Using Condition Based Maintenance to Improve the Profitability of Performance Based Logistic Contracts
This paper outlines a scheduling algorithm which leverages Condition-Based Maintenance (CBM) data to determine when maintenance should be performed. The objective of the scheduler is to reduce the cost associated with Performance-Based Logistics contracts, which ultimately improves the profit margins of Product Support Providers.An example consisting of 50 aircraft for which regular recurring maintenance and CBM actions are required is analyzed as a representative problem both in term of complexity and scale. The results indicate that significant cost savings can be achieved by utilizing a CBM scheduling algorithm. In addition, to the maintenance cost savings, the CBM scheduling algorithm is also able to identify potential resource limitations within the maintenance organization.
How to Cite
classification, condition based maintenance (CBM), cost-benefit analysis, economics and cost-benefit analysis, fleet-level optimization, performance based logistics (PBL), platform operational availability
R. Warburton, An Analytical Investigation of the Bullwhip Effect, Production and Operations Management, Vol. 13, No. 2, pp. 150-160, 2004.
H. Kellerer and V. Strusevich, Scheduling Problems for Parallel Dedicated Machines under Multiple Resource Constraints, Descrete Applied Mathemathics 113, 2004, 45-68.
H. Kellerer and V. Strusevich, Scheduling Parallel Dedicated Machines with the Speeding-Up Resource, Naval Research Logistics, Vol. 55, 2008.
T. Loukil, J. Teghem and P. Fortemps, A multi- objective production scheduling case study solved by simulated annealing, European Journal of Operational Research 179, 2007, pp. 709-722.
T. Abdui-Razaq and C Potts, Dynamic programming state-space relaxation for single machine scheduling, Journal of Oper. Res. Soc. V ol. 39 pp. 141-152, 1988.
F. Sourd and S. Kedad-Sidhoum, The one-machine problem with earliness and tardiness penalties,
Journal of Scheduling, Vol. 6 pp. 533-549, 2003.
H. Yau, Y. Pan, and L. Shi, New Solution Approaches to the General Single-Machine Earliness-Tardiness Problem, in IEEE Transactions on Automation Science and Engineering, Vol. 5, No. 2, April 2008.
E. Shchepin, and N. Vakhania, On the geometry, preemptions and complexity of multiprocessor and shop scheduling, in Annals of Operations Research, Springer, 2008.
N. Amato, P. An. Task Scheduling and Parallel-Mesh- Sweeps in Transport Computations, Technical Report, TR00-009, Department of Computer Science, Texas A&M University, 2000.
T. Cormen, C. Leiserson, and R. Rivest. Introduction to Algorithms, MIT press Cambridge, Massachusetts.
C. Papadimitriou, and K.Steiglitz. Combinatorial Optimization: Algorithms and Complexity, Dover Publications, Mineola, New York.
R. Stapelberg, Handbook of Reliability, Availability, Maintainability and Safety in Engineering Design, Springer, 2008.
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