Abstract
Degradation signals provide more information for product life status than failure data, when specific degradation mechanism can be identified. Modeling and analysis with the degradation signal is helpful to extrapolate for product lifetime prediction. In this chapter, comprehensive review has been conducted for different kinds of modeling and analysis approaches, together with the corresponding lifetime prediction results. Furthermore, discussions over related issues like product initial performance are presented.
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References
Nelson W (1981) Analysis of performance-degradation data from accelerated tests. IEEE Trans Reliab 30(2):149–155
Wang FK, Chu TP (2012) Lifetime predictions of led-based light bars by accelerated degradation test. Microelectron Reliab 52(7):1332–1336
Escobar LA, Meeker WQ, Kugler DL, Kramer LL (2015) Accelerated destructive degradation tests: data, models and analysis. Math Stat Methods Reliab:319–337
Shiau JJH, Lin HH (1999) Analyzing accelerated degradation data by nonparametric regression. IEEE Trans Reliab 48(2):149–158
Rohner M, Kerber A, Kerber M (2006) Voltage acceleration of TBD and its correlation to post breakdown conductivity of N- and P-Channel MOSFETs. IEEE Int Reliab Phys Symp Proc:76–81
Zhang J, Li W, Cheng G, Chen X, Wu H, Shen MHH (2014) Life prediction of OLED for constant-stress accelerated degradation tests using luminance decaying model. J Lumin 154:491–495
Guan Q, Tang Y, Xu A (2015) Objective Bayesian analysis accelerated degradation test based on Wiener process models. Appl Math Model 40(4):2743–2755
Pan Z, Balakrishnan N, Sun Q (2011) Bivariate constant-stress accelerated degradation model and inference. Commun Stat Simul Comput 40(2):259–269
Wan F, Zhang C, Tan Y, Chen X (2014) Data analysis and reliability estimation of step-down stress accelerated degradation test based on Wiener process. Prog Sys Health Manage Conf:41–45
Pan Z, Sun Q (2014) optimal design for step-stress accelerated degradation test with multiple performance characteristics based on Gamma processes. Commun Stat Simul Comput 43(2):298–314
Ge Z, Li XY, Jiang TM, Huang TT (2011) optimal design for step-stress accelerated degradation testing based on D-optimality. Reliab Maint Symp:1–6
Guo CS (2011) Online degradation model based on process-stress accelerated test. Acta Phys Sin 60:128501
Peng CY, Tseng ST (2010) Progressive-stress accelerated degradation test for highly-reliable products. IEEE Trans Reliab 59(1):30–37
Boulanger M, Escobar LA (1994) Experimental design for a class of accelerated degradation tests. Technometrics 36(3):260–272
Park C, Padgett WJ (2005) Accelerated degradation models for failure based on geometric Brownian motion and Gamma processes. Lifetime Data Anal 11(4):511–527
Tang S, Guo X, Yu C, Xue H, Zhou Z (2014) Accelerated degradation tests modeling based on the nonlinear Wiener process with random effects. Math Probl Eng 2014(2):1–11
Sang BK, Kim SH (2015) Estimation of elevator wire life using accelerated degradation model. J Korean Soc Qual Manag 43(3):409–420
Liu HC (2014) Gauss-power law accelerated degradation model about reliability assessment of electronic products. Journal of Guiyang University
Yang Z, Chen YX, Li YF, Zio E, Kang R (2013) Smart electricity meter reliability prediction based on accelerated degradation testing and modeling. Int J Elect Power Energy Syst 56(3):209–219
Hayes KC, Wolfe DL, Trujillo SA, Burkell JA (2010) On the interaction of disability and aging: accelerated degradation models and their influence on projections of future care needs and costs for personal injury litigation. Disabil Rehabil 32(5):424–428
