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Multi-objective genetic algorithm for optimization of system safety and reliability based on IEC 61508 requirements: A practical approach

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  • A. C. Torres-Echeverria
  • H. A. Thompson

Abstract

This paper presents a practical approach for optimization by evolutionary computation of safety instrumented system design, based on safety and reliability measures, plus life cycle cost. The standard IEC 61508 establishes the necessity of this kind of systems to meet specific safety integrity requirements, expressed in terms of safety integrity levels (SIL). The SIL is determined in terms of average probability of failure on demand (PFD avg ) for control systems that operate in demand mode. The optimization executed takes into account the level of modelling detail contemplated by the standard, including multiple failure modes, diagnostic coverage, and common cause failures. This study addresses the case of series-parallel systems. Optimization is approached by treating the problem as one of redundancy and reliability allocation, together with testing intervals specifications. Modelling is made through fault tree analysis with house events. The multi-objective genetic algorithm proposed by Fonseca and Fleming is used as the optimization technique.

Suggested Citation

  • A. C. Torres-Echeverria & H. A. Thompson, 2007. "Multi-objective genetic algorithm for optimization of system safety and reliability based on IEC 61508 requirements: A practical approach," Journal of Risk and Reliability, , vol. 221(3), pages 193-205, September.
    • Handle: RePEc:sae:risrel:v:221:y:2007:i:3:p:193-205
    DOI: 10.1243/1748006XJRR85
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    References listed on IDEAS

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    1. Gen, Mitsuo & Yun, YoungSu, 2006. "Soft computing approach for reliability optimization: State-of-the-art survey," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 1008-1026.
    2. Salazar, Daniel & Rocco, Claudio M. & Galván, Blas J., 2006. "Optimization of constrained multiple-objective reliability problems using evolutionary algorithms," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 1057-1070.
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    Cited by:

    1. Torres-Echeverría, A.C. & Martorell, S. & Thompson, H.A., 2012. "Multi-objective optimization of design and testing of safety instrumented systems with MooN voting architectures using a genetic algorithm," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 45-60.
    2. Torres-Echeverría, A.C. & Martorell, S. & Thompson, H.A., 2009. "Modelling and optimization of proof testing policies for safety instrumented systems," Reliability Engineering and System Safety, Elsevier, vol. 94(4), pages 838-854.
    3. Torres-Echeverría, A.C. & Martorell, S. & Thompson, H.A., 2011. "Modeling safety instrumented systems with MooN voting architectures addressing system reconfiguration for testing," Reliability Engineering and System Safety, Elsevier, vol. 96(5), pages 545-563.
    4. Torres-Echeverría, A.C. & Martorell, S. & Thompson, H.A., 2009. "Design optimization of a safety-instrumented system based on RAMS+C addressing IEC 61508 requirements and diverse redundancy," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 162-179.

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