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Chan, A P C, Wong, J M W and Chiang, Y H (2003) Modelling Labour Demand at Project Level — An Empirical Study in Hong Kong. Journal of Engineering, Design and Technology, 1(02), 135–50.

Edwards, D J, Cabahug, R R and Nicholas, J (2003) The Impact of Training and Education Characteristics Upon Plant Operator Maintenance Proficiency. Journal of Engineering, Design and Technology, 1(02), 119–34.

  • Type: Journal Article
  • Keywords: construction plant; equipment maintenance; maintenance management; plant operator performance; training and education
  • ISBN/ISSN: 1726-0531
  • URL: http://www.emeraldinsight.com/10.1108/eb060893
  • Abstract:
    Hiring, selecting or assessing plant operatives' proficiency in the UK construction industry is an increasingly difficult task. A number of plant operator certification schemes are available to practitioners and each scheme trains to a myriad of bespoke standards. Consequently, the decision to employ a candidate often rests upon the employer's intuition and judgement and creates an unnecessary dilemma. To address this aforementioned problem, findings of research work that modelled plant operators' maintenance proficiency is presented. A UK nationwide survey was conducted to elicit plant professional opinion on what ‘training and educational’ (T&E) attributes constitute ‘good’ operator proficiency. The data was then arranged into three categories of operator maintenance proficiency: good, average and poor Multivariate Discriminant Analysis (MDA) was used on 75 percent of a simulated data set. The model utilised five T&E attributes, namely: duration of training provided, operator holder of alternative training card (not Certificate of Training Achievement (CTA) or Scottish/National Vocational Qualifications (S/NVQ)), operator's oral communication skills, operator's planning skills and operator's mechanical knowledge. Performance analysis revealed that model classification accuracy was 89.10 percent. The remaining 25 percent hold out sample was then modelled for validation purposes using the derived MDA model. Accuracy of the sub-sample model was high at 77.60 percent whilst a paired sample T-tests for the 75 percent and 25 percent sample data established that there was no significant statistical difference between actual and predicted classifications. Future work is proposed that aims to model other factors that influence operator maintenance proficiency; namely, work situational, motivational management and personal factors.

Ganah, A A (2003) The Use of Computer Visualisation in Communicating Constructability Information in UK. Journal of Engineering, Design and Technology, 1(02), 151–67.

Oloke, D A, Edwards, D J and Thorpe, T A (2003) Predicting Construction Plant Breakdown Time Using Time Series Modelling. Journal of Engineering, Design and Technology, 1(02), 202–21.

Oyedele, L O, Tham, K W, Jaiyeoba, B E and Fadeyi, M O (2003) Model for Predicting Architect's Performance in Building Delivery Process. Journal of Engineering, Design and Technology, 1(02), 168–86.

Trethewy, R W and Atkinson, M (2003) Enhanced Safety, Health and Environment Outcomes Through Improved Design. Journal of Engineering, Design and Technology, 1(02), 187–201.