Development of intelligent quality prediction for manufacturing system

The main purpose of this research is to develop an intelligent quality prediction system. We are proposing a parameter of quality prediction module that selected 12 factors from MEPH and 16 quality evaluation factors of manufacturing system. By using back-propagation neural network method, the module is built up. The module could be used by calculating the quality evaluation from the quality factors such as material, machine, product, and staff. However, we could get the prediction of quality through the way of data fusion by the 16 quality indicators. After all, this research will test the prediction of quality by an experimentation of manufacturing system in order to prove the feasibility of the parameters and the intelligent prediction methodology.