Demand forecasting for aircraft engine aftermarket

Abstract

In 2006, Pratt and Whitney launched the Global Material Solutions business model aiming to supply spare parts to non-OEM engines with minimum 95% on-time delivery and fill-rate. Lacking essential technical knowledge of the target engines, predictability and associated confidence of the parts demands are very limited. This thesis focuses on exploring alternative and innovative approaches to providing more accurate demand forecasts based on limited information. Approaches including application of fundamental sampling theorems, random walk simulations based on Markov Chain simplification, and sensitivity analysis on incremental scrap rates were introduced. A software tool, based on the sensitivity analysis was introduced for all gas path parts. The methodology could potentially be applicable to industries other than Aerospace.