An analysis of Saudi Arabian Air Force Academy's system
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Date
2013
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University of New Brunswick
Abstract
The system used by the Saudi Arabian Air Force Academy (SAAFA) 's maintenance department is paper-based. It has significant weaknesses that impact the efficiency of the maintenance processes and imposes excessive costs, such as labour intensive manual documentation and, of course, human errors. The system must be enhanced in order to minimize the risk of maintenance quality and to improve aircraft safety. This can be done by automating the current system processes. In this report, the current system of SAAFA's maintenance department is analysed by depicting its current processes graphically using the Business Process Model and Notation methodology (BPMN) to identify processes that need to be enhanced and then automated. Spare parts management is an important process that must be improved to avoid spare parts shortages and overstocking. To facilitate spare parts management, spare parts are categorized into seven categories based on three criteria: criticality, demand and supply predictability, and costs. Then, two inventory policies are applied to the categories to optimize the two decisions: when to order new stock and how much to order. The two policies are the (s, Q)-policy and the (r, S)-policy. However, the comparison between the current inventory policy and the proposed policies is measured by analysing spare parts availability and their associated costs, i.e. order, emergency, and holding costs, in both policies. The analysis of the current policy and the proposed policies shows that the two proposed policies give higher spare parts availability and lower associated costs than the current one. Moreover, methodologies of other processes, e.g. missing tools methodology, are modified based on the requirements of the automated system and the feedback that has been received from SAAFA. The proposed system is designed based upon the technique of the Work flow Management System (WfMS), a database-based system, and modeled using BPMN. The proposed system reduces maintenance time and associated costs, reduces human interaction, and increases the accuracy of tracking maintenance operations and history.