Human Error Probability Wiki
Contents |
the field of human reliability assessment (HRA), for the purposes of evaluating the probability of a human error occurring throughout the completion of a specific average human error rate task. From such analyses measures can then be taken to reduce
Human Error Rate Prediction
the likelihood of errors occurring within a system and therefore lead to an improvement in the overall levels
Human Error Rate In Data Entry
of safety. There exist three primary reasons for conducting an HRA; error identification, error quantification and error reduction. As there exist a number of techniques used for such
How To Calculate Human Error Percent
purposes, they can be split into one of two classifications; first generation techniques and second generation techniques. First generation techniques work on the basis of the simple dichotomy of ‘fits/doesn’t fit’ in the matching of the error situation in context with related error identification and quantification and second generation techniques are more theory based in their assessment human error probability table and quantification of errors. ‘HRA techniques have been utilised in a range of industries including healthcare, engineering, nuclear, transportation and business sector; each technique has varying uses within different disciplines. HEART method is based upon the principle that every time a task is performed there is a possibility of failure and that the probability of this is affected by one or more Error Producing Conditions (EPCs) – for instance: distraction, tiredness, cramped conditions etc. – to varying degrees. Factors which have a significant effect on performance are of greatest interest. These conditions can then be applied to a “best-case-scenario” estimate of the failure probability under ideal conditions to then obtain a final error chance. This figure assists in communication of error chances with the wider risk analysis or safety case. By forcing consideration of the EPCs potentially affecting a given procedure, HEART also has the indirect effect of providing a range of suggestions as to how the reliability may therefore be improved (from an ergonomic standpoint) and hence minimising
probability of a human error occurring throughout the completion of a specific task. From such analyses measures can then be taken to reduce the likelihood of errors occurring within a system and therefore lead to an improvement in the human error assessment and reduction technique overall levels of safety. There exist three primary reasons for conducting an HRA; error error tolerant systems identification, error quantification and error reduction. As there exist a number of techniques used for such purposes, they can be split human error probability calculation into one of two classifications; first generation techniques and second generation techniques. First generation techniques work on the basis of the simple dichotomy of 'fits/doesn't fit' in the matching of the error situation in context with https://en.wikipedia.org/wiki/Human_error_assessment_and_reduction_technique related error identification and quantification and second generation techniques are more theory based in their assessment and quantification of errors. 'HRA techniques have been utilised in a range of industries including healthcare, engineering, nuclear, transportation and business sector; each technique has varying uses within different disciplines. Absolute probability judgement, which is also known as direct numerical estimation,[1] is based on the quantification of human error probabilities (HEPs). It is grounded on https://en.wikipedia.org/wiki/Absolute_probability_judgement the premise that people cannot recall or are unable to estimate with certainty, the probability of a given event occurring. Expert judgement is typically desirable for utilisation in the technique when there is little or no data with which to calculate HEPs, or when the data is unsuitable or difficult to understand. In theory, qualitative knowledge built through the experts' experience can be translated into quantitative data such as HEPs. Required of the experts is a good level of both substantive experience (i.e. the expert must have a suitable level of knowledge of the problem domain) and normative experience (i.e. it must be possible for the expert, perhaps with the aid of a facilitator, to translate this knowledge explicitly into probabilities). If experts possess the required substantive knowledge but lack knowledge which is normative in nature, the experts may be trained or assisted in ensuring that the knowledge and expertise requiring to be captured is translated into the correct probabilities i.e. to ensure that it is an accurate representation of the experts' judgements. Contents 1 Background 2 Methodologies 2.1 Aggregated individual method 2.2 Delphi method 2.3 Nominal group technique (NGT) 2.4 Consensus group method 3 Procedure 4 Worked example 4.1 Context 4.2 Required inputs 4.3 Method 4.4 Results/outcomes 4.5 Lessons fr
in fields such as manufacturing, transportation, the military, or medicine. Human performance can be affected by many factors such as age, state of https://en.wikipedia.org/wiki/Human_reliability mind, physical health, attitude, emotions, propensity for certain common mistakes, errors and cognitive biases, etc. Human reliability is very important due to the contributions of humans to the resilience of systems and to possible adverse consequences of human errors or oversights, especially when the human is a crucial part of the large socio-technical systems as is common today. User-centered human error design and error-tolerant design are just two of many terms used to describe efforts to make technology better suited to operation by humans. Contents 1 Analysis techniques 1.1 PRA-based techniques 1.2 Cognitive control based techniques 1.3 Related techniques 1.4 Human Factors Analysis and Classification System (HFACS) 2 See also 3 Footnotes 4 References 5 Further reading 6 External links human error probability 6.1 Standards and guidance documents 6.2 Tools 6.3 Research labs 6.4 Media coverage 6.5 Networking Analysis techniques[edit] A variety of methods exist for human reliability analysis (HRA).[1][2] Two general classes of methods are those based on probabilistic risk assessment (PRA) and those based on a cognitive theory of control. PRA-based techniques[edit] One method for analyzing human reliability is a straightforward extension of probabilistic risk assessment (PRA): in the same way that equipment can fail in a power plant, so can a human operator commit errors. In both cases, an analysis (functional decomposition for equipment and task analysis for humans) would articulate a level of detail for which failure or error probabilities can be assigned. This basic idea is behind the Technique for Human Error Rate Prediction (THERP).[3] THERP is intended to generate human error probabilities that would be incorporated into a PRA. The Accident Sequence Evaluation Program (ASEP) human reliability procedure is a simplified form of THERP; an associated computational tool is Simplified Human Error Analysis Code (SHEAN).[4] More recently, the US Nuclear Regulatory Co