An artificial intelligence approach for improving plant operator maintenance proficiency

Edwards, David J., Holt, Gary David and Robinson, Barry (2002) An artificial intelligence approach for improving plant operator maintenance proficiency. Journal of Quality in Maintenance Engineering, 8 (3). pp. 239-252. ISSN 1355-2511

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Construction plant maintenance practice and its plant operators are inextricably linked. This is because, unlike plant operating within the manufacturing sector, construction plant is largely dependent upon operator skill and competence to maintain the item in a safe, fully operational condition. Research has previously successfully modelled machine breakdown, but revealed that the operator’s impact upon machine breakdown rates can be considerable. A conceptual model methodology with which to assess the maintenance proficiency of individual plant operators is presented. Specifically, an artificial intelligent classification model is proposed as a means of classifying plant operator maintenance proficiency into one of three bandings. These are good, average and poor. The results of such work will form the basis of new prescriptive guidelines, for incorporation into the new certificate of training achievement (CTA) scheme, available to inexperienced construction plant operators. The paper concludes with an indication of the palpable benefits of such research, to plant owners and the construction industry at large.

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