Multi-objective optimization of safety instrumented systems maintenance strategy: a case study

PurposeThe main objective of safety instrumented systems (SISs) is to maintain a safe condition of a facility if hazardous events occur. However, in some cases, SIS's can be activated prematurely, these activations are characterized in terms of frequency by a Spurious Trip Rate (STR) and their...

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Veröffentlicht in:The International journal of quality & reliability management 2021-07, Vol.38 (8), p.1792-1815
Hauptverfasser: Touahar, Hafed, Ouazraoui, Nouara, Khanfri, Nor El Houda, Korichi, Mourad, Bachi, Bilal, Boukrouma, Houcem Eddine
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container_end_page 1815
container_issue 8
container_start_page 1792
container_title The International journal of quality & reliability management
container_volume 38
creator Touahar, Hafed
Ouazraoui, Nouara
Khanfri, Nor El Houda
Korichi, Mourad
Bachi, Bilal
Boukrouma, Houcem Eddine
description PurposeThe main objective of safety instrumented systems (SISs) is to maintain a safe condition of a facility if hazardous events occur. However, in some cases, SIS's can be activated prematurely, these activations are characterized in terms of frequency by a Spurious Trip Rate (STR) and their occurrence leads to significant technical, economic and even environmental losses. This work aims to propose an approach to optimize the performances of the SIS by a multi-objective genetic algorithm. The optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).Design/methodology/approachThe optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).FindingsA case study concerning a safety instrumented system implemented in the RGTE facility has shown the great applicability of the proposed approach and the results are encouraging. The results show that the selection of a good maintenance strategy allows a very significant minimization of the PFDavg, the frequency of spurious trips and Life Cycle Costs of SIS.Originality/valueThe maintenance strategy defined by the system designer can be modified and improved during the operational phase, in particular safety systems. It constitutes one of the least expensive investment strategies for improving SIS performances. It has allowed a considerable minimization of the SIS life cycle costs; PFDavg and the frequency of spurious trips.
doi_str_mv 10.1108/IJQRM-03-2020-0076
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However, in some cases, SIS's can be activated prematurely, these activations are characterized in terms of frequency by a Spurious Trip Rate (STR) and their occurrence leads to significant technical, economic and even environmental losses. This work aims to propose an approach to optimize the performances of the SIS by a multi-objective genetic algorithm. The optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. 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However, in some cases, SIS's can be activated prematurely, these activations are characterized in terms of frequency by a Spurious Trip Rate (STR) and their occurrence leads to significant technical, economic and even environmental losses. This work aims to propose an approach to optimize the performances of the SIS by a multi-objective genetic algorithm. The optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. 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The results show that the selection of a good maintenance strategy allows a very significant minimization of the PFDavg, the frequency of spurious trips and Life Cycle Costs of SIS.Originality/valueThe maintenance strategy defined by the system designer can be modified and improved during the operational phase, in particular safety systems. It constitutes one of the least expensive investment strategies for improving SIS performances. It has allowed a considerable minimization of the SIS life cycle costs; PFDavg and the frequency of spurious trips.</abstract><cop>Bradford</cop><pub>Emerald Publishing Limited</pub><doi>10.1108/IJQRM-03-2020-0076</doi><tpages>24</tpages></addata></record>
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source Emerald eJournals
subjects Binomial distribution
Costs
Decision making
Design optimization
Economics
Energy industry
Failure
Gases
Genetic algorithms
Investment strategy
Life cycle costs
Maintenance costs
Multiple objective analysis
Optimization techniques
Plant shutdowns
Safety
Shutdowns
Systems design
title Multi-objective optimization of safety instrumented systems maintenance strategy: a case study
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