Please use this identifier to cite or link to this item:
https://doi.org/10.1002/qre.977
DC Field | Value | |
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dc.title | A Study of time-between-events control chart for the monitoring of regularly maintained systems | |
dc.contributor.author | Khoo, M.B.C. | |
dc.contributor.author | Xie, M. | |
dc.date.accessioned | 2014-06-17T06:58:38Z | |
dc.date.available | 2014-06-17T06:58:38Z | |
dc.date.issued | 2009-11 | |
dc.identifier.citation | Khoo, M.B.C., Xie, M. (2009-11). A Study of time-between-events control chart for the monitoring of regularly maintained systems. Quality and Reliability Engineering International 25 (7) : 805-819. ScholarBank@NUS Repository. https://doi.org/10.1002/qre.977 | |
dc.identifier.issn | 07488017 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/62968 | |
dc.description.abstract | Owing to usage, environment and aging, the condition of a system deteriorates over time. Regular maintenance is often conducted to restore its condition and to prevent failures from occurring. In this kind of a situation, the process is considered to be stable, thus statistical process control charts can be used to monitor the process. The monitoring can help in making a decision on whether further maintenance is worthwhile or whether the system has deteriorated to a state where regular maintenance is no longer effective. When modeling a deteriorating system, lifetime distributions with increasing failure rate are more appropriate. However, for a regularly maintained system, the failure time distribution can be approximated by the exponential distribution with an average failure rate that depends on the maintenance interval. In this paper, we adopt a modification for a time-between-events control chart, i.e. the exponential chart for monitoring the failure process of a maintained Weibull distributed system. We study the effect of changes on the scale parameter of the Weibull distribution while the shape parameter remains at the same level on the sensitivity of the exponential chart. This paper illustrates an approach of integrating maintenance decision with statistical process monitoring methods. © 2008 John Wiley &Sons, Ltd. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1002/qre.977 | |
dc.source | Scopus | |
dc.subject | Exponential distribution | |
dc.subject | Failure rate | |
dc.subject | Maintenance interval | |
dc.subject | Regular maintenance | |
dc.subject | Reliability monitoring | |
dc.subject | Time-between-events control chart | |
dc.subject | Weibull distribution | |
dc.type | Article | |
dc.contributor.department | INDUSTRIAL & SYSTEMS ENGINEERING | |
dc.description.doi | 10.1002/qre.977 | |
dc.description.sourcetitle | Quality and Reliability Engineering International | |
dc.description.volume | 25 | |
dc.description.issue | 7 | |
dc.description.page | 805-819 | |
dc.description.coden | QREIE | |
dc.identifier.isiut | 000271877600003 | |
Appears in Collections: | Staff Publications |
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