Finding the optimal CSP inventory level for multi-echelon system in Air Force using random effects regression model
Determining the optimal inventory level of CSP (concurrent spare parts) is crucial at the time of acquisition of new aircrafts. Most of the existing optimal CSP models do not take into account the time varying characteristics of CSP even though their demand rates are sensitive to such variation. In this paper, we introduce the CSP inventory model using a two stage approach. At the first stage, we use a random effects model to predict the expected demand of CSP in a multi-echelon system consisting of depot and bases based on CSPs varying characteristics with time. At the second stage, we find the optimal inventory level of CSP by using the optimization algorithm with various constraints under limited budget. The study is expected to contribute to the Air Force establishing the optimal national defense procurement policy for CSP of aircrafts.
csp multi-echelon aircraft random effects model two stage optimization