Toggle Main Menu Toggle Search

Open Access padlockePrints

A Quantitative Method for Failure Mode and Effects Analysis

Lookup NU author(s): Professor Christian Hicks


Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Failure Mode and Effects Analysis (FMEA) is a commonly used method for designing maintenance routines by analyzing potential failures, predicting their effect and agreeing preventive action. It is often used as a basis for making decisions on operational and capital expenditure. The literature has reported that despite its popularity, the FMEA method lacks transparency, repeatability and the ability to continuously improve maintenance routines. In this paper an enhancement to the FMEA method is proposed, which enables the probability of asset failure to be expressed as a function of explanatory variables, such as age, operating conditions or process measurements. A ranked list of risk factors is produced that is based on the probability of failure and total costs, which can be used to determine maintenance routines. In its simplest form, with time as a single explanatory variable, the method reverts to time-based preventive maintenance. The procedure facilitates continuous improvement as the dataset builds up. The proposed method is demonstrated through two datasets on failures. The first is retrieved from public record and covers the failure of nuclear power plants in the United States. The second is based on an operating company exploiting a major gas field in The Netherlands. The contributions of the paper are: (a) the new procedure, which is more transparent and repeatable; and (b) a novel application of logistic modeling for evaluating risk associated with the failure of physical assets.

Publication metadata

Author(s): Braaksma AJJ, Meesters AJ, Klingenberg W, Hicks C

Publication type: Article

Publication status: Published

Journal: International Journal of Production Research

Year: 2012

Volume: 50

Issue: 23

Pages: 6904-6917

Print publication date: 16/12/2011

ISSN (print): 0020-7543

ISSN (electronic): 1366-588X

Publisher: Taylor & Francis Ltd.


DOI: 10.1080/00207543.2011.632386


Altmetrics provided by Altmetric