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Title: Stochastic modelling and maintenance optimization of systems subject to deterioration
Author: Ahmadi, Reza
ISNI:       0000 0004 2706 1049
Awarding Body: City University London
Current Institution: City, University of London
Date of Award: 2011
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During the past decades to prevent catastrophic failure of the system, avoiding potential costs arising from the system downtime and optimize maintenance costs, there has been an interest in maintenance optimization problem for repairable systems subject to deterioration. Here to tackle the maintenance optimization problem two maintenance models for deteriorating repairable systems are proposed: optimal preventive maintenance scheduling model (decision model) and optimal maintenance-repair and inspection-scheduling model (intensity control model). In chapter 4 under both periodic and non-periodic inspection policy a novel approach to the determination of optimal repair and replacement decision rule subject to system parameters is presented. A renewal argument is used to derive expressions for the long-run average cost per unit time under theses two kinds· of inspection policy. The second part of the research (see chapter 5) considers maintenance scheduling problem of manufacturing systems whose production process (resulting output) is subject to system state. The latter means, resulting outputs (revenue) from system depends on the deterioration level of the manufacturing system: the good state of the system results in more efficiency of the system and more resulting output (revenue); the bad state of the system leads to system malfunction and less revenue. To optimize revenue from the manufacturing system, using optimal intensity control model, an optimum repair and inspection policy to balance the the amount of maintenance requires to increase system efficiency against the loss of revenue arising from the system malfunction is presented. Our approach rests on assumption that the transition rate from good (normal) state to bad (degraded) state is linear/non-linear. Deriving expression for long-run average cost per unit of time under both periodic and non-periodic inspection policy, applying the repair alert and virtual age process model, is the main advantage of the presented decision model to other maintenance models. In addition, using intensity control model, optimizing revenue from manufacturing systems subject to deterioration is a novel approach to maintenance scheduling of manufacturing systems whose production process is subject to the system state and represent an extension of the known maintenance models in which the maintenance process is restricted to inspections.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: HA Statistics ; QA Mathematics