A Probabilistic Approach for Reliability and Life Prediction of Electronics in Drilling and Evaluation Tools
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Abstract
The capability to predict performance and lifetime of drilling electronics is the key to preventing costly downhole tool failures and ensuring success of any drilling operation. Drilling electronics operate under extremely harsh downhole environments with temperatures beyond 150C and vibration levels exceeding 15g. In addition to temperature and vibration, there are several factors affecting electronic reliability that have high uncertainty and cannot be accurately measured. There is a growing trend in the oil and gas industry to drill faster and operate at higher temperatures and pressures, forcing tools to operate beyond design specifications. This has resulted in increased failure rate leading to higher maintenance costs and system downtime for drilling operators as well as service providers. This paper develops a methodology to estimate the life of drilling electronics by using operational data, drilling dynamics and historical maintenance information. The methodology combines parameter estimation techniques, statistical reliability analysis and Bayesian math in a probabilistic framework. Parameter estimation is used to calibrate statistical equations to field data and probabilistic analysis is used to obtain the likelihood of failure. In the paper, the model parameters are represented as random variables, each with a probability distribution. Drilling electronics under downhole conditions can have several failure modes and each failure mode can be caused by the interaction of several variables. When information on each failure mechanism is not readily available, the failure is expressed in terms of several candidate models. Bayesian updating is used to incorporate real time operational history for a specific part and select the most accurate failure model for that part. Tis is for the first time, a systematic approach is developed for predicting the life of electronics in downhole drilling environments using statistical modeling and probabilistic methods on life cycle history and operational data from the field.
How to Cite
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reliability, applications: electronics, probabilistic, predictive analytics, Bayesian updating
Baker Hughes Incorporated. (2010), Repair and Maintenance Return Policy for Printed Circuit Board Assemblies. Document RM-002, Houston TX, USA.
Baker Hughes Incorporated (2008), OnTrak Repair & Maintenance Manual, Document OTK-10-0500-001, Houston TX, USA.
Barker, D., Dasgupta, A., Pecht, M., (1992), PWB solder joint life calculations under thermal and vibrational loading, Journal of The IES, Vol. 35, No.1, February 1992, pp. 17-25. Doi: 10.1109/ARMS.1991.154479.
Born, F., and Boenning, R., A., (1989), Marginal checking – A technique to detect incipient failures, Proceedings of the IEEE Aerospace and Electronics Conference, 22-26 May 1989, pp. 1880 – 1886. Doi. 10.1109/NAECON.1989.40473
Chatterjee, K., Modarres, M., Bernstein, J., B., (2012), Fifty years of physics of failure, Journal of Reliability Information Analysis Center, Vol: 20 #1. Doi: 10.1109/RAMS.2013.6517624.
Dasgupta, A., (1993), Failure mechanism models for cyclic fatigue, IEEE Transactions on Reliability, Vol. 42, No.
4, December 1993, pp. 548-555. Doi:10.1109/24.273577.
Duffek D., (2004), Effect of Combined Thermal and Mechanical Loading on the Fatigue of Solder Joints.Master’s Thesis. University of Notre Dame, IN, USA.
Evans, J., Lall, P., Bauernschub, R., (1995), A framework for reliability modeling of electronics. Proceedings of IEEE Annual Reliability and Maintainability Symposium, January 1995, Washington D. C., USA. DOI 10.1109/RAMS.1995.513238.
Garvey, D., R., Baumann, J., Lehr, J., Hines, J., W., (2009), Pattern recognition based remaining useful life estimation of bottom hole assembly tools. SPE/IADC Drilling Conference and Exhibition, 2009, Amsterdam, The Netherlands. Doi: 10.1109/24.273577.
Gingerich, B., L., Brusius, P., G., Maclean, I., M., (1999), Reliable electronics for high-temperature downhole applications. SPE Annual Technical Conference and Exhibition, 1999, Houston, Texas.
Hu, J., M., Pecht, M., Dasgupta, A., (1991), A probabilistic approach for predicting thermal fatigue life of wire bonding in microelectronics, ASME Journal of Electronics Packaging, Vol. 113, 1991, pp. 275-285. doi:10.1115/1.2905407.
Kalgren, P., W., Baybutt, M., Ginart, A. (2007), Application of prognostic health management in digital electronic systems. IEEE Aerospace Conference, Big Sky, Montana. Doi 10.1109/AERO.2007.352883.
Lall, P., Singh, N., Strickland, M., Blanche, J., Suhling, J., (2005), Decision-support models for thermo- mechanical reliability of lead-free flip-chip electronics in extreme environment. Proceedings of 55th Electronics Components and Technology Conference, Lake Buena Vista, FL, USA. Doi: 10.1109/ECTC.2005.1441257.
