Research on the Construction of Capability Optimization andExperimental for Injection Molding Manufacturing Process Optimization by using Six Sigma Method and TRIZ

• Main Authors: Chun-Yuan Lin, 林俊源
• Other Authors: Yung-Tsan Jou
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/856t94

碩士 === 中原大學 === 工業與系統工程研究所 === 103 === Since Industry 4.0 was initially proposed at the Hannover MESSE in Germany in 2011, the industry has transformed toward a new generation - intelligent manufacturing. On account of labor shortage in the recent years, companies have adopted a new business model where labors are replaced by machines, resulting in rapid product and service delivery. Hence, being able to improve productivity and product quality has become the new competitive advantage for companies. And what determines the competitive advantage is its Manufacturing Capability Optimization. However, one of the issues with Manufacturing Capability Optimization nowadays is the dependency on engineers’ experiences which might lead to human errors and exposure to manufacturing failure risks. By looking into product manufacturing reduction for wisdom factory and stabilization of manufacturing quality by performing flatness evaluation on real case - plastic tray, this thesis aims to address the abovementioned issue. Also, it will adopt Six Sigma and DMAIC to further address the flatness problem during the manufacturing. This thesis defines the features of injection molding manufacturing process of equipments, assesses measurement system and capabilities in manufacturing process, determines critical factors by conducting TRIZ and DOE, and eventually applies to BPN that further refines the existing Predictive Model. The result of this thesis suggests that the combination of TRIZ, DOE, and BPN is a more scientific method to better determine critical factors, and the practical implication contributes to increasing quality and providing a reference for decision making, leading to less time consumed in product manufacturing process and better product quality prediction.