[1] Sharifi, S. M. M., Gholami Mazinan, H., Karbasian, M., & & Sharifi, S. M. H. (2011). Reliability engineering. Omid Enghelab Publications. https://B2n.ir/yy1425
[2] Peng, W., Li, Y. F., Yang, Y. J., Huang, H. Z., & Zuo, M. J. (2014). Inverse Gaussian process models for degradation analysis: A Bayesian perspective. Reliability engineering & system safety, 130, 175–189. https://doi.org/10.1016/j.ress.2014.06.005
[3] Pandey, M. D., & Lu, D. (2013). Estimation of parameters of degradation growth rate distribution from noisy measurement data. Structural safety, 43, 60–69. https://doi.org/10.1016/j.strusafe.2013.02.002
[4] Ling, M. H., Tsui, K. L., & Balakrishnan, N. (2014). Accelerated degradation analysis for the quality of a system based on the gamma process. IEEE transactions on reliability, 64(1), 463–472. https://doi.org/10.1109/TR.2014.2337071
[5] Chen, H., & Yuan, H. (2010). Reliability assessment based on proportional degradation hazards model. 2010 IEEE 17th international conference on industrial engineering and engineering management (pp. 958–962). IEEE. https://doi.org/10.1109/ICIEEM.2010.5646465
[6] Ye, Z. S., Chen, L. P., Tang, L. C., & Xie, M. (2014). Accelerated degradation test planning using the inverse Gaussian process. IEEE transactions on reliability, 63(3), 750–763. https://doi.org/10.1109/TR.2014.2315773
[7] Shen, Y., Zhang, C., Tan, Y., & Chen, X. (2011). Accelerated degradation testing for systems with multiple performance parameters. 2011 international conference on quality, reliability, risk, maintenance, and safety engineering (pp. 292–296). IEEE. https://doi.org/10.1109/ICQR2MSE.2011.5976615
[8] Wang, L., Pan, R., Li, X., & Jiang, T. (2013). A Bayesian reliability evaluation method with integrated accelerated degradation testing and field information. Reliability engineering & system safety, 112, 38–47. https://doi.org/10.1016/j.ress.2012.09.015
[9] Wang, L., Li, X., Jiang, T., & Zhuang, X. (2011). The adt evaluation method based on mcmc. 2011 IEEE international conference on industrial engineering and engineering management (pp. 1251–1255). IEEE. https://doi.org/10.1109/IEEM.2011.6118116
[10] Collins, D. H., Freels, J. K., Huzurbazar, A. V, Warr, R. L., & Weaver, B. P. (2013). Accelerated test methods for reliability prediction. Journal of quality technology, 45(3), 244–259. https://doi.org/10.1080/00224065.2013.11917936
[11] Elsayed, E. A. (2012). Reliability engineering. John Wiley & Sons. https://B2n.ir/ku9415
[12] Limon, S., Yadav, O. P., & Liao, H. (2017). A literature review on planning and analysis of accelerated testing for reliability assessment. Quality and reliability engineering international, 33(8), 2361–2383. https://doi.org/10.1002/qre.2195
[13] Wang, H., Zhao, Y., Ma, X., & Wang, H. (2017). Optimal design of constant-stress accelerated degradation tests using the M-optimality criterion. Reliability engineering & system safety, 164, 45–54. https://doi.org/10.1016/j.ress.2017.03.010
[14] Si, X. S., Wang, W., Hu, C. H., & Zhou, D. H. (2011). Remaining useful life estimation-a review on the statistical data driven approaches. European journal of operational research, 213(1), 1–14. https://doi.org/10.1016/j.ejor.2010.11.018
[15] Zhang, Y. (2020). Graphic illustration for mechanical reliability design (3)-testing and data collection. Life cycle reliability and safety engineering, 9, 303–318. https://doi.org/10.1007/s41872-020-00126-z
[16] Gray, K. A., & Paschkewitz, J. J. (2016). Next generation HALT and HASS: Robust design of electronics and systems. John Wiley & Sons. https://doi.org/10.1002/9781118700228
[17] Tsai, C. C., Tseng, S. T., & Balakrishnan, N. (2010). Optimal burn-in policy for highly reliable products using gamma degradation process. IEEE transactions on reliability, 60(1), 234–245. https://doi.org/10.1109/TR.2010.2087430
[18] Ebeling, C. E. (1996). An introduction to reliability and maintainability engineering. Waveland Press. https://www.amazon.com/Introduction-Reliability-Maintainability-Engineering/dp/1577666259
[19] Agrawal, V. D., Kime, C. R., & Saluja, K. K. (2002). A tutorial on built-in self-test. I. Principles. IEEE design & test of computers, 10(1), 73–82. https://doi.org/10.1109/54.199807
[20] Shi, Y., & Meeker, W. Q. (2011). Bayesian methods for accelerated destructive degradation test planning. IEEE transactions on reliability, 61(1), 245–253. https://doi.org/10.1109/TR.2011.2170115
