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A novel decision diagrams extension method

Author

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  • Li, Shumin
  • Si, Shubin
  • Dui, Hongyan
  • Cai, Zhiqiang
  • Sun, Shudong

Abstract

Binary decision diagram (BDD) is a graph-based representation of Boolean functions. It is a directed acyclic graph (DAG) based on Shannon׳s decomposition. Multi-state multi-valued decision diagram (MMDD) is a natural extension of BDD for the symbolic representation and manipulation of the multi-valued logic functions. This paper proposes a decision diagram extension method based on original BDD/MMDD while the scale of a reliability system is extended. Following a discussion of decomposition and physical meaning of BDD and MMDD, the modeling method of BDD/MMDD based on original BDD/MMDD is introduced. Three case studies are implemented to demonstrate the presented methods. Compared with traditional BDD and MMDD generation methods, the decision diagrams extension method is more computationally efficient as shown through the running time.

Suggested Citation

  • Li, Shumin & Si, Shubin & Dui, Hongyan & Cai, Zhiqiang & Sun, Shudong, 2014. "A novel decision diagrams extension method," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 107-115.
    • Handle: RePEc:eee:reensy:v:126:y:2014:i:c:p:107-115
    DOI: 10.1016/j.ress.2014.01.017
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    References listed on IDEAS

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    1. Xing, Liudong & Levitin, Gregory, 2013. "BDD-based reliability evaluation of phased-mission systems with internal/external common-cause failures," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 145-153.
    2. Remenyte-Prescott, R. & Andrews, J.D., 2008. "An enhanced component connection method for conversion of fault trees to binary decision diagrams," Reliability Engineering and System Safety, Elsevier, vol. 93(10), pages 1543-1550.
    3. Ibáñez-Llano, Cristina & Rauzy, Antoine & Meléndez, Enrique & Nieto, Francisco, 2010. "A reduction approach to improve the quantification of linked fault trees through binary decision diagrams," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1314-1323.
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    Cited by:

    1. Dui, Hongyan & Li, Shumin & Xing, Liudong & Liu, Hanlin, 2019. "System performance-based joint importance analysis guided maintenance for repairable systems," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 162-175.
    2. Wang, Chaonan & Xing, Liudong & Levitin, Gregory, 2015. "Probabilistic common cause failures in phased-mission systems," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 53-60.
    3. Zaitseva, Elena & Levashenko, Vitaly & Kostolny, Jozef, 2015. "Importance analysis based on logical differential calculus and Binary Decision Diagram," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 135-144.
    4. Mo, Yuchang & Xing, Liudong & Amari, Suprasad V. & Bechta Dugan, Joanne, 2015. "Efficient analysis of multi-state k-out-of-n systems," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 95-105.
    5. Zhai, Qingqing & Xing, Liudong & Peng, Rui & Yang, Jun, 2018. "Aggregated combinatorial reliability model for non-repairable parallel phased-mission systems," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 242-250.
    6. Hu, Bin & Seiler, Peter, 2015. "Pivotal decomposition for reliability analysis of fault tolerant control systems on unmanned aerial vehicles," Reliability Engineering and System Safety, Elsevier, vol. 140(C), pages 130-141.

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