Lall, P. (1996), Temperature as an input to microelectronics reliability models. IEEE Transactions on Reliability, vol. 45, no. 1, pp. 3-9.
Lall, P., Choudhary, P., Gupte, S., Suhling, J., Hofmeister,J. (2007), Statistical pattern recognition and built-in reliability test for feature extraction and health monitoring of electronics under shock loads. Proceedings of 57th IEEE, Electronic Components and Technology Conference, 2007, Sparks, Nevada. Doi: 10.1109/ECTC.2007.373942
Mirgkizoudi, M., Changqing, L., Riches, S., (2010), Reliability testing of electronic packages in harsh environments. Proceedings of 12th Electronics Packaging Technology Conference, 2010. Doi: 10.1109/EPTC.2010.5702637
Mishra, S. and Pecht, M. (2002), In-situ sensors for product reliability monitoring, Proceedings of SPIE, Vol. 4755, 2002, pp. 10-19. Doi: 10.1117/12.462807
Nasser, L., Curtin, M. (2006), Electronics reliability prognosis through material modeling and simulation, IEEE Aerospace Conference, Big Sky,Montana. Doi: 10.1109/AERO.2006.1656125
Normann, R. A., Henfling, J. A., Chavira, D. J. (2005),Recent advancements in high-temperature, high- reliability electronics will alter geothermal exploration. Proceedings World Geothermal Congress, Antalya, Turkey.
Osterman, M. (2001), We still have a headache with arrhenius, Electronics Cooling, Vol. 7, Number 1, pp. 53-54, February 2001.
Pecht, M., Radojcic, R., Rao, G. (1999), Guidebook for managing silicon chip reliability, CRC Press, Boca Raton, FL.
Pecht, M., Lall, P., Hakim, E. (1997), Influence of temperature on microelectronics and system reliability, CRC Press, New York, NY
Ridgetop Semiconductor-Sentinel Silicon TM Library, “Hot Carrier (HC) Prognostic Cell,” August 2004
Shinohara, K., Yu, Q. (2010), Evaluation of fatigue life of semiconductor power device by power cycle test and thermal cycle test using finite element analysis. Engineering, 2010, 2, 1006-1018. Doi: 10.4236/eng.2010.212127.
Sutherland, H., Repoff, T., House, M., and Flickinger, G., Prognostics, a new look at statistical life prediction for condition-based maintenance, IEEE Aerospace Conference, 2003. Volume: 7-3131, March 8-15, 2003. Doi: 10.1109/AERO.2003.1234156.
Vichare, N. M. (2006), Prognosis and Health Management of Electronics by Utilizing Environmental and Usage Loads, Doctoral dissertation. 2006, University of Maryland, College Park.
Vichare, N., Rodgers, P., Eveloy, V., Pecht, M., Environment and Usage Monitoring of Electronic Products for Health Assessment and Product Design, Journal of Quality Technology and Quality Management, Vol. 4, No. 2, pp. 235-250, 2007.
Vijayaragavan, N. (2003), Physics of Failure Based Reliability Assessment of Printed Circuit Boards used in Permanent Downhole Monitoring Sensor Gauges. Master dissertation. University of Maryland, College Park, USA.
Wassell, M., Stroehlein, B. (2010), Method of establishing vibration limits and determining accumulative vibration damage in drilling tools. SPE Annual Technical Conference and Exhibition, September 2010, Florence, Italy. Doi: 10.2118/135410-MS
White, M., Bernstein, J. B. (2008), Microelectronics reliability: Physics-of-failure based modeling and lifetime evaluation. NASA Joint Propulsion Laboratory Report, Project Number: 102197.
Wong, K. L. (1995), A new framework for part failure rate prediction models. IEEE Transactions on Reliability, 44(1):139-145, March. Doi: 10.1109/24.376540
Young, D., Christou, A. (1994), Failure mechanism models for electromigration, IEEE Transactions on Reliability, Vol. 43, No. 2, pp. 186 – 192. Doi
10.1109/24.294986
Zhang, H., Kang, R., Pecht, M. (2009), A hybrid prognostics and health management approach for condition based maintenance. IEEE International Conference on Industrial Engineering and Engineering Management, pp1165–1169. Doi 10.1109/IEEM.2009.5372976.
Zhang R., Mahadevan S., 2000, Model uncertainty and Bayesian updating in reliability–based inspection. Structural Safety 22, 145-160.doi 10.1016/S0167- 4730(00)00005-9.
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