Human reliability analysis techniques

Di Pasquale V., lannone R., Miranda S. Riemma S. 2013. An Overview of Human Reliability Analysis Techniques in Manufacturing Operations. In Prof Massi-miliano Schiraldi (ed.). Operations Management. 

Human error probabilities can also be estimated using methodologies and techniques originally developed in the nuclear industry. A number of different models are available (Swain, Comparative Evaluation of Methods for Human Reliability Analysis, GRS Project RS 688, 1988). This estimation process should be done with great care, as many factors can affect the reliability of the estimates. Methodologies using expert opinion to obtain failure rate and probability estimates have also been used where there is sparse or inappropriate data. 

Such a task description invites task analysis, which would lead naturally to human reliability analysis (HRA). Indeed, perhaps the earliest work in this field applied HRA techniques to construct fault trees for aircraft structural inspection (Lock and Strutt 1985). The HRA tradition lists task steps, such as expanded versions of the generic functions above, lists possible errors for each step, then compiles performance shaping factors for each error. Such an approach was tried early in the FAA s human factors initiative (Drury et al. 1990) but was ultimately seen as difficult to use because of the sheer number of possible errors and PSFs. It is occasionally revised, such as in the current FRANCIE project (Haney 1999), using a much expanded framework that incorporates inspection as one of a number of possible maintenance tasks. Other attempts have been made to apply some of the richer human error models (e.g.. Reason 1990 Hollnagel 1997 Rouse 1985) to inspection activities (La-toreUa and Drury 1992 Prabhu and Drury 1992 Latorella and Prabhu 2000) to inspection tasks. These have given a broader understanding of the possible errors but have not helped better define the PoD curve needed to ensure continuing airworthiness of the civil air fleet. 

Lyons, M Adams, S Woloshynowych, M. and Vincent, C.A. (2004) Human reliability analysis in healthcare a review of techniques. InternationalJournal of Risk and Safety in Medicine, 16(4), 223-237. 

All of these techniques rely on past experience to a certain extent. Fault and event trees are the most common frequency modeling techniques for complex situations that require tracking of chains of events. Human reliability analysis and external events analysis can be considered essentially as components of fault and event tree analysis, with the information generated from their application to he fed into the fault and event trees. 

Human reliability analysis is an important component of risk analysis. Reviews of past accidents show that human error accounts for the vast majority of these events. The technique most widely used for estimating human error probabilities is called THERP (Swain and Guttman, 1983). The method uses event trees drawn in a different format to arrive at a human error probability. See Fig. 10.15 for an example. In these event trees, failure paths branch right and success paths branch left. 

Human Error Identification or Human Reliability Analysis methods and techniques available. 

Historically, the emphasis in Human Reliability Analysis (HRA) has been on techniques for the derivation of Human Error Probabilities (HEPs) for use in systems analysis techniques such as FTA. However, HEA should be an integrated process that includes a systematic and rigorous qualitative analysis to identify the nature of the errors that can arise prior to any attempt at quantification. This qualitative Human Error Identification (HEI) must ensure that no significant failures are omitted from the analysis. 

There are a number of methods for evaluating the probability of human error. Two of the better-known methods are the Technique for Human Error Rate Prediction (THERP) (Reference NUREG/CR-1278) and the Accident Sequence Evaluation Program Human Reliability Analysis Procedure (Reference NUREG/CR-4772). Error rates are usually established on a per-demand basis. 

This involves assessing the design, by means of reliability analysis techniques, to determine whether the targets can be met. Techniques include fault tree and logic block diagram and FMEA analysis, redundancy modeling, assessments of common cause failure, human error modeling, and the choice of appropriate component failure rate data. Reliability assessment may also be used to evaluate potential financial loss. The process is described in Work Instruc-tion/001 (Random hardware failures). 

A THERP tree is a technique used in human reliability assessment to calculate the probability of a human error during the execution of a task. (THERP stands for Technique for Human Error Rate Prediction.) A THERP tree is basically an event tree, where the root is the initiating event and the leaves are the possible outcomes. THERP is described in a publication from 1983 (Swain, A.D. and Guttmann, H.E., Handbook of Human Reliability Analysis with Emphasis on Nuclear Power Plant Applications, NUREG/CR-1278, USNRC), and is still widely used despite its unrealistic assumptions about human performance. One important... 

Second generation methods which were first applied in 1990, are based on a cognitive model that is more appropriate to explain human behavior. The focus shifted to the cognitive aspects of humans, the causes of errors rather than their frequency, the study of the interaction of the factors that increase the probability of error, and the interdependencies of the PSF (Fehce Petrillo, 2011). The most representative tools are Standardized Plant Analysis Risk-Human reliability analysis method (SPAR-H), German et al. (2005) A Technique for Human Error ANAlysis (ATHEANA), NUREG-1624 (2000) as well as Cognitive Reliability and Error Analysis Method (CREAM), Hollnagel (1998). 

This tool is based on the Technique for Human Error Rate Prediction. ASEP comprises pre-accident screening with nominal human reliability analysis, and post-accident screening and nominal human reliability analysis facilities (Kirwan, and Ainsworth, 1992)... 

As implied in the diagram representing the GEMS model (Figure 2.5) and discussed in Section 2.6.3, certain characteristic error forms occur at each of the three levels of performance. This information can be used by the human-reliability analyst for making predictions about the forms of error expected in the various scenarios that may be considered as part of a predictive safety analysis. Once a task or portion of a task is assigned to an appropriate classification, then predictions can be made. A comprehensive set of techniques for error prediction is described in Chapter 5. 

In addition, the chapter will provide an overview of htunan reliability quantification techniques, and the relationship between these techniques and qualitative modeling. The chapter will also describe how human reliability is integrated into chemical process quantitative risk assessment (CPQRA). Both qualitative and quantitative techniques will be integrated within a framework called SPEAR (System for Predictive Error Analysis and Reduction). 

If the results of the qualitative analysis are to be used as a starting-point for quantification, they need to be represented in an appropriate form. The form of representation can be a fault tree, as shown in Figure 5.2, or an event tree (see Bellamy et al., 1986). The event tree has traditionally been used to model simple tasks at the level of individual task steps, for example in the THERP (Technique for Human Error Rate Prediction) method for human reliability... 

Because most research effort in the human reliability domain has focused on the quantification of error probabilities, a large number of techniques exist. However, a relatively small number of these techniques have actually been applied in practical risk assessments, and even fewer have been used in the CPI. For this reason, in this section only three techniques will be described in detail. More extensive reviews are available from other sources (e.g., Kirwan et al., 1988 Kirwan, 1990 Meister, 1984). Following a brief description of each technique, a case study will be provided to illustrate the application of the technique in practice. As emphasized in the early part of this chapter, quantification has to be preceded by a rigorous qualitative analysis in order to ensure that all errors with significant consequences are identified. If the qualitative analysis is incomplete, then quanhfication will be inaccurate. It is also important to be aware of the limitations of the accuracy of the data generally available... 

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