Yang G, Zaghati Z (2006) Accelerated life tests at higher usage rates: a case study. Reliability and maintainability symposium, 313–317
Yellamati D, Arthur E, James S, Morris G, Heydt T, Graf E (2013) Predictive reliability models for variable frequency drives based on application profiles. 2013 Proceedings Reliability and Maintainability Symposium (RAMS), 1–6
Hwang DH, Park JW, Jung JH (2011) A study on the lifetime comparison for electric double layer capacitors using accelerated degradation test. International Conference on Quality, Reliability, Risk, Maintenance and Safety Engineering, 302–307
Shen CN, Xu JJ, Chao MC (2014) A study for the relationship between drive level and the activation energy in arrhenius accelerated aging model for small size quartz resonators. 2014 IEEE International Frequency Control Symposium (FCS), 1–3
Cooper MS (2005) Investigation of arrhenius acceleration factor for integrated circuit early life failure region with several failure mechanisms. IEEE Trans Compon Packag Technol 28(3):561–563
Zhou J, Yao J, Song Y, Hu HH (2014) The step-down-stress accelerated storage testing evaluation methods of small sample electronic products based on arrhenius model. 2014 10th international conference on reliability, maintainability and safety (ICRMS), 908–912
Dai HF, Zhang XL, Gu WJ, Wen XZ, Sun ZC (2013) A semi-empirical capacity degradation model of ev li-ion batteries based on eyring equation. IEEE Vehicle Power and Propulsion Conference (VPPC), 1–5
Endicott H, Hatch B, Sohmer R (1965) Application of the eyring model to capacitor aging data. IEEE Trans Compon Parts 12(1):34–41
Meeker WQ, Escobar LA (1998) Statistical methods for reliability data
Wu EY, Sune J (2009) On voltage acceleration models of time to breakdown-part I: experimental and analysis methodologies. IEEE Trans Electron Devices 56(7):1433–1441
Hu LC, Kang AC, Wu TY, Shih JR, Lin YF, Wu K, King YC (2006) Efficient low-temperature data retention lifetime prediction for split-gate flash memories using a voltage acceleration methodology. IEEE Trans Device Mater Reliab 6(4):528–533
Padgett WJ, Durham SD, Mason AM (1995) Weibull analysis of the strength of carbon fibers using linear and power law models for the length effect. J Compos Mater 29(14):1873–1884
Escobar LA, Meeker WQ (2007) A review of accelerated test models. Stat Sci 21(4):552–577
Zuo MJ, Renyan J, Yam R (1999) Approaches for reliability modeling of continuous-state devices. IEEE Trans Reliab 48(1):9–18
Wang L, Zhang H, Xue H (2012) Life prediction based on degradation amount distribution using composite time series analysis. Ieri Procedia 1(9):217–224
Ye ZS, Xie M (2014) Stochastic modelling and analysis of degradation for highly reliable products. Appl Stoch Model Bus Ind 31(1):16–32
Tseng ST, Tang J, Ku IH (2003) Determination of burn-in parameters and residual life for highly reliable products. Nav Res Logist 50(1):1–14
Joseph VR, Yu IT (2006) Reliability improvement experiments with degradation data. IEEE Trans Reliab 55(1):149–157
Si XS, Wang W, Hu CH, Chen MY, Zhou DH (2013) A Wiener-process-based degradation model with a recursive filter algorithm for remaining useful life estimation. Mech Syst Signal Process 35(1–2):219–237
Wang H, Xu T, Mi Q (2015) Lifetime prediction based on gamma processes from accelerated degradation data. Chin J Aeronaut 28(1):172–179
Iervolino I, Giorgio M, Chioccarelli E (2013) Gamma degradation models for earthquake-resistant structures. Struct Saf 45(45):48–58
Noortwijk JMV (2009) A survey of the application of gamma processes in maintenance. Reliab Eng Syst Saf 94(1):2–21
Wang X, Xu D (2010) An inverse Gaussian process model for degradation data. Technometrics 52(2):188–197
