Numerous accidents are caused by human errors leading to unwarranted down time which could in turn cost manufacturers billions of Dollars. These costs are mostly incurred from unscheduled breakdowns and non routine replacement maintenance engineering. Smaller root causes problems are the overall culprit. They are grouped so that errors caused by employees could be subject to some amount of predictability and control. This may be achieved by simultaneously applying the Kendall’s Coefficient of Concordance and the Spearman Correlation Coefficient. Questionnaires were issued. Each contained 40 possible causes of human errors.They were evaluated and ranked by 13 judges. These judges reviewed the questionnaires and came up with the top ten most critical causes of employee human error. These new questionnaires were in turn administered to 10 respondents to give their honest evaluation, opinion, and ranking. These were further analyzed using the Spearman 2-factor model. From the findings, the rankings of the judges were in agreement with the Kendall Coefficient of Concordance of 0.35 and Eigen values of 16.700, and 0.837 of factor loading, f0 and f1 respectively and communality (h2) factor of an eigen value of 3.729 was obtained. Eventually, 3 clusters of human error causation variables A, B and C were obtained and grouped. Within these clusters, the errors could be easily identified and controlled.
