Predictive Human Error Analysis technique

This section illustrates how the techniques described in Chapter 4 can be used to develop a procedure for the job of the top floor operator in the batch plant considered earlier. Two techniques are illustrated (i) a hierarchical task analysis (HTA) of the job, and (ii) a predictive human error analysis (PHEA) of the operations involved. HTA provides a description of how the job is actually done while PHEA identifies critical errors which can have an impact on the system in terms of safety or quality. The basic structure of the procedure is derived from the HTA which specifies in increasing detail the goals to be achieved. To emphasize critical task steps, various warnings and cautions can be issued based on the likely errors and recovery points generated by the PHEA. 

ABSTRACT Permit To Work (FTW) is a means of safety system to coordinate different work activities. However, it may be susceptible for human error. The purpose of this study was identification and analysis of human errors in PTW system using Predictive Human Error Analysis (PHEA) technique. The most important identified errors were inadequate isolation of process equipments, inadequate labelling of equipment, and delay in starting the work after issue the work permit, improper gas testing, inadequate site preparation measures etc. Finally for preventing and recovering from the identified errors, site work permit form and its procedure was revised. 

In the second stage. Predictive Human Error Analysis (PHEA) technique was used for... 

In addition to their descriptive fimctions, TA techniques provide a wide variety of information about the task that can be useful for error prediction and prevention. To this extent, there is a considerable overlap between Task Analysis and Human Error Analysis (HEA) techniques described later in this chapter. HEA methods generally take the result of TA as their starting point and examine what aspects of the task can contribute to human error, hr the context of human error reduction in the CPI, a combination of TA and HEA methods will be the most suitable form of analysis. 

The application of human error analysis (HEA) techniques is to predict possible errors that may occur in a task. The next stage of error analysis is to identify error recovery possibilities implicit within the task, and to specify possible... 

The technique for human error-rate prediction (THERP) [ Swain and Guttmann, 1980] is a widely applied human reliability method (Meister, 1984] used to predict human error rates (i.e., probabilities) and the consequences of human errors. The method relies on conducting a task analysis. Estimates of the likelihood of human errors and the likelihood that errors will be undetected are assigned to tasks from available human performance databases and expert judgments. The consequences of uncorrected errors are estimated from models of the system. An event tree is used to track and assign conditional probabilities of error throughout a sequence of activities. 

An evaluation method to determine the probability that a system-required human action, task, or job will be successfully completed within the required time period and that no extraneous human actions detrimental to system performance will be performed. It provides quantitative estimates of human error potential due to work environment, human-machine interfaces, and required operational tasks. Such an evaluation can identify weaknesses in operator interfaces with a system, quantitatively demonstrate improvements in human interfaces, improve system evaluations by including human elements, and demonstrate quantitative prediction of human behavior. See also ATHEANA (A Technique for Human Error Analysis) Human Error Analysis. 

In the process of risk and human reliability assessment, there are various methods to be used, such as Cognitive Reliability and Error Analysis Model (CREAM), A Technique for Human Error Analysis (ATHENA), and Technique for Human Error Rate Prediction (THERP). 

The various analytical methods for predicting and reducing human error can be assigned to four groups or sections. In order to make a start on any form of analysis or prediction of human error, it is obviously necessary to gather information. The first section therefore describes a number of techniques that can be applied to acquire data about what the worker does, or what happened in an accident. 

The other main application area for predictive error analysis is in chemical process quantitative risk assessment (CPQRA) as a means of identifying human errors with significant risk consequences. In most cases, the generation of error modes in CPQRA is a somewhat unsystematic process, since it only considers errors that involve the failure to perform some pre-specified function, usually in an emergency (e.g., responding to an alarm within a time interval). The fact that errors of commission can arise as a result of diagnostic failures, or that poor interface design or procedures can also induce errors is rarely considered as part of CPQRA. However, this may be due to the fact that HEA techniques are not widely known in the chemical industry. The application of error analysis in CPQRA will be discussed further 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). 

Qualitative human error prediction is the most important aspect of assessing and reducing the human contribution to risk. For this reason, it will be described in some detail in this section. The qualitative analysis performed in SPEAR involves the following techniques ... 

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... 

A systematic task analysis is essential for a good prediction of human error. The data for such an analysis come partly from logical analysis of what should happen and partly from observation of what does happen. Such techniques are dealt with in chapter 10. 

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. 

Taxonomy-based HEI techniques use external error mode (EEM) taxonomies to identify potential errors within complex sociotechnical systems. Typically, EEMs are considered for each component step in a particular task or scenario to determine credible errors that may arise during human-machine interaction. Techniques such as the Systematic Human Error Reduction and Prediction Approach (SHERPA) (Embrey, 1986), the Human Error Template (HET) (Stanton et al., 2006), the Technique for the Retrospective and Predictive Analysis of Cognitive Errors (TRACEr) (Shorrock and Kirwan, 2002), and the Cognitive Reliability and Error Analysis Method (CREAM) (Hollnagel, 1998) all use domain-specific EEM taxonomies. Taxonomic approaches to HEI are typically the most successful in terms of sensitivity and are also the least expensive, quickest, and easiest to use however,... 

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... 

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. 

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