Development of Model for Assembly Time Prediction of Electronic Products

Abstract

In these days, companies face fierce competition for survival in the global market. Price competitiveness is one of more important factor to survive, because every company pursues to manufacture high quality products. It is helpful to have the competitiveness that if we can predict and reduce product cost in product life cycle. Accordingly, this paper presents the model to estimate manufacturing cost in product development stage. Especially, we focused on developing assembly time prediction models to estimate assembly cost in manufacturing cost, as this model has not been covered in previous studies. The prediction models were established by neural network and regression models by considering assembly type for accurate time prediction. We can find and validate that the neural network models were superior to the regression models. Finally, real world case studies are presented on managing cost with predicted assembly cost.