Constructing A Decision Model for Strategic Capacity Planning

碩士 === 國立清華大學 === 工業工程與工程管理學系 === 100 === DRAM makers in Taiwan started to think over again about their business model after the series of incredibly market shocks from year 2007 to 2011. They try to use their own 8-inch equipments to shift their original business model to Niche wafer foundry. But,...

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Bibliographic Details
Main Authors: Liu, Te-Chun, 劉得鈞
Other Authors: Chien, Chen-Fu
Format: Others
Language:zh-TW
Published: 2012
Online Access:http://ndltd.ncl.edu.tw/handle/25680938206944861617
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Summary:碩士 === 國立清華大學 === 工業工程與工程管理學系 === 100 === DRAM makers in Taiwan started to think over again about their business model after the series of incredibly market shocks from year 2007 to 2011. They try to use their own 8-inch equipments to shift their original business model to Niche wafer foundry. But, when it comes to be a Niche foundry player, the decision of strategic capacity plan within the ever-changing market will be a serious and important topic. This study, based on the UNISON decision framework, analyze the 3 decision elements (tendency, limitation, and decision stakeholders of the problem.) of the Niche wafer foundry industry, so as to decompose the decision problem of strategic capacity plan, and well define the boundary of this decision problem. After we clarify a set of objectives in this boundary, construct a hierarchy of objectives, we can combine a certain-model mothodology for decision-making (Analytic hierarchy process,AHP) with an uncertain one (decision tree), to creat a decision model and attributes for the strategic capacity plan. After an empirical study on this decision framework, we found this study which combines a certain decision model with an uncertain one, can bring us a bird’s eye view to review the trend of this industry, resources limitation of company, Moreover, it considered the uncertainty of market demands and prices. This study builds up a decision rule for different levels of market demand throughout a sensitivity study. It helps decision makers to make excellent decisions conditionally, and it will effectively utilize equipments and reach the goal of earning long-term, robust profits.