Human Error Probability Evaluation

the importance of each element (derrick, vessel, lazy decky, net and Gilson) is determined. Using the comparison scale in Table 9.7, the matrix below is obtained for the probability importance of each element. 

The weighting vector and normalised vector are determined by considering the weighting vector obtained in the Level Two matrix and are shown below  

The probability of human error is considered for each of the task carried out by determining the type of human behaviour required to carry out the task successbilly. Using the generic human error data by Rasmussen (Table 9.2), each task is assigned the operator behaviour and the generic error probability. This data is then used to compare each task against the others to determine the Level Three matrix. The various tasks identified in this example and the associated generic data are provided in Table 9.8. 

The matrices for the probability of occurrence for each task are determined as follows  

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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. 

History and Technical Basis. The influence diagram approach (IDA) (also known as the sociotechnical approach to human reliability (STAHR) (see Phillips et al., 1990) is a technique that is used to evaluate human error probabilities as a... 

The alarm system contributes to reducing risk to acceptable level. The reliabdify of entire alarm system consists of reliability of equipment (hardware), software and human - operator expressed by human error probability (HEP) evaluated using relevant methods of human reliability analysis (HRA). To provide required... 

Potential human errors and equipment failures are combined in dynamic event trees for the final evaluation of event probabilities as identified initially from the bow tie diagrams. Data about Human Error Probabilities (HEPs) are estimated with the use of the FPE tool on the basis of expert judgement and theoretical insight (i.e., the CREAM methodology HoUnagel 1998) applied in combination with fuzzy logic principles (Zadeh 2008). 

According to this rating, a screening of the human performance is performed. Moreover, since a nominal task analysis has been performed to analyse all tasks in sequence, probabilities for human errors that can lead to deviations from the required sequence can be estimated. Critical PSFs have been also identified and their impact to the human error probability is evaluated with the FPE. Additionally, critical operating and recovery points needing improvements are identified. The imp act o f the se improvements to the overall hmnan performance is depicted through the use of the FPE tool. This whole process is explained with the use of a specific example. 

The human error probabilities used should reflect the factors which can influence the performance of the operator, including the level of stress, the time available to carry out the task, the availabihty of operating procedures, the level of training and environmental conditions. These should be identified by the task analysis carried out as part of the design evaluation. 

The Technique for Human Error Rate Prediction (THERP) was developed by Swain and Guttman (1983) to evaluate the probability of human error within specific tasks. THERP uses a fault tree approach to model Human Error Probabilities (HEP), but also attempts to account for other factors in the environment that may influence these probabilities. These factors are referred to as Performance Shaping Eactors (PSE). The probabilities used in THERP can either be generated by the analyst, usually from simulator data, or can be taken from tables generated by Swain and Guttman from available data and expert judgement. 

Kliigel J (2007) An improved methodology for the evaluation of human error probabilities in a seismic PSA. In Transactiims, SMiRT 19, Toronto Pellissetti ME, Klapp U (2011) Integration of correlation models fin seismic failures into fault tree based seismic PSA. In Transactions, SMiRT 21, New Delhi... 

While OAETs are best used for the qualitative insights that are gained, they can also be used as a basis for the quantitative assessment of human reliability. By assigning error probabilities to each node of the event tree and then multiplying these probabilities, the probability of each event state can be evaluated (see Chapter 5). 

In April 1982, a data workshop was held to evaluate, discuss, and critique data in order to establish a consensus generic data set for the USNRC-RES National Reliability Evaluation Program (NREP). The data set contains component failure rates and probability estimates for loss of coolant accidents, transients, loss of offsite power events, and human errors that could be applied consistently across the nuclear power industry as screening values for initial identification of dominant accident sequences in PRAs. This data set was used in the development of guidance documents for the performance of PRAs. 

This approach is illustrated by the development of event trees and fault tree analysis. In fault tree analysis, the probability of an accident is estimated by considering the probabihty of human errors, component failures, and other events. This approach has been extensively applied in the field of risk analysis (Gertman and Blackman 1994). THERP (Swain and Guttman 1983) extends the conditioning approach to the evaluation of human reliability in complex systems. 

Use of conditional human error probabihties (HEPs) to model the effect of dependence the THERP approach amounts to evaluate the probability of failure of one task, when it is known that the previous task has failed. 

Fault tree analysis is a technique by which the system safety engineer can rigorously evaluate specific hazardous events. It is a type of logic tree that is developed by deductive logic from a top undesired event to all subevents that must occur to cause it. It is primarily used as a qualitative technique for studying hazardous events in systems, subsystems, components, or operations involving command paths. It can also be used for quantitatively evaluating the probability of the top event and all subevent occurrences when sufficient and accurate data are available. Quantitative analyses shall be performed only when it is reasonably certain that the data for part/component failures and human errors for the operational environment exist. 

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. 

The hazard identification and evaluation of a complex process by means of a diagram or model that provides a comprehensive, overall view of the process, including its principal elements and the ways in which they are interrelated. There are four principal methods of analysis failure mode and effect, fault tree, THERP, and cost-benefit analysis. Each has a number of variations, and more than one may be combined in a single analysis. See also Cost-Benefit Analysis Failure Mode and Effects Analysis (FMEA/FMECA) Fault Tree Analysis (FTA) THERP (Technique for Human Error Rate Probability). 

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. 

Epistemic uncertainty is uncertainty that comes from lack of knowledge. This lack of knowledge comes from many sources, for example, inadequate understanding of the processes, incomplete knowledge of the phenomena, imprecise evaluation of the related charactetistics, etc. Epistemic uncertainties affect the values of the probabilities and frequencies of the events included in the accident scenarios, such as mechanical failure and repair rate, probability of failure on demand for a control system, or human error. There are three different cases in this regard ... 

CREAM Cognitive reliability and error analysis method. In CREAM, the operator model is more significant and less simplistic than that of first generation approaches. It can be used both for performance prediction as well as accident analysis. CREAM is used for evaluation of the probability of a human error for completion of a specific task. There is good application of fuzzy logic in this method. It was again started for nuclear application but has wider applications, too. 

There are a number of methods for evaluation of the probability of human error, for example, the technique for human error rate prediction, discussed earlier (Clause 6.2.1 of Chapter V). The best source for determining the human error rate would be company/facility-specific historical data, but in most organizations this is not available [11]. So, other means need to be explored. The reliability of support systems necessary for an operator s action is also an important issue that can influence risk reduction. The majority of SIS systems are designed as deenergize to actuate. The calculation of PFD for these SIS systems does not generally have to take into consideration any system outside of the SIS. See also Clause 3.2.2. 

The basis of quantitative risk assessments and risk evaluations is probability. Probabilities of equipment failures and human errors are fed into the risk assessment process. Quantitative risk assessment (called probabilistic safety assessment in Europe) depends very heavily on this. 

Regardless of the variety of HRA methods available to enable practitioners to assess the risks associated with human error by estimating its probability, the substantially high uncertainties related to the human behavioural characteristics, interlaced with actual technology aspects and organisational context, turn this kind of evaluation into a very complicated matter, raising reasonable concern about the accuracy and practicality of such probabilities. 

Fault Tree Analysis (FTA) is a formal deductive procedure for determining combinations of component failures and human errors that could result in the occurrence of specified undesired events at the system level (Ang and Tang (1984)). It is a diagrannnatic method used to evaluate the probability of an accident resulting from sequences and combinations of faults and failure events. This method can be used to analyse the vast majority of industrial system reliability problems. FTA is based on the idea that ... 

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