The aim of this research is to propose an alternative approach to determine the maintainability prediction for aircraft components. In this research, the author looks at certain areas of the maintainability prediction process where missteps or misapplications most commonly occur. The first of these is during the early stage of the Design for Maintainability (DfMt) process. The author discovered the importance of utilising historical information or feedback information. The second area is during the maintainability prediction where the maintenance of components is quantified; here, the author proposes having the maximum target for each individual maintainability component. This research attempts to utilise aircraft maintenance historical data and information (i.e. feedback information systems). Aircraft feedback information contains various types of information that could be used for future improvement rather than just the failure elements. Literature shows that feedback information such as Service Difficulty Reporting System (SDRS) and Air Accidents Investigation Branch, (AAIB) reports have helped to identify the critical and sensitive components that need more attention for further improvement. This research consists of two elements. The first is to identity and analyse historical data. The second is to identify existing maintainability prediction methodologies and propose an improved methodology. The 10 years’ data from Federal Aviation Administration (FAA) SDRS data of all aircraft were collected and analysed in accordance with the proposed methodology before the processes of maintainability allocation and prediction were carried out. The maintainability was predicted to identify the potential task time for each individual aircraft component. The predicted tasks time in this research has to be in accordance with industrial real tasks time were possible. One of the identified solutions is by using maintainability allocation methodology. The existing maintainability allocation methodology was improved, tested, and validated by using several case studies. The outcomes were found to be very successful. Overall, this research has proposed a new methodology for maintainability prediction by integrating two important elements: historical data information, and maintainability allocation. The study shows that the aircraft maintenance related feedback information systems analyses were very useful for deciding maintainabilityeffectiveness; these include planning, organising maintenance and design improvement. There is no doubt that historical data information has the ability to contribute an important role in design activities. The results also show that maintainability is an importance measure that can be used as a guideline for managing efforts made for the improvement of aircraft components.

The aim of this research is to propose an alternative approach to determine the maintainability prediction for aircraft components. In this research, the author looks at certain areas of the maintainability prediction process where missteps or misapplications most commonly occur. The first of these is during the early stage of the Design for Maintainability (DfMt) process. The author discovered the importance of utilising historical information or feedback information. The second area is during the maintainability prediction where the maintenance of components is quantified; here, the author proposes having the maximum target for each individual maintainability component. This research attempts to utilise aircraft maintenance historical data and information (i.e. feedback information systems). Aircraft feedback information contains various types of information that could be used for future improvement rather than just the failure elements. Literature shows that feedback information such as Service Difficulty Reporting System (SDRS) and Air Accidents Investigation Branch, (AAIB) reports have helped to identify the critical and sensitive components that need more attention for further improvement. This research consists of two elements. The first is to identity and analyse historical data. The second is to identify existing maintainability prediction methodologies and propose an improved methodology. The 10 years’ data from Federal Aviation Administration (FAA) SDRS data of all aircraft were collected and analysed in accordance with the proposed methodology before the processes of maintainability allocation and prediction were carried out. The maintainability was predicted to identify the potential task time for each individual aircraft component. The predicted tasks time in this research has to be in accordance with industrial real tasks time were possible. One of the identified solutions is by using maintainability allocation methodology. The existing maintainability allocation methodology was improved, tested, and validated by using several case studies. The outcomes were found to be very successful. Overall, this research has proposed a new methodology for maintainability prediction by integrating two important elements: historical data information, and maintainability allocation. The study shows that the aircraft maintenance related feedback information systems analyses were very useful for deciding maintainabilityeffectiveness; these include planning, organising maintenance and design improvement. There is no doubt that historical data information has the ability to contribute an important role in design activities. The results also show that maintainability is an importance measure that can be used as a guideline for managing efforts made for the improvement of aircraft components.