End-of-life inventory control of aircraft spare parts under performance based logistics

Abstract We consider an inventory control problem of aircraft spare parts during the end-of-life (EOL) phase of fleet operations. For these spare parts, demand rates vary with the diminishing number of operational aircraft, as the aircraft retire out of service. As aircraft approach to the EOL phase, managing the spare parts supply chain becomes more challenging and costly. Before entering the EOL period, the aircraft manufacturer typically requires its customers to place final purchase orders for spare parts for the remaining lifetime of the aircraft. For this problem, we present an algorithm that computes the optimal final order size of components under a budget constraint. By modeling the remaining part inventory as a continuous-time Markov chain, we develop analytical solutions using differential equations for single and two-item cases. After observing numerical difficulty for the multi-item case, we employ a simulation-optimization with a gradient search method. The algorithm finds the spares requirement of aircraft components during the EOL period with aircraft availability which serves as a useful performance metric during the spare part supply chain management under a performance-based logistics (PBL) environment.

[1]  Ruud H. Teunter,et al.  Inventory control of service parts in the final phase , 2002, Eur. J. Oper. Res..

[2]  Ruud H. Teunter,et al.  End-of-life service , 1999 .

[3]  Stephen C. Graves,et al.  A Multi-Echelon Inventory Model for a Repairable Item with One-for-One Replenishment , 1985 .

[4]  T. Tan,et al.  The final order problem for repairable spare parts under condemnation , 2009, J. Oper. Res. Soc..

[5]  Ruud H. Teunter,et al.  The 'final orderrs problem , 1998, Eur. J. Oper. Res..

[6]  Leonard Fortuin,et al.  The All‐Time Requirement of Spare Parts for Service After Sales—Theoretical Analysis and Practical Results , 1980 .

[7]  Rommert Dekker,et al.  Customer differentiated end-of-life inventory problem , 2011, Eur. J. Oper. Res..

[8]  Alireza Ahmadi,et al.  Part-out-based spares provisioning management: A military aviation maintenance case study , 2014 .

[9]  Jr. John R. Moore Forecasting and Scheduling for Past-Model Replacement Parts , 1971 .

[10]  Rainer Kleber,et al.  An Advanced Heuristic for Multiple‐Option Spare Parts Procurement after End‐of‐Production , 2013 .

[11]  Mokhtar S. Bazaraa,et al.  Nonlinear Programming: Theory and Algorithms , 1993 .

[12]  J. B. Rosen The Gradient Projection Method for Nonlinear Programming. Part I. Linear Constraints , 1960 .

[13]  J. Muckstadt A Model for a Multi-Item, Multi-Echelon, Multi-Indenture Inventory System , 1973 .

[14]  Roxanna Sun,et al.  F-35 Joint Strike Fighter: Problems Completing Software Testing May Hinder Delivery of Expected Warfighting Capabilities , 2014 .

[15]  Craig C. Sherbrooke,et al.  Metric: A Multi-Echelon Technique for Recoverable Item Control , 1968, Oper. Res..

[16]  Mark S. Daskin,et al.  The effect of lifetime buys on warranty repair operations , 2010, J. Oper. Res. Soc..

[17]  L. Venkat Raghavan,et al.  3D Metal Printing Technology , 2016 .

[18]  Serguei Netessine,et al.  Performance Contracting in After-Sales Service Supply Chains , 2007, Manag. Sci..

[19]  Ahmad Al Hanbali,et al.  Last time buy and repair decisions for spare parts , 2015, Eur. J. Oper. Res..

[20]  Gilvan C. Souza,et al.  Good buy? Delaying end-of-life purchases , 2003, Eur. J. Oper. Res..

[21]  Edward B. Saff,et al.  Fundamentals of Differential Equations and Boundary Value Problems, 6th Edition , 1993 .

[22]  T. M. Whitin,et al.  An Optimal Final Inventory Model , 1961 .

[23]  Craig C. Sherbrooke,et al.  VARI-METRIC: Improved Approximations for Multi-Indenture, Multi-Echelon Availability Models , 1986, Oper. Res..

[24]  David R. Kincaid,et al.  Numerical mathematics and computing , 1980 .