Collaborative Forecasting Models For The Machine Tools Industry

碩士 === 東海大學 === 工業工程與經營資訊學系 === 93 === The machine tools industry is one of the ten most important industries in Taiwan. In 2004, the production value of machine tool has reached 80 billion NT dollars, and the production value has already been ranked the fifth in the world. Because of their unique c...

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Bibliographic Details
Main Authors: HSU CHUNG CHIEH, 許仲傑
Other Authors: Jen-Teng Tsai
Format: Others
Language:zh-TW
Published: 2005
Online Access:http://ndltd.ncl.edu.tw/handle/53342889832880004298
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Summary:碩士 === 東海大學 === 工業工程與經營資訊學系 === 93 === The machine tools industry is one of the ten most important industries in Taiwan. In 2004, the production value of machine tool has reached 80 billion NT dollars, and the production value has already been ranked the fifth in the world. Because of their unique characteristics, such as the long lead time of critical components, the various categories of product, few amounts of machine tools, high price of product, and the information shortage of marketing sales which was produced by agent’s sales …etc., it is hard for machine tool’s worker to process the sales forecasting. Hence, the company of machine tools always faces the problem of delaying the date of delivery, or the company must take the plan of increasing the quantities of inventory to solve the problem which we mentioned before. Since 1988, the concept of CPFR (Collaboration Planning, Forecasting, and Replenishment), proposed by VICS (Voluntary Interindustry Commerce Standards), had been introduced into many enterprises and had been provided with positive performance. The well forecasting performance is very important while the company of machine tools proceeds to CPFR process. It is one of the critical bases for decision making on the supply chain and it causes the tremendous effects for the material procurements, inventory control, as well as production management. The aims of this study are building the model with adding the factor which affected the sales quantity, providing by the agent and supplier. Then, taking a domestic company of machine tools as example, we are going to find out the appropriate method of collaborative forecasting after contrasting to the methods of Weighted Moving Averages, Exponential Smoothing, Grey Forecasting, and the Multiple Regression Model. Finally, the collaborative forecasting prototype system is developed for the company of machine tools as a consultation.