Peng CY (2015) Inverse Gaussian processes with random effects and explanatory variables for degradation data. Technometrics 57(1):100–111
Ye ZS, Chen LP, Tang LC, Xie M (2014) Accelerated degradation test planning using the inverse Gaussian process. IEEE Trans Reliab 63(63):750–763
Wang X (2010) Wiener processes with random effects for degradation data. J Multivar Anal 101(2):340–351
Ye ZS, Wang Y, Tsui KL, Pecht M (2013) Degradation data analysis using wiener processes with measurement errors. IEEE Trans Reliab 62(4):772–780
Li J, Wang Z, Liu X, Zhang Y, Fu H, Liu C (2016) A Wiener process model for accelerated degradation analysis considering measurement errors. Microelectron Reliab 65:8–15
Tang LC, Yang GY, Xie M (2004) Planning of step-stress accelerated degradation test, Reliability and Maintainability Annual Symposium, 287–292
Padgett WJ, Tomlinson MA (2004) Inference from accelerated degradation and failure data based on Gaussian process models. Lifetime Data Anal 10(2):191–206
Lawless J, Crowder M (2004) Covariates and random effects in a Gamma process model with application to degradation and failure. Lifetime Data Anal 10(3):213–227
Kallen MJ, Noortwijk JMV (2005) Optimal maintenance decisions under imperfect inspection. Reliab Eng Syst Saf 90(2–3):177–185
Meeker WQ (2009) Trends in the statistical assessment of reliability. Adv Degrad Model:3–16
Hu CH, Lee MY, Tang J (2014) Optimum step-stress accelerated degradation test for Wiener degradation process under constraints. Eur J Oper Res 241(2):412–421
Lu CJ, Meeker WQ (1993) Using degradation measures to estimate a time-to-failure distribution. Technometrics 35(2):161–174
Wu SJ, Shao J (1999) Reliability analysis using the least squares method in nonlinear mixed-effect degradation model. Stat Sin 9(3):855–877
Robinson ME, Crowder MJ (2001) Bayesian methods for a growth-curve degradation model with repeated measures. Lifetime Data Anal 6(4):357–374
Wakefield JC, Smith AFM, Racine-Poon A, Gelfand AE (1994) Bayesian analysis of linear and nonlinear population models using the Gibbs sampler. J R Stat Soc 43(1):201–221
Peng W, Li YF, Yang YJ, Huang HZ, Zuo MJ (2014) Inverse Gaussian process models for degradation analysis: a Bayesian perspective. Reliab Eng Syst Saf 130(1):175–189
Chen Z, Zheng S (2005) Lifetime distribution based degradation analysis. IEEE Trans Reliab 54(1):3–10
Bae SJ, Kuo W, Kvam PH (2007) Degradation models and implied lifetime distributions. Reliab Eng Syst Saf 92(5):601–608
Bae SJ, Kvam PH (2012) A nonlinear random-coefficients model for degradation testing. Technometrics 46(4):460–469
Weaver BP et al (2011) Methods for planning repeated measures degradation studies. Technometrics 55(2):122–134
Yuan XX, Pandey MD (2009) A nonlinear mixed-effects model for degradation data obtained from in-service inspections. Reliab Eng Syst Saf 94(2):509–519
Lu J, Park J, Yang Q (1997) Statistical inference of a time-to-failure distribution derived from linear degradation data. Technometrics 39(4):391–400
Weaver BP, Meeker WQ (2014) Methods for planning repeated measures accelerated degradation tests. Appl Stoch Model Bus Ind 30(6):658–671
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Hu, L., Li, L., Hu, Q. (2017). Degradation Modeling, Analysis, and Applications on Lifetime Prediction. In: Chen, DG., Lio, Y., Ng, H., Tsai, TR. (eds) Statistical Modeling for Degradation Data. ICSA Book Series in Statistics. Springer, Singapore. https://doi.org/10.1007/978-981-10-5194-4_3
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DOI: https://doi.org/10.1007/978-981-10-5194-4_3
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