Dynamic human resource management decision support model based on tactical aircraft maintenance demand forecasts

Abstract

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