產銷整合之協同預測因子分析－以工具機業為例

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题名:	產銷整合之協同預測因子分析－以工具機業為例
其它题名:	An analysis of collaborative forecasting factors for the machine tools industry
作者:	吳佩勳
贡献者:	林水順;蔡禎騰 Lin,Shui-Shun;Tsai, Jen-Teng 東海大學工業工程與經營資訊學系
关键词:	協同預測;工具機業;供應鏈管理 Collaborative Forecasting;Machine Tools Industry;Supply Chain Management
日期:	2004
上传时间:	2011-05-12T06:08:39Z (UTC)
摘要:	工具機業在劇烈變化的競爭環境下，企業的快速回應與存貨壓力面臨很大的挑戰。而導入協同規劃預測與補貨策略模式將有效提升企業間供應鏈體系資訊傳遞的即時性與協調性，提高預測準確度，降低存貨成本，並加強企業內部與外部夥伴間資訊雙向即時整合，提高供應鏈流程掌握及企業應變能力。以往業者進行產銷預測時，僅考慮公司內部相關影響因子，而忽略外部合作廠商所造成的影響，且工具機業其上游關鍵零組件前置期長、獨占性強，往往造成需求預測落差，產生庫存過剩或不足的壓力，甚至無法即時滿足顧客需求。因此，本研究探討協同預測作業、工具機產業特性與供應鏈管理相關理論，歸納出影響工具機業產銷協同預測六項主因子與十四項次因子，並結合層級程序分析法，探討因子間相對重要性。結果顯示前三名為市場動態的「市場景氣指標」，產能的「前置時間」，成本的「產品成本」。此外，本研究發展一套工具機業進行協同預測的作業流程架構，並以此架構深入訪談工具機業者，推論協同預測模式可用於工具機業，但合作夥伴間信賴程度需要加強，以提高成功合作的可能性。而本研究發展的協同預測作業流程適合該產業，可供工具機業者導入時參考。 In the drastically changing and competitive environment, the machine tools industry is required to respond to the market demands rapidly. To accomplish that, the collaborative market forecasting capability is critical in the cooperation of manufactures, marketers and component providers. A good collaborative market forecasting capability will reduce the inventory, shorten the production lead time and enhance the cooperation of the participating partners. Spotlight on the machine tools industry, the key components are typically expensive and with long order lead time. Moreover, the orders from the customers are with short delivery time requirements. Thus, the manufacturer is forced to put large quantities of inventory at hand, which could be costly and inefficient. It’s crucial to have a reliable market volume forecasting system for the manufacturer taking into account the marketer and component provider’s input. As a result, this paper investigate researches related to collaborative market forecasting, characteristics of machine tools industry and supply chain management topics, then develops six main forecasting factors and 14 sub-factors that affect the market forecasting in machine tools industry. As to the importance of each factor, we apply the Analytical Hierarchical Process method to rank the importance of these factors. In addition, this paper develops a process structure of collaborative market forecasting for machine tools industry, and verify this process structure by interviewing enterprises in machine tools industry. To be brief, the process structure of collaborative market forecasting developed in this paper is suitable for machine tools industry, and could be a reference for further researches.
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