Degradation and Reliability Modeling of Two-Component System with Degradation Rate Interaction

doi:10.23940/ijpe.18.11.p17.27112722

Int J Performability Eng ›› 2018, Vol. 14 ›› Issue (11): 2711-2722.doi: 10.23940/ijpe.18.11.p17.27112722

Previous Articles Next Articles

Degradation and Reliability Modeling of Two-Component System with Degradation Rate Interaction

Zhiyuan Yang^{a, *}, Jianmin Zhao^a, Chiming Guo^a, and Liying Li^b

^a Department of Management Engineering, Shijiazhuang Branch, Army Engineering University, Shijiazhuang, 050000, China;
^b College of Information, Hebei University of Science and Technology, Shijiazhuang, 050000, China

Submitted on ;
Contact: * E-mail address: yzy_sjz90@126.com
About author:Zhiyuan Yang is a Ph.D. student at Army Engineering University, Shijiazhuang, China. His current areas of research include degradation modeling and maintenance decision.Jianmin Zhao is a professor at Army Engineering University, Shijiazhuang, China. He received his Ph.D. degree from the University of Birmingham, Birmingham, UK. His areas of interest include PHM and maintenance decision.Chiming Guo is a lecturer at Army Engineering University, Shijiazhuang, China. He received his Ph.D. degree from the National University of Defense Technology, Changsha, China. His areas of interest include reliability engineering and maintenance engineering.Liying Li is a lecturer at Hebei University of Science and Technology, Shijiazhuang, China. She received her Master's degree from Shijiazhuang Tiedao University, Shijiazhuang, China. Her areas of interest include probability analysis and stochastic simulation.

Abstract

Abstract: The stochastic dependency, which has a significant impact on degradation and reliability modeling, exists in many complex systems. The stochastic dependency is analyzed from a degradation processes interaction perspective in this paper. For a two-component system, a degradation rate interaction model is developed to describe the dependency between the degradations of two components with a nonlinear Wiener process. This is achieved by considering that the degradation rate of a component is affected by the degradation state of the other component in the proposed system. Then, the parameter estimation approach is given, and the reliability models of the components and system are derived. Finally, a numerical example about fatigue crack development is presented to validate the developed models. Moreover, a comparison study with some present models is taken to show the performance of the developed degradation and reliability models.

Key words: two-component system, stochastic dependency, degradation modeling, reliability, Wiener process

Zhiyuan Yang, Jianmin Zhao, Chiming Guo, and Liying Li. Degradation and Reliability Modeling of Two-Component System with Degradation Rate Interaction [J]. Int J Performability Eng, 2018, 14(11): 2711-2722.

