Research of the dyeing and finishing industry quality performance forecast

• Main Authors: Chih-Feng Huang, 黃志豐
• Other Authors: Dong-Her Shih
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/84731151059399701858

碩士 === 國立雲林科技大學 === 資訊管理系碩士班 === 97 === The reason that the quality performance easy to receive neglect, the most primary factor is not easy to produce the equally easy quantification likely: today planned production how many units ? How many do the actual accomplishments produce? How many units even divide one day into: how momentarily can confirm the production efficiency? The study plans to conduct the relevant analysis using the approaches of artificial neural network (ANN) and Decision Tree (DT) Decision Tree approach is very outstanding in the fields of classification and forecasting. We can easily obtain the classification or forecasting reports through this tool. On the other hand, ANN possesses robust computing power and it has been widely applied in the fields of forecasting. In verification, this study collects the in-practice quality data and HR data to support our inference. From the results, the accuracy for both DT approach are over 80 % and ANN approach near 80%.