Incorporates: International Journal of Quality Science
Online from: 1984
Subject Area: Managing Quality
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|Title:||Maintenance and recurrent event analysis of circuit breaker data|
|Author(s):||Daniel Bumblauskas, (Department of Industrial & Manufacturing Systems Engineering, Iowa State University, Ames, Iowa, USA and Department of Management, Robert J., Trulaske, Sr College of Business, University of Missouri, Columbia, Missouri, USA), William Meeker, (Department of Statistics, Iowa State University, Ames, Iowa, USA), Douglas Gemmill, (Department of Industrial & Manufacturing Systems Engineering, Iowa State University, Ames, Iowa, USA)|
|Citation:||Daniel Bumblauskas, William Meeker, Douglas Gemmill, (2012) "Maintenance and recurrent event analysis of circuit breaker data", International Journal of Quality & Reliability Management, Vol. 29 Iss: 5, pp.560 - 575|
|Keywords:||Asset management, Electric power equipment, Electric power systems, Mean cumulative function, Power system maintenance, Quality control, Reliability|
|Article type:||Research paper|
|DOI:||10.1108/02656711211230526 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
|Acknowledgements:||The authors would like to thank Ed Donohue, Ted Kelley, Stephen Kochis, and Beth Dahm for their support of this research work.|
Purpose – The purpose of this paper is to review cotemporary maintenance programs and analyze factory production data for an SF
Design/methodology/approach – Production and field event data were analyzed using statistical analysis tools. The population data were formatted so that a recurrent event analysis could be conducted to establish the mean cumulative function (MCF) by model and product family (class). Average Field Two-year Recorded Event Rate (AFTRER) is introduced and compared to commonly used Field Incident Rate (FIR) and Mean-Time between Failure (MTBF) measures.
Findings – Common managerial operating questions can be answered as exhibited for the provided circuit breaker population. This includes the longevity of field issues, the anticipated life cycle of a model or class, and AFTRER for models or classes of interest. These statistical analysis tools are used to make critical production quality and asset management observations and aid in decision-making.
Research limitations/implications – Due to limitations in existing database systems, the cost of events and explanatory variables related to event rates were not included in the analyses. There remains much work to be done in terms of the installation and retro-fitting of breakers with conditions monitors in the field.
Practical implications – A framework to analyze maintenance data from fleet of similar assets using recurrent event data analysis is provided. The methods illustrated here would be useful for quality and asset managers to make operating decisions. This includes resource allocation decisions across a network of equipment.
Social implications – Data analyzed are for power circuit breakers which are a critical element in the operation and reliability of the US power grid.
Originality/value – Using recurrent event data analysis to review and develop solutions to production quality and asset management problems including a comparison of AFTRER to FIR and MTBF measures.
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