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An Overview on Human Error Analysis and Reliability Assessment

In: Human Factors and Reliability Engineering for Safety and Security in Critical Infrastructures

Author

Listed:
  • Fabio Felice

    (University of Cassino and Southern Lazio)

  • Antonella Petrillo

    (University of Napoli “Parthenope”)

Abstract

There is a continuous debate about the proper role of man and machine in complex operational frameworks. Formal human analyses and risk management techniques are becoming more important part to manage the relationship between human factors and accident analyses. There are different types of Human Reliability Analysis (HRA) models. HRA methods differ in their characteristics but a common feature in all methods is the definition of the human error probability (HEP). The aim of this chapter is not to cover all of the possible HRA approaches and above not from a mathematical point of view but conceptual one. In fact, no one approach can answer all of the separate issues that can arise in human reliability. The utility of a particular approach is a function of a number of components, not just the absolute value of a method. Expert judgment is an integral part of HRA to capture information about human actions. Definitively, the aim of this chapter is twofold. It tries to respond to these questions: What is HRA? and What are the main features of the most well-known HRA methods?

Suggested Citation

  • Fabio Felice & Antonella Petrillo, 2018. "An Overview on Human Error Analysis and Reliability Assessment," Springer Series in Reliability Engineering, in: Fabio De Felice & Antonella Petrillo (ed.), Human Factors and Reliability Engineering for Safety and Security in Critical Infrastructures, pages 19-41, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-319-62319-1_2
    DOI: 10.1007/978-3-319-62319-1_2
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    Cited by:

    1. Surbhi Gupta & Anil Chandra, 2022. "A four-unit repairable system with three subsystems in series and one subsystem containing n components in parallel under environmental failure," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(4), pages 1895-1902, August.
    2. Mario Di Nardo & Mariano Clericuzio & Teresa Murino & Chiara Sepe, 2020. "An Economic Order Quantity Stochastic Dynamic Optimization Model in a Logistic 4.0 Environment," Sustainability, MDPI, vol. 12(10), pages 1-25, May.

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