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Title: Multi-objective system optimisation with respect to availability, maintainability and cost
Author: Nggada, Shawulu Hunira
ISNI:       0000 0004 2723 0228
Awarding Body: University of Hull
Current Institution: University of Hull
Date of Award: 2012
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Safety critical engineering systems are becoming increasingly larger and more complex. One way of ensuring the dependability of such systems is via architectural redundancy and replication of components. Use of redundancy has its limitations though, as it can increase the size, weight and cost of a system beyond acceptable levels. An alternative approach to improving dependability is by designing the system with preventive maintenance (PM) in mind. A well articulated PM policy can reduce the occurrence of system failure, thereby improving dependability attributes such as safety, reliability and availability as well as cost. In a typical scenario, components of the system are maintained periodically at a fixed time interval (month, year, etc). This interval may vary from component to component and therefore the determination of an optimal PM schedule for all components in the system is non trivial. The options for maintenance are simply too many to exhaustively enumerate and evaluate, and therefore the choice of an optimal PM schedule that provide the best trade-offs between dependability and cost becomes a search and optimisation problem. It is precisely this problem that this thesis addresses. Firstly, the thesis investigates the effects of perfect and imperfect preventive maintenance policies on system reliability, availability and cost by establishing mathematical models for both policies. Secondly, a multi-objective optimisation approach is formulated for PM scheduling that takes into account dependability and cost, and finally the approach is evaluated on two case studies using a well-established semi-automated dependability analysis tool - HiP-HOPS. The approach allows automatic model transformation such as substitution of components as well as PM maintenance to be applied by Genetic Algorithms as mechanisms for automatically improving design and achieving trade-offs between dependability and cost. Results from case studies show that this approach can provide an effective tool for definition of PM schedules and lead to engineering and economic benefits.
Supervisor: Papadopoulous, Yiannis. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Computer science