Aircraft scheduled maintenance programme development : decision support methodologies and tools

The air transport business is large in its operations, integrated, automated and complex. Air carriers are constantly striving to achieve high standards of safety and simultaneously to attain an increased level of availability performance at minimal cost. This needs to be supported through an effective maintenance programme which has a major impact on the availability performance and which ultimately can enhance the aircraft’s capability to meet market demands at the lowest possible cost. The development of a maintenance programme is challenging, but can be enhanced by supporting methodologies and tools. The purpose of this study is to develop decision support methodologies and tools for aircraft scheduled maintenance programme development within the framework of Maintenance Review Board (MRB) process. To achieve the purpose of the research, literature studies, case studies, and simulations have been conducted. Empirical data have been collected through document studies, interviews, questionnaires, and observations from the aviation industry. For data analysis, theories and methodologies within risk, dependability and decision making have been combined with the best practices from the aviation industry. One result of the research is the identification of potential areas for improving the use of MSG-3 methodology in aircraft scheduled maintenance development. Another result is the development of a systematic methodology guided by the application of an Event Tree Analysis (ETA) for the identification and quantification of different operational risks caused by aircraft system failures, to support decision making for maintenance task development. A third result is a proposed methodology, based on a combination of different Multi-Criteria Decision Making (MCDM) methodologies, for selecting the most effective maintenance strategy for aircraft scheduled maintenance development. Finally, the fourth result is a proposed Cost Rate Function (CRF) model supported by a graphical approach. The approach can be used to identify the optimum maintenance interval and frequencies of Failure Finding Inspection (FFI) and to develop a combination of FFI and restoration tasks for the aircraft’s repairable items which are experiencing aging. These results are related to some of the specific industrial challenges, and are expected to enhance the capability of making effective and efficient decisions during the development of maintenance tasks. The results have been verified through interaction with experienced practitioners within major aviation manufacturers and air operators