tqm assessment in electrical substation operations using neural networks and taguchi method

The paper describes the usage of artificial neural networks and the taguchi method to assess the total quality management in an organization. the neural networks are applied to predict the defects that occur during the electrical high-voltage substation operations in the mazandaran electric company in the period of march 2019- march 2020. then, the quality of operation is carried out using l16 taguchi orthogonal arrays on four crucial questions including efforts to update knowledge, training, continuous learning, and ongoing developments of personnel, that are answered by relevant engineers. the outputs of the neural networks are used as inputs in the response of each experiment in the taguchi method. improving the quality of human resources performance is the aim of the research, so finally, it is declared that the engineers who respond to tqm questionnaires by the view extracted from the taguchi method would have a better performance than others would, and they can prevent probable defects up to 4.79 cases by proper inspection in a year.