Applicaion of the Neural Network in the Due-Date Assignment problems of the Wafer Factory

• Main Authors: Chen-Chia Chu, 朱震家
• Other Authors: Pei-Chann Chang
• Format: Others
• Language: zh-TW
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/09712300440119062719

碩士 === 元智大學 === 工業工程研究所 === 87 === 　　Semiconductor is a new hi-tech industry. One characteristic of hi-tech industry is the long manufacturing lead times. Although clients usually order the product half or one year before, the over-long due date assignment may make the factories and clients have financial difficulties. In the original due date assignment, a company often predicts the due date according to the product and shop condition. But in regard to the complicatedly technological processes of semiconductor industry, there are many effective factors that do not present correlation; so, the conventional due date assignment model cannot use the information of these effective factors reasonably. Therefore, this research is to develop an operative due date assignment between factories and clients for them to avoid losing unnecessarily prime costs. The research is based on dynamic shop condition to identify the factors that effect due date assignment through computer simulation and statistic analyzes, then develop a due date assignment model that is useful for semiconductor industry by way of neural network, and hope to predict practical due date validly. The first step of the research is to combine computer simulation and statistics analyzes, and use it to find out the effective factors of due date assignment. Second, establish an efficient due date assignment according to effective factors through neural network to predict the due date of semiconductor products precisely.