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

References

[1] R. Dekker, R. E. Wildeman,F. A. V. D. D. Schouten, “A Review of Multi-Component Maintenance Models with Economic Dependence,” Mathematical Methods of Operation Research, Vol. 45, No. 3, pp. 411-435, October 1997
[2] Y. Sun, L. Ma,J. Mathew, “Failure Analysis of Engineering Systems with Preventive Maintenance and Failure Interactions,” Computers and Industrial Engineering, Vol. 57, No. 2, pp. 539-549, September 2009
[3] Y. Sun, L. Ma, J. Mathew, W. Wang,S. Zhang, “Mechanical Systems Hazard Estimation Using Condition Monitoring,” Mechanical System and Signal Processing, Vol. 20, No. 5, pp. 1189-1201, July 2006
[4] D. Bhattacharya and F. J. Samaniego, “Estimating Component Characteristics from System Failure-Time Data,” Naval Research Logistics, Vol. 57, No. 4, pp. 380-389, June 2010
[5] R. I.Zequeira and C. Berenguer, “On the Inspection Policy of a Two-Component Parallel System with Failure Interaction,” Reliability Engineering and System Safety, Vol. 88, No. 1, pp. 99-107, April 2005
[6] A. Barros, C. Berenguer,A. Grall, “A Maintenance Policy for Two-Unit Parallel Systems based on Imperfect Monitoring Information,” Reliability Engineering and System Safety, Vol. 91, No. 2, pp. 131-136, February 2006
[7] Y. Sun, L. Ma, J. Mathew,S. Zhang, “An Analytical Model for Interactive Failures,” Reliability Engineering and System Safety, Vol. 91, No. 5, pp. 495-504, May 2006
[8] H. R.Golmakani and H. Moakedi, “Periodic Inspection Optimization Model for a Two-Component Repairable System with Failure Interaction,” Computers and Industrial Engineering, Vol. 63, No. 3, pp. 540-545, November 2012
[9] J. K. Sari, M. J. Newby, A. C. Brombacher,L. C. Tang, “Bivariate Constant Stress Degradation Model: LED Lighting System Reliability Estimation with Two-Stage Modeling,” Quality and Reliability Engineering International, Vol. 25, No. 8, pp. 1067-1084, December 2009
[10] Z. Pan and N. Balakrishnan, “Reliability Modeling of Degradation of Products with Multiple Performance Characteristics based on Gamma Processes,” Reliability Engineering and System Safety, Vol. 96, No. 8, pp. 949-957, August 2011
[11] Y. Wang and H. Pham, “Modeling the Dependent Competing Risks with Multiple Degradation Processes and Random Shock Using Time-Varying Copulas,” IEEE Transactions on Reliability, Vol. 61, No. 1, pp. 13-22, March 2012
[12] Z. Pan, N. Balakrishnan, S. Quan,J. Zhou, “Bivariate Degradation Analysis of Products based on Wiener Processes and Copulas,” Journal of Statistical Computation and Simulation, Vol. 83, No. 7, pp. 1316-1329, July 2013
[13] H. P. Hong, W. Zhou, S. Zhang,W. Ye, “Optimal Condition-based Maintenance Decisions for Systems with Dependent Stochastic Degradation of Components,” Reliability Engineering and System Safety, Vol. 121, No. 1, pp. 276-288, January 2014
[14] H. Li, E. Deloux,L. Dieulle, “A Condition-based Maintenance Policy for Multicomponent Systems with Lévy Copulas Dependence,” Reliability Engineering and System Safety, Vol. 149, pp. 44-55, May 2016
[15] L. Bian and N. Gebraeel, “Stochastic Modeling and Real-Time Prognostics for Multi-Component Systems with Degradation Rate Interactions,” IIE Transactions, Vol. 46, No. 5, pp. 470-482, February 2014
[16] N. Rasmekomen and A. K. Parlikad, “Condition-based Maintenance of Multi-Component Systems with Degradation State-Rate Interactions,” Reliability Engineering and System Safety, Vol. 148, pp. 1-10, April 2016
[17] A. F. Shahraki, O. P. Yadav,H. Liao, “A Review on Degradation Modelling and Its Engineering Applications,” International Journal of Performability Engineering, Vol. 13, No. 3, pp. 299-314, May 2017
[18] I. Ntzoufras, “Bayesian Modeling Using WinBUGS,” John Wiley and Sons, Hoboken, NJ, 2009
[19] X. Si, W. Wang, C. Hu, D. Zhou,M. G. Pecht, “Remaining Useful Life Estimation based on a Nonlinear Diffusion Degradation Process,” IEEE Transactions on Reliability, Vol. 61, No. 1, pp. 50-67, January 2012
[20] C. T.Barker and M. J. Newby, “Optimal Non-Periodic Inspection for a Multivariate Degradation Model,” Reliability Engineering and System Safety, Vol. 94, No. 1, pp. 33-43, January 2009
[21] X. Wang, N. Balakrishnan,B. Guo, “Residual Life Estimation based on a Generalized Wiener Degradation Process,” Reliability Engineering and System Safety, Vol. 124, pp. 13-23, April 2014
[22] W. Q.Meeker and L. A. Escobar, “Statistical Method for Reliability Data,” John Wiley and Sons, New York, 1998
[23] X. Wang, B. Guo,Z. Cheng, “Residual Life Estimation based on Bivariate Wiener Degradation Process with Time-Scale Transformation,” Journal of Statistical Computation and Simulation, Vol. 84, No. 3, pp. 545-563, March 2014

