Optimization of Multi-response for Mixture Experiments Using PCA and DEA

• Main Authors: Tsai, Pei-Hsun, 蔡佩洵
• Other Authors: Tong, Lee-Ing
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/44519196939905505267

碩士 === 國立交通大學 === 工業工程與管理學系 === 98 === In some mixture experiments, such as chemical or material experiments, the responses of the experiments are affected by the proportional relationship among the factors (or components) rather than the quantities of the factors. Hence, the conventional design of experiments (DOE) techniques is not appropriate for the mixture experiments. Moreover, with the rapid improvement of the manufacturing technologies and the increasing demands from the consumers, product design is becoming more and more complicated. Optimization of a single response can no longer satisfy the needs of customers. Therefore, this study first utilizes Principle Components Analysis (PCA) and Data Envelopment Analysis (DEA) to integrate the multiple responses into a composite index, and then employs Group Method of Data Handling (GMDH) to develop a procedure to optimize the composite index under the restricted proportion of components. A real case of rubber bowl production from a Taiwanese automobile company is utilized to demonstrate the effectiveness of the proposed procedure.