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General Paper

Optimal inspection intervals for safety systems with partial inspections

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Pages 2051-2062 | Received 01 Mar 2010, Accepted 01 Aug 2010, Published online: 21 Dec 2017
 

Abstract

The introduction of International Standard IEC 61508 and its industry-specific derivatives sets demanding requirements for the definition and implementation of life-cycle strategies for safety systems. Compliance with the Standard is important for human safety and environmental perspectives as well as for potential adverse economic effects (eg, damage to critical downstream equipment or a clause for an insurance or warranty contract). This situation encourages the use of reliability models to attain the recommended safety integrity levels using credible assumptions. During the operation phase of the safety system life cycle, a key decision is the definition of an inspection programme, namely its frequency and the maintenance activities to be performed. These may vary from minimal checks to complete renewals. This work presents a model (which we called ρβ model) to find optimal inspection intervals for a safety system, considering that it degrades in time, even when it is inspected at regular intervals. Such situation occurs because most inspections are partial, that is, not all potential failure modes are observable through inspections. Possible reasons for this are the nature and the extent of the inspection, or potential risks generated by the inspection itself. The optimization criterion considered here is the mean overall availability Ao, but also taking into account the requirements for the safety availability As. We consider several conditions that ensure coherent modelling for these systems: sub-systems decomposition, k-out-of-n architectures, diagnostics coverage (observable/total amount of failure modes), dependent and independent failures, and non-negligible inspection times. The model requires an estimation for the coverage and dependent-failure ratios for each component, global failure rates, and inspection times. We illustrate its use through case studies and compare results with those obtained by applying previously published methodologies.

Acknowledgements

The authors acknowledge Dr Per Hokstad of the Department of Safety and Reliability, SINTEF Industrial Management, for kindly letting us use the example presented in Hauge et al (2006). The first author acknowledges the financial support of Material and Manufacturing Ontario and member companies of the Centre for Maintenance Optimization and Reliability Engineering (C-MORE) Consortium that allowed his research visit to the University of Toronto.

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