HOME JOURNALS CONTACT

Asian Journal of Information Technology

Classifying Plant Operator Productivity Using Computational Science
Junli Yang , David J. Edwards and P.E.D. Love

Abstract: This paper presents a conceptual model with which to classify plant operator productivity using the artificial intelligent technique, neural networks (ANN). Specially, an artificial network model is proposed that uses factors such as: operator`s motivation, management role, maintenance task taken, stress and fatigue, education and training. Within these broad ‘generic` factors, a comprehensive range of variables exist. The ANN system design proposes a feed-forward multiplayer perceptron with back-propagation algorithm that will predict three levels of operator` productivity (namely high, medium and low). It is then proposed that the maths and algorithms developed be incorporated into a web-based software solution that connects databases of information, held on a server with dual connectivity capabilities, to users using Active Server Pages (ASP) programming code. Using this approach, it is anticipated that a user-friendly package will be developed that will enable the widest possible practitioner audience to access the software, anywhere on the planet, anytime of day.

How to cite this article
Junli Yang , David J. Edwards and P.E.D. Love , 2004. Classifying Plant Operator Productivity Using Computational Science . Asian Journal of Information Technology, 3: 336-346.

© Medwell Journals. All Rights Reserved