Abstract
Industry 4.0 is known as a powerful supportive system that enterprises can enhance their competitiveness. One of critical techniques of industry 4.0 is Cyber-Physical System (CPS). CPS is a mechanism which can control or monitor physical equipment in the front end and utilize the cloud computing in the back end to achieve intelligent production or services. Although the concept of CPS has been understood by industries, how to implement CPS and accomplish the goal of enterprises remains vogue. This study utilizes the framework of CPS to achieve intelligent product design. Based on the data collected from sensors of CPS, Principal Components Analysis (PCA) is firstly employed to figure out key factors. Next, A Artificial Neural Network (ANN) method is developed to build a forecast model to identify parameters which have better yield in the backend. CPS then modify these parameters improve the yield as well as future product design. As a result, the yield issue can be solved not only in the manufacturing but also in the product design stage.