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Abstract Details
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Activity Number:
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573
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Quality and Productivity
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| Abstract - #301401 |
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Title:
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A Special Nonhomogeneous Poisson Process Estimation for Window-Observation Repairable System
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Author(s):
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Ming Li*+ and Brock Osborn and Yili Hong
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Companies:
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GE Global Research and GE Global Research and Virginia Tech
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Address:
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Applied Statistics Lab, Niskayuna, NY, 12309,
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Keywords:
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Reliability ;
Repairable System ;
Nonhomogeneous Poisson Process ;
Window-Observation Data ;
Forecast
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Abstract:
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A fleet of heavy-duty industry equipment is used in infrastructure constructions. The age of the equipment usually exceeds 20 years, and during its useful life repair and maintenance are needed. Unfortunately, not all repairs or maintenance events are recorded. The historical data set consists of series of observation windows in which the equipment is monitored and events are recorded. The time between observation windows varies from several days to several years. To model the reliability of the equipment and to forecast the cost of future repairs and maintenance events, a special three-piece nonhomogeneous Poisson process method is applied to the window-observation data. The bath-tub intensity results provide useful information for reliability estimations.
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