Title of article :
A framework to practical predictive maintenance modeling for multi-state systems
Author/Authors :
Cher Ming Tan، نويسنده , , Nagarajan Raghavan، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2008
Pages :
13
From page :
1138
To page :
1150
Abstract :
A simple practical framework for predictive maintenance (PdM)-based scheduling of multi-state systems (MSS) is developed. The maintenance schedules are derived from a system-perspective using the failure times of the overall system as estimated from its performance degradation trends. The system analyzed in this work is a flow transmission water pipe system. The various factors influencing PdM-based scheduling are identified and their impact on the system reliability and performance are quantitatively studied. The estimated times to replacement of the MSS may also be derived from the developed model. The results of the model simulation demonstrate the significant impact of maintenance quality and the criteria for the call for maintenance (user demand) on the system reliability and mean performance characteristics. A slight improvement in maintenance quality is found to postpone the system replacement time by manifold. The consistency in the quality of maintenance work with minimal variance is also identified as a very important factor that enhances the systemʹs future operational and downtime event predictability. The studies also reveal that in order to reduce the frequency of maintenance actions, it is necessary to lower the minimum user demand from the system if possible, ensuring at the same time that the system still performs its intended function effectively. The model proposed can be utilized to implement a PdM program in the industry with a few modifications to suit the individual industrial systems’ needs.
Keywords :
Time to failure (TTF) , Restoration factor (RF) , User demand , Multi-state system (MSS) , Time to replacement (TTR) , Universal generating function (UGF) , Maintenance quality , Markov chain analysis
Journal title :
Reliability Engineering and System Safety
Serial Year :
2008
Journal title :
Reliability Engineering and System Safety
Record number :
1187822
Link To Document :
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