An expert system for selecting manufacturing workers for training

Abstract Intelligent real-time decision support systems are specialized domain-based tools for management. The intelligent component of decision support systems (DSS) assumes a certain level of human expertise that can be used to advise the manager on certain decision issues. In the domain of training, emphasis has been on tutoring and learning system developments. In the manufacturing industries, the problem of selecting employees for training is time consuming and belongs to a special class of multiattribute decision making. Although many manufacturing concerns have developed and implemented commendable training programs, there are still concerns of under training or overtraining based on the selection process of the employees. This paper describes a prototype knowledge-based training selection system that will identify and weight trainability factors and advise the manager on the employee trainability level. The simulation prototype, known as TSES (Trainability Selection Expert System), is a concept-driven expert system that evaluates the user subjective input data and gives some fuzzy ranking to aid management decisions. TSES behaves as a diagnostic “expert” in determining the selection and prioritizing of employee data.

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