Failure and maintenance data extraction from power plant maintenance management databases

Babakalli Alkali; Tim Bedford; John Quigley; Jim Gaw

doi:10.1016/j.jspi.2008.05.037

Failure and maintenance data extraction from power plant maintenance management databases

Babakalli Alkali, Tim Bedford, John Quigley, Jim Gaw

Mechanical Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

Reliability analysis is plagued by a lack of accurate data, leading to suboptimal parameter estimates and inaccurate decisions about replacement intervals and preventive maintenance activities. This paper discusses some of the problems associated with failure and maintenance data extraction from coal-fired power plant maintenance databases. Data from four generating units were observed for over 5 years and a reasonable number of equipment classes reviewed. The coal mills are identified as significant equipment that affects the availability of the generating units. This paper describes the interplay of events which includes failure modes, failure, repair and operating time.

Original language	English
Pages (from-to)	1766-1776
Number of pages	11
Journal	Journal of Statistical Planning and Inference
Volume	139
Issue number	5
DOIs	https://doi.org/10.1016/j.jspi.2008.05.037
Publication status	Published - 1 May 2009

Keywords

reliability
competing risk
engineering
database

Documents and Links

10.1016/j.jspi.2008.05.037

http://researchonline.gcu.ac.uk/sec/91

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title = "Failure and maintenance data extraction from power plant maintenance management databases",

abstract = "Reliability analysis is plagued by a lack of accurate data, leading to suboptimal parameter estimates and inaccurate decisions about replacement intervals and preventive maintenance activities. This paper discusses some of the problems associated with failure and maintenance data extraction from coal-fired power plant maintenance databases. Data from four generating units were observed for over 5 years and a reasonable number of equipment classes reviewed. The coal mills are identified as significant equipment that affects the availability of the generating units. This paper describes the interplay of events which includes failure modes, failure, repair and operating time.",

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AU - Alkali, Babakalli

AU - Bedford, Tim

AU - Quigley, John

AU - Gaw, Jim

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N2 - Reliability analysis is plagued by a lack of accurate data, leading to suboptimal parameter estimates and inaccurate decisions about replacement intervals and preventive maintenance activities. This paper discusses some of the problems associated with failure and maintenance data extraction from coal-fired power plant maintenance databases. Data from four generating units were observed for over 5 years and a reasonable number of equipment classes reviewed. The coal mills are identified as significant equipment that affects the availability of the generating units. This paper describes the interplay of events which includes failure modes, failure, repair and operating time.

AB - Reliability analysis is plagued by a lack of accurate data, leading to suboptimal parameter estimates and inaccurate decisions about replacement intervals and preventive maintenance activities. This paper discusses some of the problems associated with failure and maintenance data extraction from coal-fired power plant maintenance databases. Data from four generating units were observed for over 5 years and a reasonable number of equipment classes reviewed. The coal mills are identified as significant equipment that affects the availability of the generating units. This paper describes the interplay of events which includes failure modes, failure, repair and operating time.

KW - reliability

KW - competing risk

KW - engineering

KW - database

U2 - 10.1016/j.jspi.2008.05.037

DO - 10.1016/j.jspi.2008.05.037

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JO - Journal of Statistical Planning and Inference

JF - Journal of Statistical Planning and Inference

SN - 0378-3758

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