropriate maintenance strategy is perceived to have serious limitations, principally because it lacks decision analysis. Due to the complex nature of decision-making in maintenance management, different models have been developed for selecting critical equipment. However, many of these models considered maintenance management as operational concern and ignored the strategic concerns of maintenance management. This thesis builds upon earlier works on decision-making for selecting critical equipment and maintenance strategy. It sets out to construct three hypotheses by introducing evidence from a comprehensive literature review, case study analysis and in-depth interviews. The thesis focuses on artificial intelligence and multi-criteria decision-making techniques (i.e. Fuzzy Logic and Analytical Hierarchy Process) to bridge this gap. It proposes a strategic decision-making model in maintenance and asset management for selecting critical equipment and deciding on a maintenance strategy. The novelty of model is to propose an approach in which maintenance strategy can be applied based on the equipment criticality while not making a trade-off between safety and cost but rather to combine the concern of safety with financial, operational and technical perspectives. The model provides an opportunity to consider safety as the first priority. The research output suggests that existing criticality assessment methods for optimising maintenance delivery have limited value and are suffering from a lack of strategic decision analysis. Multi-criteria decision-making tools could be used to improve decision-making of criticality assessment methods and hence maintenance strategy implementation. The validity of the proposed strategic decision-making model was tested through case study analysis and in-depth interviews. The results suggest that a strategic decision-making model could have a significant impact on improving safety, reliability and operational availability. The strategic decision-making model would enable asset managers to track the consequences of their decisions whilst dealing with maintenance. It is also an effective tool in the hands of a maintenance department to convince their asset managers to make a maintenance investment.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Asset Management ; Strategic Decision Making ; Artificial Intelligence ; Fuzzy Logic ; Analytical Hierarchy Process