A profile for classifying plant operator maintenance proficiency

For plant managers in charge of personnel recruitment (hiring, selection or assessment), selecting the ideal plant operative is a difficult task. The decision to choose a candidate rests upon the manager's intuitive assessment and judgement of the operator's proficiency. The thesis presents research that models plant operators' maintenance proficiency and provides a tool to assist managers select the best operative. Data for this work was collated via a UK nation-wide questionnaire survey that sought to elicit plant professional opinion on the five generic factors that constitute good operator proficiency. These factors include personal, training and education, work situational, motivation and management factors. A total of 105 questionnaires were completed by plant-user. Multivariate Discriminant Analysis (MDA) was then applied to the 75 percent (25 percent as hold-out sample) of a simulated data set to derive models that would accurately classify operator characteristics into one of the three generic categories of 'good', 'average' and 'poor'. Three to five models were produced for each generic factor. These models were evaluated in order to ascertain model robustness, efficiency and validity. The most efficient and accurate models for each factor were chosen based upon performance analysis statistics. This result finding provided this study with a profile of a maintenance proficient plant operator which included the following attributes: number of years of experience as plant operator, eye-hand co-ordination, eye-hand-foot coordination, planning skills, pay, work satisfaction, operator responsibilities as defined by management, clear management policies and management pay scheme. The study further recommended that each of these derived variables should be defined and assessed to its exact nature in order to obtain proper scales and measurements for its effective application in the plant-user industry.