Metrics, Models, and Scenarios for Evaluating PHM Effects on Logistics Support
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Abstract
The growing potential of Prognostics and Health Management (PHM) technology to facilitate the maintenance and support of systems emphasizes the need for the ability to determine just what the impacts and benefits of PHM will be. In order to incorporate a capability to evaluate the effects of PHM in logistics support models, the abstraction of PHM metrics and functions is a necessary step. What are the essential prognostics metrics and functions within a logistics support system that will adequately model the effects of PHM? The purpose of this paper is identifying overall categories for understanding the different types of impacts and benefits a PHM system can have from a logistics support perspective. This paper also discusses how prognostics can be assessed by a modeling capability implemented in a legacy logistics support discrete-event simulation, and some examples and results for different support scenarios implementing a prognostics capability.
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logistics, performance metrics, prognostic performance
[2] Saxena, A., Celaya, J. Balaban, E., Goebel, K., Saha, B., Saha, S., Schwabacher, M., “Metrics for Evaluating Performance of Prognostics Techniques,” 2008 International Conference on Prognostics and Health Management, Denver, Colorado, October 2008.
[3] Qiu, H., Eklund, N., Hu, X., Iyer, N., “Evaluation of Filtering Techniques for Aircraft Engine Condition Monitoring and Diagnosis,” 2008 International Conference on Prognostics and Health Management, Denver, Colorado, October 2008.
[4] Kurtoglu, T., Mengschoel, O., Poll, S., “A Framework for Systematic Benchmarking of Monitoring and Diagnostic Systems,” 2008 International Conference on Prognostics and Health Management, Denver, Colorado, October 2008.
[5] Saxena, A., Goebel, K., Simon, D., Eklund, N., “Prognostics Challenge Competition Summary: Damage Propagation Modeling for Aircraft Engine Run-to-Failure Simulation,” 2008 International Conference on Prognostics and Health Management, Denver, Colorado, October 2008.
[6] Wang, T., Lee, J., “On Performance Evaluation of Prognostics Algorithms,” 2009 Machine Failure Prevention Technology Conference, Dayton, Ohio, April 2009.
[7] Sandborn, P. A., Wilkinson, C., “A Maintenance Planning and Business Case Development Model for the Application of Prognostics and Health
Management (PHM) to Electronic Systems,” Microelectronics
Reliability, vol. 47, no. 12, pp. 1889–1901, Dec. 2007.
[8] Feldman, K., Sandborn, P., Jazouli, T., “The Analysis of Return on
Investment for PHM Applied to Electronic Systems,” 2008 International Conference on Prognostics and Health Management, Denver, Colorado, October 2008.
[9] Feldman, K., Jazouli, T., Sandborn, P., “A Methodology for Determining the Return on Investment Associated with Prognostics and Health Management,” IEEE Transactions on Reliability, vol. 58, no. 2, pp. 305-316, June 2009.
[10] Scanff, E., Feldman, K. L., Ghelam, S., Sandborn, P., Glade, M., Foucher, B., “Life Cycle Cost Impact of Using Prognostic Health Management (PHM) for Helicopter Avionics,” Microelectronics Reliability, vol. 47, no. 12, pp. 1857-1864, Dec. 2007.
[11] Shroder, R., Frankle, N., “Economic Modeling for Prognostic Health Management,” 2008 Machine Failure Prevention Technology Conference, Dayton, Ohio, April 2008.
[12] Williams, Z., Gilbertson, D., Sheffield, G., “Fleet Analysis and Planning Using CBM+ Open Architecture,” 2008 International Conference on Prognostics and Health Management, Denver, Colorado, October 2008.
[13] Hess, R. A., Heimes, F. O., Propes, N. C., “A Health Management Solution for Hybrid Electric Vehicle Transit Fleets,” 2008 International Conference on Prognostics and Health Management, Denver, Colorado, October 2008.
[14] Jessop, S., Cook, T. C., “A Model-Based Mission Planning and Decision Support Tool,” 2009 Machine Failure Prevention Technology Conference, Dayton, Ohio, April 2009.
[15] Gebraeel, N., Elwany, A., “An Adaptive Prognostic Methodology for Sensor-Driven Component Replacement and Spare Parts Ordering Policies,” 2009 Machine Failure Prevention Technology Conference, Dayton, Ohio, April 2009.
[16] Bedard, P., “Prioritizing Prognostic and Reliability Growth Investments,” 2009 Machine Failure Prevention Technology Conference, Dayton, Ohio, April 2009.
[17] Luna, J., “A Probabilistic Model for Evaluating PHM Effectiveness,”
2008 International Conference on Prognostics and Health Management, Denver, Colorado, October 2008.
[18] (Unpublished work style) PHM Implementation in SEM, Sandia
National Laboratories, Albuquerque, NM, 2003.
[19] (Presentation style) Implementating PHM in SEM, Sandia National
Laboratories, Albuquerque, NM, 2003.
[20] (Manual style) ASC LCOM 2.7.1 User’s Manual, Aeronautical Systems
Command, ASC/ENMS, Wright-Patterson AFB, OH, 2005.
[21] (Manual style) ASC LCOM 2.6 User’s Manual, Aeronautical Systems
Command, ASC/ENMS, Wright-Patterson AFB, OH, 2004.
[22] Luna, J., Kolodziejski, P., Frankle, N., Conroy, D. C., Shroder, R., “Strategies for Optimizing the Application of Prognostic Health Management to Complex Systems,” 2009 Machine Failure Prevention Technology Conference, Dayton, Ohio, April 2009.
[23] Pipe, K., “Practical Prognostics for Condition Based Maintenance,”
2008 International Conference on Prognostics and Health Management, Denver, Colorado, October 2008.
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