Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation

This paper tries to integrate sequential imperfect maintenance policy into condition-based predictive maintenance (CBPM). A reliability-centered predictive maintenance policy is proposed for a continuously monitored system subject to degradation due to the imperfect maintenance. It is assumed that the system hazard rate is a known function of the system condition and then can be derived directly through CBPM. A hybrid hazard rate recursion rule based on the concept of age reduction factor and hazard rate increase factor is built up to predict the evolution of the system reliability in different maintenance cycles. Whenever the system reliability reaches the threshold R, an imperfect preventive maintenance (PM) is performed on the system. The optimal reliability threshold R is determined by minimizing the cumulative maintenance cost per unit time in the residual life of the system which is based on simulation. Finally, a discussion is presented to show how the optimal results depend on the different cost parameters.

[1]  Kishor S. Trivedi,et al.  Closed-form analytical results for condition-based maintenance , 2002, Reliab. Eng. Syst. Saf..

[2]  Francisco Germán Badía,et al.  Optimal inspection and preventive maintenance of units with revealed and unrevealed failures , 2002, Reliab. Eng. Syst. Saf..

[3]  Andrew K. S. Jardine,et al.  Optimizing condition‐based maintenance decisions for equipment subject to vibration monitoring , 1999 .

[4]  Antoine Grall,et al.  A condition-based maintenance policy for stochastically deteriorating systems , 2002, Reliab. Eng. Syst. Saf..

[5]  T. Nakagawa,et al.  Extended optimal replacement model with random minimal repair costs , 1995 .

[6]  Viliam Makis,et al.  A decision optimization model for condition‐based maintenance , 1998 .

[7]  T. Nakagawa Optimal policy of continuous and discrete replacement with minimal repair at failure , 1984 .

[8]  J.-K. Chan,et al.  Modeling repairable systems with failure rates that depend on age and maintenance , 1993 .

[9]  Jay Lee Teleservice engineering in manufacturing: challenges and opportunities , 1998 .

[10]  R. V. Canfield,et al.  Cost Optimization of Periodic Preventive Maintenance , 1986, IEEE Transactions on Reliability.

[11]  R. Barlow,et al.  Optimum Preventive Maintenance Policies , 1960 .

[12]  Antoine Grall,et al.  Sequential condition-based maintenance scheduling for a deteriorating system , 2003, Eur. J. Oper. Res..

[13]  Gregory Levitin,et al.  Optimization of imperfect preventive maintenance for multi-state systems , 2000, Reliab. Eng. Syst. Saf..

[14]  V. Jayabalan,et al.  Cost optimization of maintenance scheduling for a system with assured reliability , 1992 .

[15]  Sebastian Martorell,et al.  Age-dependent reliability model considering effects of maintenance and working conditions , 1999 .

[16]  Mazhar Ali Khan Malik,et al.  Reliable Preventive Maintenance Scheduling , 1979 .

[17]  Diederik J.D. Wijnmalen,et al.  Optimum condition-based maintenance policies for deteriorating systems with partial information , 1996 .

[18]  Young Ho Chun,et al.  An Algorithm for Preventive Maintenance Policy , 1986, IEEE Transactions on Reliability.

[19]  T. Nakagawa Sequential imperfect preventive maintenance policies , 1988 .

[20]  Ruey Huei Yeh State-age-dependent maintenance policies for deteriorating systems with Erlang sojourn time distributions , 1997 .

[21]  Y. X. Zhao,et al.  On preventive maintenance policy of a critical reliability level for system subject to degradation , 2003, Reliab. Eng. Syst. Saf..

[22]  R. Keith Mobley,et al.  An introduction to predictive maintenance , 1989 .

[23]  W. Wang A model to determine the optimal critical level and the monitoring intervals in condition-based maintenance , 2000 .