Building flexibility in the volatile aftermarket parts : supply chains of the defense aerospace industry

Abstract

Within the Integrated Defense Systems of The Boeing Company, aftermarket support of military aircraft serves as an increasingly large source of revenue. One of the newest contracts between Boeing and the U.S. Government created such a supply partnership at the Army Rotorcraft Repair Depot in Corpus Christi, Texas. At this depot, all Army helicopters, including Boeing's AH-64 Apache Attack helicopter and CH-47 Chinook Cargo helicopter undergo major repair and overhaul. In 2004, Boeing entered an agreement with the U.S. Government to assume responsibility of the repair depot's supply chain for aftermarket parts for Boeing rotorcraft. Over the last two years, Boeing has been creating and refining Corpus Christi's support structure to ensure that the required repair parts arrive when demanded. In establishing this new supply chain, Boeing has identified numerous inefficiencies as a result of inaccurate and highly volatile forecasts. This thesis examines the impact of volatility within the new support structure and creates flexible solutions to mitigate its negative effects on lead times, multiple sources of supply and inventory management.

(cont.) Efforts to increase communication flow across the supply chain are used to capitalize on economies of scale for cost reduction while safety stock recommendations are made for critical end-items. Monte Carlo simulations are employed to justify and validate the solutions. The results of the thesis reveal that a strategic selection of raw material safety stock can reduce procurement lead times by an average 61% for a subset of parts while maintaining financial responsibility. Additionally, by leveraging cost reduction techniques, an average increase of 11% in Boeing's income from sales can be achieved while eliminating inefficient administrative delays and increasing customer fulfillment rates. These two recommendations demonstrate specific solutions for mitigating the effects of demand volatility and inaccurate forecasting.