The Improvement and Evaluation Model for New Products'' Manufacturing System

碩士 === 元智大學 === 工業工程與管理學系 === 90 === In order to engage in the fast economic environment change and industry-wise growth, manufacturing companies must transform themselves quick enough into high profit and efficiency ones through high value-added products developing with heavy R&D efforts during...

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Bibliographic Details
Main Authors: Lu, Tsung Chieh, 呂聰傑
Other Authors: Yuan-Jye Tseng
Format: Others
Language:zh-TW
Published: 2002
Online Access:http://ndltd.ncl.edu.tw/handle/75776799426185182323
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Summary:碩士 === 元智大學 === 工業工程與管理學系 === 90 === In order to engage in the fast economic environment change and industry-wise growth, manufacturing companies must transform themselves quick enough into high profit and efficiency ones through high value-added products developing with heavy R&D efforts during new product development (NPD) processes. However, in the post R&D stage, the key concern is that how the production division can pick up the already developed technologies from R&D and implement them into the mass production stage smoothly with high throughputs and effectiveness. Due to the new products’ production systems are initially designed by R&D engineers whom without real mass production experience, there are always some problems taking place between the R&D transferring process to mass production lead-in period. As a result, the low productivity and flexibility occurred during the early mass production stage. The purpose of this research is to solve the above problems by an improved 2-phase integrated model referring as DBR scheduling and rationalizing the production processes to improve the new production system’s effectiveness. By implementing my proposed method, there will be some productivity, flexibility and quality index evaluated by system simulation, and team discussion and brainstorming. In this research, there are 2 examples applied in the integrated improvement model. After 2-phase improvement, the productivity index raised 373% and 22%, and the flexibility index raised 121.1% and 59.2% respectively; for the quality index, the yield is same as original but the product’s “no-good” probability decreased 26.5% and 19.6% respectively.