Component Reliability Criticality or Importance Measures for Systems With Degrading Components

This paper proposes two new importance measures: one new importance measure for systems with -independent degrading components, and another one for systems with -correlated degrading components. Importance measures in previous research are inadequate for systems with degrading components because they are only applicable to steady-state cases and problems with discrete states without considering the continuously changing status of the degrading components. Our new importance measures are proposed as functions of time that can provide timely feedback on the critical components prior to failure based on the measured or observed degradation. Furthermore, the correlation between components is considered for developing these importance measures through a multivariate distribution. To evaluate the criticality of components, we analysed reliability models for multi-component systems with degrading components, which can also be utilized for studying maintenance models. Numerical examples show that the proposed importance measures can be used as an effective tool to assess component criticality for systems with degrading components.

[1]  Luca Podofillini,et al.  Generalised importance measures for multi-state elements based on performance level restrictions , 2003, Reliab. Eng. Syst. Saf..

[2]  Shaomin Wu,et al.  Joint importance of multistate systems , 2005, Comput. Ind. Eng..

[3]  David W. Coit,et al.  Composite importance measures for multi-state systems with multi-state components , 2005, IEEE Transactions on Reliability.

[4]  Lirong Cui,et al.  Analysis for joint importance of components in a coherent system , 2007, Eur. J. Oper. Res..

[5]  Rong Li,et al.  Residual-life distributions from component degradation signals: A Bayesian approach , 2005 .

[6]  Christophe Bérenguer,et al.  Reliability importance analysis of Markovian systems at steady state using perturbation analysis , 2008, Reliab. Eng. Syst. Saf..

[7]  Jye-Chyi Lu,et al.  A Random Coefficient Degradation Model With Ramdom Sample Size , 1999, Lifetime data analysis.

[8]  Jussi K. Vaurio.  Importance measures for multi-phase missions , 2011, Reliab. Eng. Syst. Saf..

[9]  Kailash C. Kapur.  Multi-state reliability : models and applications , 2006 .

[10]  Peng Wang,et al.  Reliability prediction based on degradation modeling for systems with multiple degradation measures , 2004, Annual Symposium Reliability and Maintainability, 2004 - RAMS.

[11]  S. L. Albin,et al.  Preventive replacement in systems with dependent components , 1992 .

[12]  David W. Coit,et al.  Simultaneous Quality and Reliability Optimization for Microengines Subject to Degradation , 2009, IEEE Transactions on Reliability.

[13]  Kai Yang,et al.  Continuous state reliability analysis , 1996, Proceedings of 1996 Annual Reliability and Maintainability Symposium.

[14]  Emanuele Borgonovo,et al.  A new importance measure for risk-informed decision making , 2001, Reliab. Eng. Syst. Saf..

[15]  C. Joseph Lu,et al.  Using Degradation Measures to Estimate a Time-to-Failure Distribution , 1993 .

[16]  J. Sethuraman,et al.  Multistate Coherent Systems. , 1978 .

[17]  Steven M. Cox,et al.  Stochastic models for degradation-based reliability , 2005 .

[18]  Luis A. Escobar,et al.  Accelerated degradation tests: modeling and analysis , 1998 .

[19]  D. Vasseur,et al.  International survey on PSA figures of merit , 1999 .

[20]  Shenggui Zhang,et al.  Integrated importance measures of multi-state systems under uncertainty , 2010, Comput. Ind. Eng..

[21]  Charles E Ebeling,et al.  An Introduction to Reliability and Maintainability Engineering , 1996 .

[22]  Shaomin Wu,et al.  Performance utility-analysis of multi-state systems , 2003, IEEE Trans. Reliab..

[23]  Richard E. Barlow,et al.  Coherent Systems with Multi-State Components , 1978, Math. Oper. Res..

[24]  M E Robinson,et al.  Bayesian Methods for a Growth-Curve Degradation Model with Repeated Measures , 2000, Lifetime data analysis.

[25]  Suk Joo Bae,et al.  A change-point analysis for modeling incomplete burn-in for light displays , 2006 .

[26]  S. Iyer.  The Barlow-Proschan importance and its generalizations with dependent components , 1992 .

[27]  Luca Podofillini,et al.  Monte Carlo simulation analysis of the effects of different system performance levels on the importance of multi-state components , 2003, Reliab. Eng. Syst. Saf..

[28]  C. Lie,et al.  Joint reliability-importance of two edges in an undirected network , 1993 .

[29]  John Andrews.  Birnbaum and criticality measures of component contribution to the failure of phased missions , 2008, Reliab. Eng. Syst. Saf..

[30]  E. Wu,et al.  On the progressive breakdown statistical distribution and its voltage acceleration , 2007, 2007 IEEE International Electron Devices Meeting.

[31]  Xian-Xun Yuan,et al.  A nonlinear mixed-effects model for degradation data obtained from in-service inspections , 2009, Reliab. Eng. Syst. Saf..

[32]  Way Kuo,et al.  Patterns of the Birnbaum importance in linear consecutive-k-out-of-n systems , 2012 .

[33]  W. Griffith.  MULTISTATE RELIABILITY MODELS , 1980 .

[34]  Suk Joo Bae,et al.  Degradation models and implied lifetime distributions , 2007, Reliab. Eng. Syst. Saf..

[35]  Nagi Gebraeel,et al.  Prognostics-Based Identification of the Top-$k$ Units in a Fleet , 2010, IEEE Transactions on Automation Science and Engineering.

[36]  F. C. Meng.  Comparing the importance of system components by some structural characteristics , 1996, IEEE Trans. Reliab..