Neural networks and search for minimum defectiveness in molding operation in ceramic industry

Abstract

This study is to be conducted in a ceramics production plant where the highest product defectiveness occurs in the molding shop of the plant. There are a number of factors that affect the amount of product defectiveness. The purpose is to search for a set of factor treatment conditions which provide the minimum defectiveness performance in the shop. Artificial Neural Network (ANN) method was used to realize the purpose. Based on the statistical analysis, the ANN approach is found to be reliable in predicting the amount of defectiveness that depends on various factors.