Degradation and Reliability Modeling of Two-Component System with Degradation Rate Interaction

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended 0

[1]	Amit Kumar Singh and P. C. Tewari. An Overview of Reliability, Availability, Maintainability, and Safety Strategies for Complex Systems in Various Process Industries [J]. Int J Performability Eng, 2023, 19(12): 788-796.
[2]	Yonghua Li, Shujian Liu, Xiaoning Bai, and Yufeng Wang. An Interval-Probability Hybrid Structural Reliability Calculation Method Based on CSSA-BR-BP [J]. Int J Performability Eng, 2023, 19(10): 687-699.
[3]	Jinxin Wang, Zhiping Zhai, Yuezheng Lan, Xiaoyi Zhai, and Lixiang Zhao. Reliability Analysis and Optimization of Forage Crushers Based on Bayesian Network [J]. Int J Performability Eng, 2023, 19(10): 700-709.
[4]	Yu-Lun Chao, Yi-Kuei Lin, and Cheng-Ta Yeh. AMC-Based Algorithm for Network Reliability Evaluation of a Manufacturing System with Scrapping and Rework [J]. Int J Performability Eng, 2022, 18(4): 231-240.
[5]	Madhumitha J, and G. Vijayalakshmi. Multi-State Performance Analysis of Linear Consecutive 2-out-of-4: F System using Markov Reward Model [J]. Int J Performability Eng, 2022, 18(12): 903-910.
[6]	Risu Na, Weiguo Zhang, Kaifa Jia, and Quan Zhang. Key Factors of Seal Ring Reliability based on QFD [J]. Int J Performability Eng, 2022, 18(11): 759-769.
[7]	Tae-Jin Yang. Comparative Analysis on the Reliability Performance of NHPP Software Reliability Model Applying Exponential-Type Lifetime Distribution [J]. Int J Performability Eng, 2022, 18(10): 679-689.
[8]	Surbhi Gupta, H.D. Aroraa, Anjali Naithania, Anil Chandrab. Reliability Assessment of the Planning and Perception Software Competencies of Self-Driving Cars [J]. Int J Performability Eng, 2021, 17(9): 779-786.
[9]	Tyler D. Ridder and Ram M. Narayanan. Radar Detection Performability under Graceful Degradation [J]. Int J Performability Eng, 2021, 17(8): 666-675.
[10]	Yi-Chun Cheng, Yi-Kuei Lin, and Ping-Chen Chang. Reliability Evaluation for a Multistate Network with Time Attribute and Periodical Maintenance [J]. Int J Performability Eng, 2021, 17(8): 676-685.
[11]	Yi-Fan Chen, Yi-Kuei Lin, and Cheng-Fu Huang. Using Deep Neural Networks to Evaluate the System Reliability of Manufacturing Networks [J]. Int J Performability Eng, 2021, 17(7): 600-608.
[12]	Youssef Bassir, Achraf Wahid, Abdelkarim Kartouni, and Mohamed ELghorba. Estimation of Wire Rope Reliability by Two Analytical Approach [J]. Int J Performability Eng, 2021, 17(7): 619-626.
[13]	Rahul Ray, Shiva Shankar Choudhary, and Lal Bahadur Roy. Reliability Analysis of Layered Soil Slope Stability using ANFIS and MARS Soft Computing Techniques [J]. Int J Performability Eng, 2021, 17(7): 647-656.
[14]	Yi-Hao Chiu, Yi-Kuei Lin, and Thi-Phuong Nguyen. Network Reliability of a Stochastic Online-Food Delivery System with Space and Time Constraints [J]. Int J Performability Eng, 2021, 17(5): 433-443.
[15]	Saurav Shekhar Kar and Lal Bahadur Roy. Reliability Analysis of a Finite Slope Considering the Effects of Soil Uncertainty [J]. Int J Performability Eng, 2021, 17(5): 473-483.