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Design optimization of a safety-instrumented system based on RAMS+C addressing IEC 61508 requirements and diverse redundancy

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  • Torres-Echeverría, A.C.
  • Martorell, S.
  • Thompson, H.A.

Abstract

This paper presents the design optimization by a multi-objective genetic algorithm of a safety-instrumented system based on RAMS+C measures. This includes optimization of safety and reliability measures plus lifecycle cost. Diverse redundancy is implemented as an option for redundancy allocation, and special attention is paid to its effect on common cause failure and the overall system objectives. The requirements for safety integrity established by the standard IEC 61508 are addressed, as well as the modelling detail required for this purpose. The problem is about reliability and redundancy allocation with diversity for a series–parallel system. The objectives to optimize are the average probability of failure on demand, which represents the system safety integrity, Spurious Trip Rate and Lifecycle Cost. The overall method is illustrated with a practical example from the chemical industry: a safety function against high pressure and temperature for a chemical reactor. In order to implement diversity, each subsystem is given the option of three different technologies, each technology with different reliability and diagnostic coverage characteristics. Finally, the optimization with diversity is compared against optimization without diversity.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:94:y:2009:i:2:p:162-179
    DOI: 10.1016/j.ress.2008.02.010
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    References listed on IDEAS

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    1. Guo, Haitao & Yang, Xianhui, 2007. "A simple reliability block diagram method for safety integrity verification," Reliability Engineering and System Safety, Elsevier, vol. 92(9), pages 1267-1273.
    2. 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.
    3. Konak, Abdullah & Coit, David W. & Smith, Alice E., 2006. "Multi-objective optimization using genetic algorithms: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 992-1007.
    4. Marseguerra, M. & Zio, E. & Martorell, S., 2006. "Basics of genetic algorithms optimization for RAMS applications," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 977-991.
    5. 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. Fu, Jianmin & Li, Honghao & Chi, Yajuan & Zhen, Jia & Xu, Xiangfeng, 2021. "nSIL Evaluation and Sensitivity Study of Diverse Redundant Structure," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    2. Mechri, Walid & Simon, Christophe & BenOthman, Kamel, 2015. "Switching Markov chains for a holistic modeling of SIS unavailability," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 212-222.
    3. Xu, Ming & Chen, Tao & Yang, Xianhui, 2012. "The effect of parameter uncertainty on achieved safety integrity of safety system," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 15-23.
    4. 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.
    5. Cai, Baoping & Li, Wenchao & Liu, Yiliu & Shao, Xiaoyan & Zhang, Yanping & Zhao, Yi & Liu, Zengkai & Ji, Renjie & Liu, Yonghong, 2021. "Modeling for evaluation of safety instrumented systems with heterogeneous components," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    6. Jiangbin Zhao & Shubin Si & Zhiqiang Cai & Ming Su & Wei Wang, 2019. "Multiobjective optimization of reliability–redundancy allocation problems for serial parallel-series systems based on importance measure," Journal of Risk and Reliability, , vol. 233(5), pages 881-897, October.
    7. Mohamed Arezki Mellal & Enrico Zio, 2019. "An adaptive cuckoo optimization algorithm for system design optimization under failure dependencies," Journal of Risk and Reliability, , vol. 233(6), pages 1099-1105, December.
    8. Redutskiy, Yury & Camitz-Leidland, Cecilie M. & Vysochyna, Anastasiia & Anderson, Kristanna T. & Balycheva, Marina, 2021. "Safety systems for the oil and gas industrial facilities: Design, maintenance policy choice, and crew scheduling," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    9. Qi, Meng & Kan, Yufeng & Li, Xun & Wang, Xiaoying & Zhao, Dongfeng & Moon, Il, 2020. "Spurious activation and operational integrity evaluation of redundant safety instrumented systems," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    10. 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.
    11. Cheraghi, Morteza & Taghipour, Sharareh, 2024. "A mathematical optimization model for determining safety integrity levels in process facilities," Reliability Engineering and System Safety, Elsevier, vol. 243(C).

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