Impact on composite structures shows a different damage behaviour compared to metal structures. Due to the current short operational life time of composite aircraft the risks of impact damages on composite structures are unknown. This paper proposes a new method for quantitative risk analysis of low velocity impact damages on composite aircraft structures by combining a conventional risk analysis with the probability of detection of the damages. Real damage data of metal structures is used to estimate impactors and to predict damages on composite structures by means of an aircraft impact damage model. To create a large set of impact events and to conduct a more accurate analysis impactor data estimated from the real metal damage data is augmented. Three fuselage sections with a significant difference in amount of damages have been selected to compare the different risk results. The outcome of a conventional risk analysis and the outcome of the probability of detection of damages show that the section with the highest amount of damages results into the highest risk. However, the proposed method by combining the probability of detection of the damages with a conventional risk analysis shows different and more revealing results. The fuselage section with nearly 50% less damages compared to the section with the highest damages appears to be the highest risk section but the difference with the other fuselage sections is small. The proposed risk analysis method intends to be a useful tool for aircraft maintenance organisations for a different approach of assessing the risks of impact damages on composite structures.

In this thesis, a methodology is presented to predict impact damage on next-generation (composite) aircraft based on maintenance data of in-service (metal) aircraft. To achieve this conversion, an analytical model is developed to Model Impact Damage on Aircraft Structures (MIDAS) for composite (-C ) and metal (-M ) aircraft. The model characterizes impact threats based on damage dimensions in two steps. First, for a given specific threat an impact event is approximated, and the corresponding damage (i.e. the permanent dent) is estimated. Second, the analytical model is reverse engineered to deduce the impact threat characteristics from the permanent damage. MIDAS-M implements a new transition region between the local and global deformation modes based on penetration limits, while composite variant (MIDAS-C) provides a novel approach for the permanent indentation in the post fiber breakage region.

Airline Maintenance and Engineering (M&E) organizations are faced with a number of repairs time to time for their fleet of aircraft due to accidental damages. As these damages are unpredictable in nature, the approach to repairing these damages is reactive. These type of repairs fall under the category of corrective or unscheduled maintenance policy compared to the planned preventive or scheduled maintenance. As the occurrence of these unscheduled repairs result in consumption of more maintenance resources in an untimely manner, they add to the existing costs for the organisation. Hence, it is of interest to the M&E to predict the demand for these resources for a future period so that the organisation is better prepared to handle future maintenance activities. One of the resources impacted due to unscheduled repairs is capacity, i.e maintenance hangar facility. If the capacity of a hangar facility can be divided into certain number of slots, then prediction of the demand for these slots would be beneficial to the maintenance planner. In order to identify the demand for these slots, it is first important to forecast the trend of unscheduled repairs. To achieve this goal, i.e. prediction of future repair and determination of slot capacity, a novel application for the integrated use of a reliability and inventory control model has been identified in this thesis. Here, the concepts of inventory control has been specifically applied to a maintenance application to determine the maintenance capacity by taking into account the stochastic demand of unscheduled repairs. The model used to predict the demand of unscheduled repair is a Non-homogeneous Poisson Process (NHPP) reliability model with a Power law intensity function and the inventory control model that was found to be applicable is the singlesystem single location Base-stock policy model. The reliability model considers the superpositioning principle through which the failure behaviour for the entire fleet of aircraft could be predicted. Certain performance measures were identified from the inventory control model, which helped in determining capacity based on optimum costs as well as service level requirements. As a proof of concept, a study is done on identifying the long-run capacity requirements for a fleet of Boeing 777 aircraft of a major European airline. Two specific structural components were identified on which the study was carried out, namely, the leading slats and the outboard flaps. The results showed the successful implementation of the model by identifying 30 slots necessary in the next 1500 flight cycles at an optimum cost for the case of leading edge slats.

Some aircraft damages require immediate attention. Typically, there are several alternative actions, resulting in varying outcomes. Application of MCDM was investigated to quickly choose the best scenario, as this is not always immediately apparent. In doing so, this research contributes to the state-of-the-art by a) considering alternative evaluation for multiple simultaneous operational occurrences and b) performing a comparative analysis of several MCDM methods in terms of applicability, suitability and robustness. WSM, TOPSIS and VIKOR have been identified as potentially appropriate. Using the criteria survivability, time and cost, different scenarios have been evaluated. It resulted that for single occurrences the outcome only varies for very extreme weight settings. In a multiple damage occurrences scenario, i.e. several aircraft competing for limited resources, differences have been found. While TOPSIS and VIKOR generate similar recommendations, WSM yields different results. Furthermore, it was found that VIKOR is not suited for the used heuristic approach, as it results in an ambiguous performance score of several solutions relative to each other. Its sensitivity makes its use in an operational environment questionable, as small changes easily lead to a different recommendation. Looking at the frequent use of a DSS in an operational environment as opposed to a strategic one, WSM is the best choice. This is due to its ease of implementation, its robustness and its simplicity.

The long and therefore expensive training of aircraft maintenance technicians underline the need for accurate demand forecasts that allow for dynamic control of acquisition and training rate of personnel. This control enables human resource management to react swiftly to increases in workforce demand at times of technician shortages. To help human resource management a novel decision support model based on tactical demand forecasts in the aircraft maintenance context is proposed in this paper. Additionally, this paper presents a systematic research towards the optimal models to forecast tactical maintenance demand. The analysis is conducted using aggregated structural repair data of a fleet of wide-body passenger aircraft in the first ten years of its introduction. The results of this study show the potential of the proposed model as it is robust for varying amounts of non-constant workforce outflow and different fleet sizes. Furthermore, the model can be applied efficiently from one year after the acquisition of the first new aircraft. The novelty of this study is the direct integration of personnel training and acquisition with workforce demand forecasts. Additional research is recommended to validate the use of this model on other aircraft types, to explore the use of this model in the area of human resource management optimization and to extent this model to an organizational level