science

Technique for human error-rate prediction

Technique for human error-rate prediction is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Technique for human error-rate prediction rather than just read about it. In short: The Technique for human error-rate prediction (THERP) is a technique that is used in the field of Human Reliability Assessment (HRA) to evaluate the probability of human error occurring throughout the completion of a task. From such an analysis (after calculating a probability of human error in a given task), some corrective measures could be taken to reduce the likelihood of errors occurring within a system.

Key takeaways

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Reference excerpt

The Technique for human error-rate prediction (THERP) is a technique that is used in the field of Human Reliability Assessment (HRA) to evaluate the probability of human error occurring throughout the completion of a task. From such an analysis (after calculating a probability of human error in a given task), some corrective measures could be taken to reduce the likelihood of errors occurring within a system. The overall goal of THERP is to apply and document probabilistic methodological analyses to increase safety during a given process. THERP is used in fields such as error identification, error quantification and error reduction.

Techniques THERP may refer to a number of techniques, which are split into one of two classifications: first-generation techniques and second-generation techniques. First-generation techniques are based on a simple dichotomy, or a dichotomous structure, of whether the technique fits an error situation in the related error identification and quantification of consideration. Second-generation techniques are more theoretical in their assessment and quantification of errors, addressing, rather, the schematic’s situational or interactive elements. HRA techniques are utilized for various applications in a range of disciplines and industries including healthcare, engineering, nuclear power, transportation, and business. THERP models human error probabilities (HEPs) using a fault-tree approach (similar to an engineering risk assessment), which integrate & account for performance-shaping factors that may influence these probabilities. The probabilities for the human reliability analysis event tree (HRAET), for example, are a calculative assessment tool drawn from a database developed by authors Alan D. Swain and H. E. Guttmann. Local data from simulations or accident reports may be used instead if supplemental data may deepen the examination of human-related error. The resultant tree portrays a step-by-step account of the stages involved in a task, in a logical order. The technique is known as a total methodology because it simultaneously manages many different activities, including task analysis, error identification, and representation in the form of HRAET and HEP quantification.

Background THERP is a first-generation methodology, which means that its procedures follow the way conventional reliability analysis models a machine. The technique was developed in the Sandia Laboratories for the US Nuclear Regulatory Commission. Its primary author is Swain, who developed the THERP methodology gradually over a lengthy period. THERP relies on a large human reliability database that contains HEPs and is based upon both plant data and expert judgments. The technique was the first approach in HRA to come into broad use and is still widely used in a range of applications even beyond its original nuclear setting.

THERP methodology The methodology for the THERP technique is broken down into 5 main stages: 1. Define the system failures of interest These failures include functions of the system where human error has a greater likelihood of influencing the probability of a fault, and those of interest to the risk assessor; operations in which there may be no interest include those not operationally critical or those for which there already exist safety countermeasures. 2. List and analyse the related human operations, and identify human errors that can occur and relevant human error recovery modes This stage of the process necessitates a comprehensive task and human error analysis. The task analysis lists and sequences the discrete elements and information required by task operators. For each step of the task, possible errors are considered by the analyst and precisely defined. The possible errors are then considered by the analyst, for each task step. Such errors can be broken down into the following categories:

Errors of omission – leaving out a step of the task or the whole task itself Error of commission – this involves several different types of error: Errors of selection – error in use of controls or in issuing of commands Errors of sequence – required action is carried out in the wrong order Errors of timing – task is executed before or after when required Errors of quantity – inadequate amount or in excess The opportunity for error recovery must also be considered as this, if achieved, has the potential to drastically reduce error probability for a task. The tasks and associated outcomes are input to an HRAET in order to provide a graphical representation of a task’s procedure. The trees’ compatibility with conventional event-tree methodology i.e. including binary decision points at the end of each node, allows it to be evaluated mathematically. An event tree visually displays all events that occur within a system. It starts off with an initiating event, then branches develop as various consequences of the starting event. These are represented in a number of different paths, each associated with a probability of occurrence. As mentioned previously, the tree works on a binary logic, so each event either succeeds or fails. Below is an example of an event tree that represents a system fire:

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Illustrations

Technique for human error-rate prediction illustration

Worked examples

Example 1 — a first encounter with Technique for human error-rate prediction

Start with the simplest possible case. Write down what Technique for human error-rate prediction claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Technique for human error-rate prediction before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Technique for human error-rate prediction ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Technique for human error-rate prediction

In research: Technique for human error-rate prediction appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Technique for human error-rate prediction in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Technique for human error-rate prediction is common in secondary-school and first-year university syllabi. It links to neighbouring topics Human reliability, so understanding it makes those chapters shorter.
In everyday life: Look for Technique for human error-rate prediction outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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Frequently asked questions

What is Technique for human error-rate prediction in simple terms?

Why does Technique for human error-rate prediction matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Technique for human error-rate prediction?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Technique for human error-rate prediction.