[21] Lu, C. J., & Meeker, W. O. (1993). Using degradation measures to estimate a time-to-failure distribution. Technometrics, 35(2), 161–174. https://doi.org/10.1080/00401706.1993.10485038
[22] Zhang, X. (2013). Experiment design and reliability analysis of accelerated degradation test [Thesis]. University of Cincinnati. https://etd.ohiolink.edu/acprod/odb_etd/etd/r/1501/10?clear=10&p10_accession_num=ucin1378197282
[23] Sawant, M., & Christou, A. (2012). Failure modes and effects criticality analysis and accelerated life testing of LEDs for medical applications. Solid-state electronics, 78, 39–45. https://doi.org/10.1016/j.sse.2012.05.042
[24] McPherson, J. W. (2013). Time-to-failure modeling. In Reliability physics and engineering: Time-to-failure modeling (pp. 37–49). Springer. https://doi.org/10.1007/978-3-319-00122-7_4
[25] Meeker, W., Escobar, L., & Hong, Y. (2009). Using accelerated life tests results to predict product field reliability. Technometrics, 51 (2), 146-161. https://doi.org/10.1198/TECH.2009.0016
[26] Yang, G. (2005). Contributions to planning and analysis of accelerated testing [Thesis]. https://dissertation.com/abstract/1380214
[27] DeBonis, J. R. (2010). Gas turbine engines: Nozzles. In encyclopedia of aerospace engineering. Wiley Online Library. http://dx.doi.org/10.1002/9780470686652.eae096
[28] Deere, K. (2003). Summary of fluidic thrust vectoring research at nasa langley research center. 21st AIAA applied aerodynamics conference (p. 3800). American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2003-3800
[29] Gamble, E., Terrell, D., & DeFrancesco, R. (2004). Nozzle selection and design criteria. 40th AIAA/ASME/SAE/ASEE joint propulsion conference and exhibit (p. 3923). American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2004-3923
[30] Nelson, W. B. (2009). Accelerated testing: Statistical models, test plans, and data analysis. John Wiley & Sons. https://B2n.ir/tb2103
[31] Carey, M. B., & Koenig, R. H. (1991). Reliability assessment based on accelerated degradation: A case study. IEEE transactions on reliability, 40(5), 499–506. https://doi.org/10.1109/24.106763
[32] Boulanger, M., & Escobar, L. A. (1994). Experimental design for a class of accelerated degradation tests. Technometrics, 36(3), 260–272. https://doi.org/10.1080/00401706.1994.10485803
[33] Tobias, P. A., & Trindade, D. (2011). Applied reliability. CRC Press. https://B2n.ir/kp8883
[34] Tseng, S. T., & Yu, H. F. (1997). A termination rule for degradation experiments. IEEE transactions on reliability, 46(1), 130–133. https://doi.org/10.1109/24.589938
[35] Escobar, L. A., Meeker, W. Q., Kugler, D. L., & Kramer, L. L. (2003). Accelerated destructive degradation tests: Data, models, and analysis. In Mathematical and statistical methods in reliability (pp. 319–337). World Scientific. https://doi.org/10.1142/9789812795250_0021
[36] Sanchez, L. M., & Pan, R. (2009). Product robust design via accelerated degradation tests. 2009 annual reliability and maintainability symposium (pp. 89–94). IEEE. https://doi.org/10.1109/RAMS.2009.4914656
[37] Ding, Y., Yang, Q., King, C. B., & Hong, Y. (2019). A general accelerated destructive degradation testing model for reliability analysis. IEEE transactions on reliability, 68(4), 1272–1282. https://doi.org/10.1109/TR.2018.2883983
[38] Xu, Z., Hong, Y., & Jin, R. (2016). Nonlinear general path models for degradation data with dynamic covariates. Applied stochastic models in business and industry, 32(2), 153–167. https://doi.org/10.1002/asmb.2129
[39] Xiao, X., & Ye, Z. (2016). Optimal design for destructive degradation tests with random initial degradation values using the Wiener process. IEEE transactions on reliability, 65(3), 1327–1342. https://doi.org/10.1109/TR.2016.2575442
[40] Chen, D. G., Lio, Y., Ng, H. K. T., & Tsai, T. R. (2017). Statistical modeling for degradation data. Springer. https://doi.org/10.1007/978-981-10-5194-4
[41] Ruz, D. M. C., Pedersen, H. C., Liniger, J., Bhola, M., & Wrat, G. (2024). A Review of state of the art for accelerated testing in fluid power pitch systems. Wind, 4(3), 208–226. https://doi.org/10.20944/preprints202405.2070.v1
[42] Guo, J., Han, Z., Wu, S., Long, J., Chen, C., & Liu, Z. (2025). Multi-objective optimization design for accelerated degradation test based on game theory. Scientific reports, 15(1), 1–20. https://doi.org/10.1038/s41598-025-98959-0