Optimizing Mixture Experiments using GMDH and Genetic Algorithm

• Main Author: 余靜芳
• Other Authors: 唐麗英
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/pz7fjy

碩士 === 國立交通大學 === 工業工程與管理系所 === 96 === In some specific areas, such as chemical or material experiments, engineers often misuse factorial design on mixture experiments. Because the responses of mixture experiments are affected by the proportional relationship among the factors (or components) rather than the quantities of the factors, the conventional designed of experiments techniques are not appropriate for the mixture experiments. Moreover, with the improvement of technology 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 utilizes Group Method of Data Handling (GMDH) and Genetic Algorithm (GA) to develop a procedure for optimizing single response and multi-response mixture experiments. Two cases from previous studies and a real case of rubber bowl production from a Taiwanese automobile company are utilized to demonstrate the effectiveness of the proposed procedure