Multi-State Physics Model for the Reliability Assessment of a Component under Degradation Processes and Random Shocks

We extend a multi-state physics model (MSPM) framework for component reliability assessment by including semi-Markov and random shock processes. Dependences between the two processes are considered. A Monte Carlo simulation algorithm is developed to compute component reliability. An example is illustrated with respect to a literature case study.

[1]  Daniel T. Gillespie,et al.  Monte Carlo simulation of random walks with residence time dependent transition probability rates , 1978 .

[2]  Enrico Zio,et al.  A Multistate Physics Model of Component Degradation Based on Stochastic Petri Nets and Simulation , 2012, IEEE Transactions on Reliability.

[3]  Patrick G. Heasler,et al.  Multi-State Physics Models of Aging Passive Components in Probabilistic Risk Assessment , 2011 .

[4]  Kevin K. Anderson LIMIT THEOREMS FOR GENERAL SHOCK MODELS WITH INFINITE MEAN INTERSHOCK TIMES , 1987 .

[5]  Georgia-Ann Klutke,et al.  The availability of inspected systems subject to shocks and graceful degradation , 2002, IEEE Trans. Reliab..

[6]  Robert W Youngblood Treatment of Passive Component Reliability in Risk-Informed Safety Margin Characterization FY 2010 Report , 2010 .

[7]  Alaa Elwany,et al.  Residual Life Predictions in the Absence of Prior Degradation Knowledge , 2009, IEEE Transactions on Reliability.

[8]  Yaping Wang,et al.  Modeling the Dependent Competing Risks With Multiple Degradation Processes and Random Shock Using Time-Varying Copulas , 2012, IEEE Transactions on Reliability.

[9]  Maurizio Guida,et al.  An age- and state-dependent Markov model for degradation processes , 2011 .

[10]  Jian-Ming Bai,et al.  Generalized Shock Models Based on a Cluster Point Process , 2006, IEEE Transactions on Reliability.

[11]  Viliam Makis,et al.  Optimal maintenance policy for a multi-state deteriorating system with two types of failures under general repair , 2009, Comput. Ind. Eng..

[12]  Elmer E Lewis,et al.  Monte Carlo simulation of Markov unreliability models , 1984 .

[13]  John Dalsgaard Sørensen,et al.  Physics of failure as a basis for solder elements reliability assessment in wind turbines , 2012, Reliab. Eng. Syst. Saf..

[14]  M. Crowder,et al.  Covariates and Random Effects in a Gamma Process Model with Application to Degradation and Failure , 2004, Lifetime data analysis.

[15]  G. K. Agrafiotis,et al.  On Excess-time Correlated Cumulative Processes , 1995 .

[16]  Richard A. Levine,et al.  Multicomponent lifetime distributions in the presence of ageing , 2000 .

[17]  Elsayed A. Elsayed,et al.  A Geometric Brownian Motion Model for Field Degradation Data , 2004 .

[18]  Gregory Levitin,et al.  Multi-State System Reliability - Assessment, Optimization and Applications , 2003, Series on Quality, Reliability and Engineering Statistics.

[19]  Loon Ching Tang,et al.  A Distribution-Based Systems Reliability Model Under Extreme Shocks and Natural Degradation , 2011, IEEE Transactions on Reliability.

[20]  A. W. Marshall,et al.  Shock Models and Wear Processes , 1973 .

[21]  Hayriye Ayhan,et al.  A maintenance strategy for systems subjected to deterioration governed by random shocks , 1994 .

[22]  Hoang Pham,et al.  Reliability modeling of multi-state degraded systems with multi-competing failures and random shocks , 2005, IEEE Trans. Reliab..

[23]  Toshio Nakagawa,et al.  Replacement policies for a cumulative damage model with minimal repair at failure , 1989 .

[24]  Allan Gut,et al.  Extreme Shock Models , 1999 .

[25]  Aparna V. Huzurbazar,et al.  FLOWGRAPH MODELS FOR COMPLEX MULTISTATE SYSTEM RELIABILITY , 2005 .

[26]  Hong-Zhong Huang,et al.  An Approach to Reliability Assessment Under Degradation and Shock Process , 2011, IEEE Transactions on Reliability.