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• Main Authors: Yi-Xun Weng, 翁乙薰
• Other Authors: Gwo-Ji Sheen
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/eh75r2

碩士 === 國立中央大學 === 工業管理研究所在職專班 === 102 === Current operation between ODM and OBM is, ODM will provide a flexible supply chain management operation to OBM. OBM can adjust their predicted product shipping volume once OBM foresees any change on product shipping volume. One the adjustment is to lower predicted product shipping volume, ODM will need to handle slow moving materials. It means, ODM will need to pay additional HUB storage fee/management fee. In a normal business cycle, market has its self-regulation system. When we face an abnormal business cycle, market self-regulation will be ineffective. This thesis intends to find a better solution to predict product shipping volumes under an unpredicted and abnormal business cycle. With data mining methodology, we will predict product shipping volumes with horizon view and vertical view by regression analysis model. In a horizon view, we will get a predicted product shipping volumes by other products shipping volume. In a vertical view, we will get an old-and-new product transition ratio when OBM needs to implement new generation product.