Industrial training qualitative evaluation with fuzzy logic and an experience classification method

Abstract

It is usual that companies must develop their own training processes, adaptable to their own production systems. In fact, the evaluation of the training process is a function of significant importance and must guarantee means for the identification of demands for corrective actions and for a procedure that ensures the continuous evolution of the process, therefore, that meets a dynamic of continuous improvement. The evaluation of a training process aims to provide information to support the decision making of the trainer, the process manager and other decision makers. This paper aims to propose a model of qualitative evaluation for industrial training based in fuzzy logic and a method of classification of training experiences. This training evaluation model considers the level of uncertainty that exists in qualitative responses (from trainees) and based on this, proposes a method for defining priorities for decision-making and carrying out improvement actions with the aim of evolving the training program. This action research was developed through a theoretical framework guided by the characterization of the context and the opportunity for improvement identified in this characterization, development of the model, and finally in the application of the model in an industrial training process.