Applying SPC and Learning Curve in OEE Growth Curve

• Main Author: 杜炳龍
• Other Authors: 李文義
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/58312336047936622185

碩士 === 長庚大學 === 企業管理研究所 === 90 === The concept of total production maintenance (TPM) has been widely applied into manufacture and other industries in recent three decades. There have been many researches concerning TPM. But, most of them belong to case study or just discuss about growth of performance. No one discuss variance of growth. This study focuses on variance of growth. We integrate statistical process control (SPC) and learning curve to create an integrated process control chart. We use raw data of four factories from Japan to practice our creating model. These four models are standards to factories which are practicing TPM. You can check your growth situations. If your situations are worse than four factories from Japan, you should improve yourself. If situations are similar, you can forecast future growth and variance. Then you can avoid bad situations earlier. By the way, we use another concept, ARIMA, to construct another control model. First, we analysis raw data of four factories, then find the best ARIMA models which fit actual data. Second, we use residual to construct control chart. Finally we compare these two methods, time constant model and ARIMA model, with weakness and strength.