J Selvik

A framework for reliability and risk centered maintenance

Reliability centered maintenance (RCM) is a well-established analysis method for preventive maintenance planning. As its name indicates, reliability is the main point of reference for the planning, but consequences of failures are also assessed. However, uncertainties and risk are to a limited extent addressed by the RCM method, and in this paper we suggest an extension of the RCM to reliability and risk centered maintenance (RRCM) by also considering risk as the reference for the analysis in addition to reliability. A broad perspective on risk is adopted where uncertainties are the main component of risk in addition to possible events and associated consequences. A case from the offshore oil and gas industry is presented to illustrate and discuss the suggested approach.

Using the ALARP principle for safety management in the energy production sector of chemical industry

Abstract In the context of chemical industry, in particular in high hazard industries, the adoption of safety measures is essential to reduce risks and environmental impacts, due to the release of dangerous substances, at level that is reasonably practicable. The ALARP (As Low As Reasonably Practicable) principle is broadly used for decision-making in safety management, supported by cost-benefit analyses and the grossly disproportionate criterion, but without paying the proper attention to the decision frame (defined by the level of uncertainty and knowledge of the chemical phenomena, the use of best available technologies, the potential of major losses due to the release of hazardous materials and other items). In this paper, by examining the energy production sector of chemical industry, it will be argued that the decision context makes the application of the ALARP principle not always proper, whereas a dynamic interpretation, in which decisions are made oscillating between two borderlines, where in one case reference is made to expected values and in the other one to the precautionary principle, is more appropriate.

How to interpret safety critical failures in risk and reliability assessments

Abstract Management of safety systems often receives high attention due to the potential for industrial accidents. In risk and reliability literature concerning such systems, and particularly concerning safety-instrumented systems, one frequently comes across the term ‘safety critical failure’. It is a term associated with the term ‘critical failure’, and it is often deduced that a safety critical failure refers to a failure occurring in a safety critical system. Although this is correct in some situations, it is not matching with for example the mathematical definition given in ISO/TR 12489:2013 on reliability modeling, where a clear distinction is made between ‘safe failures’ and ‘dangerous failures’. In this article, we show that different interpretations of the term ‘safety critical failure’ exist, and there is room for misinterpretations and misunderstandings regarding risk and reliability assessments where failure information linked to safety systems are used, and which could influence decision-making. The article gives some examples from the oil and gas industry, showing different possible interpretations of the term. In particular we discuss the link between criticality and failure. The article points in general to the importance of adequate risk communication when using the term, and gives some clarification on interpretation in risk and reliability assessments.

How to classify failures when collecting data for safety-instrumented systems in the oil and gas industry

The oil and gas industry places a high value on achieving high reliability and availability on safety critical equipment. To achieve this, assessments of the reliability performances of such equipment are required, both before and during the production phase. The fact that the reliability data available to support the assessments is often sparse or insufficiently detailed presents a challenge. These assessments also typically require insights into the system in which the equipment is used and information about failure detection. However, this ensemble information is often difficult to achieve in the way the data are collected today. As a response to this challenge, one suggested option is to collect reliability data using one acknowledged failure mode classification specifically designed to assess the reliability of safety-instrumented systems. This is a classification adopted from the International Electrotechnical Commission standard 61508. In this article, we discuss the pros and cons of adopting this failure mode classification in generic reliability data collection in the oil and gas industry. One argument discussed is that the data may lack relevant information about the associated safety system and thus be valid for a specific system only, not for generic equipment and systems in general. Hence, should the classification be implemented, the collected data should be used with care.

Prioritising of safety measures in land use planning: on how to merge a risk-based approach with a cost-benefit analysis approach

The Norwegian Water Resources and Energy Directorate (NVE) is a governmental body, which, i.e., seeks to improve societys ability to deal with floods and landslides. The NVE is required by the national government and the Norwegian parliament to prioritise flood defences and landslide damage in those situations considered of highest risk. At the same time, the NVE should also prioritise safety measures with reference to cost-effectiveness. Within the NVE, prioritising safety measures with reference to risk and to cost-effectiveness is stated as challenging, and in some situations contradictory. To improve this situation, and to contribute to the ability to achieve more informed decisions upon prioritising of safety measures against floods and landslides, we have in this paper developed a semi-quantitative approach which incorporates assessments of both risk and cost-effectiveness. A more consistent and transparent decision-making process is then achieved. An example is included to illustrate our ideas.