Human error knowledge-based

A relatively simple model has been developed by Rasmussen to quantify human error rates based on the level of training (Rasmussen (1979, 1981)). This model divides the behaviour into three basic categories skill-based, rule-based, and knowledge-based behaviours. 

As was discussed in Chapter 2 Rasmussen has provided the basic model of human error based on three levels of behaviour skill-, rule- and knowledge-based (S-B, R-B, K-B). This SRK model has been operationalised to describe operator errors in process control tasks by combining it with characteristic task elements, which as a whole cover the entire spectrum of operator subtasks. 

Skills, rules, and knowledge model Models human information processing in terms of three levels of behavioral control skill based, rule based, and knowledge based Models the processes and requirements for each level of behavior Can be used with quantitative models of human performance to estimate task time and errors... 

An important feature of ADS-IDAC is that all information must first he perceived by the operator prior to being used to formulate a diagnosis or activate a knowledge-based action. Because the perception process can filter and distort plant information, the operator s plant assessment will not necessarily match the actual plant state. Consequently, the operator may skip procediue steps that are relevant to the actual plant state or execute inappropriate knowledge-based actions. By examining the situations that cause the operator s perceived plant assessment to diverge from reality, situational contexts that might lead to human error events can be identified. 

Human errors fall into three groups - slips, lapses and mistakes, which can be further sub-divided into rule-based and knowledge-based mistakes. 

Other authors like Jens Rasmussen ([14], [15]) distinguish between different levels of human performance and correlate them to required attention and familiarity with the task, cf. Fig.5. It is evident that knowledge-based actions are associated with the highest error probability, but most actions required from a car driver are rule based like obeying traffic signs, or skill-based like changing the gears. 

The classification of human error within the FASGEP project takes into account the woric of Rasmussen, specifically the classification of Rule-Based errors, Skill-Based errors, and Knowledge-Based errors. The causal relationships for each of the classifications have been developed into a causal network. A type of graphical probability model is based on this. 

One problem with the Rasmussen data is that it requires subjective analysis of the operator s training and capabilities. A set of human error rates was developed by Hunns for more specific tasks, not relying as much on the operator s capabilities and knowledge (Hunns (1982)). These data are presented in Table 9.3 and were based on extrapolation from human error rate databases. These data are similar to the rates of Rasmussen in Table 9.2 but provide some actual examples and do not require as much subjective analysis as the Rasmussen data. 

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