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Human error engineering is a discipline of acquiring and applying scientific and mathematical knowledge in order to build or design a system or a process that is free of unwanted human errors. The word “engineering” means that it is advanced beyond the level of just a “science,” which merely focuses on understanding the fundamentals of human error. Human error engineering focuses on applying quantitative tools to find the most cost-effective ways to prevent, detect, and correct unwanted human errors.
In general, there are six categories of human errors. They are listed in the following table:
SKILL-BASED ERROR | RULE-BASED ERROR | KNOWLEDGE-BASED ERROR | ||
|---|---|---|---|---|
| OMMISSION | Lapse | Application error | Noncompliance error | Indecision error |
| COMMISSION | Slip | Mistake | ||
Over the past ten years, PII has collected numerous sets of human error data from more than 30,000 field workers to produce six experiential correlations that could predict these six types of errors. The six experiential correlations correlate the error rates with key observable causal factors, such as daily working hours, frequency of lessons learned meetings, or quality of pre-job briefings.
Until this quantitative and rigorous engineering approach was developed by PII, critical factors that induce human errors, and their relative contribution among themselves, could not be determined, nor could effective ways to prevent, detect, and correct human errors be found.
For example, PII found that the error rate of slips is positively correlated with the Hazard Awareness Index, which is a function of drowsiness, distraction, over-confidence, time pressure, and one’s ability to recognize the hazards just before the occurrence of the hazards. Using this experiential correlation, one is able to perform the following tasks:
Our technology in addressing equipment failures, people performance and organizational/procedural/management inefficiencies and root causes is unmatched by any company in the world.