研究生: |
艾瑪蘇 Erma - Suryani |
---|---|
論文名稱: |
需求情境分析與產能擴充規劃:系統動態架構 Demand Scenario Analysis and Planned Capacity Expansion: a System Dynamics Framework |
指導教授: |
周碩彥
Shuo-Yan Chou |
口試委員: |
王孔政
Kung-Jeng Wang 王福琨 Fu-Kwun Wang 陳振明 Jen-Ming Chen 謝中奇 Chung-Chi Hsieh 謝光進 Kong-King Shieh 張聖麟 Sheng-lin Chang |
學位類別: |
博士 Doctor |
系所名稱: |
管理學院 - 工業管理系 Department of Industrial Management |
論文出版年: | 2010 |
畢業學年度: | 98 |
語文別: | 英文 |
論文頁數: | 103 |
中文關鍵詞: | 需求預測 、動態系統 、模擬 、容量规划 、情境 |
外文關鍵詞: | Demand forecasting, System dynamics, Simulation, Capacity planning, Scenario |
相關次數: | 點閱:737 下載:48 |
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本論文目的在於發展水泥與航空旅客需求預測之模型,該模型藉由發展出未來需求的不同情境並評估之,以達產能規劃之目的。本研究以系統動態模型來決定未來需求之情境,並且,分別基於樂觀與悲觀決策方式去預測二個案例研究的未來需求。
在第一個案例研究裡,本文建立了一個由基礎建設、國內生產毛額與投資成長率等三要主要因素之國際消費需求模型。該模型評估了二個情境,第一個情境是假設每年需求成長約7%之下,個案是否進行產能擴充計畫。第二個情境是加入考量樂觀與悲觀決策方式,去修改基礎建設、國內生產毛額與投資成長率。研究發現,如果每年需求成長7%而個案沒有擴產計畫的話,在2011年將發生產能不足。假設年需求量以7%的速率成長,且公司可多提高500萬的產能;那麼,公司將能滿足其市場需求於2017年。相對地,當經濟成長緩慢時,在2020年之前,個案即便沒有擴產也可滿足市場需求。
第二個研究案例是針對航空旅客的需求預測與產能擴充。本研究首先建立了一個測預未來航空旅客的需求模式,並進而分析各個情境之下的跑道與航廈之產能規劃。為了更健全本模型的敏感性分析,本文結合了結構性與參數性的情境以利分析。在結構性情境方面,本研究針對航空運費的因素來分析航廈內旅客流量的變化。在參數性情境方面,本研究建立樂觀與悲觀情境以預測未來的航空旅客量。研究結果發現,影響航空客運量最主要的因素包括航空運費、服務水準、國內生產毛額、人口數、每日航班數與等候時間。
The purpose of this dissertation is to develop models for demand forecasting and capacity planning (for cement and air passenger). The models were used to evaluate some scenarios related to planned capacity expansion to meet the future demand. This research is focus on using system dynamics modeling to determine the future behavior of demand. Two case studies had been utilized to forecast demand based on optimistic and pessimistic projections.
In the first study, we established a model of the national demand consumption consisting of three main drivers such as construction, GDP, and investment growths. The model is used to evaluate two scenarios. The first scenario depicted the structure scenario if demand is expected to grow around 7% annually without and with capacity expansion. The second scenario depicted the parameter scenario if we modified the value of the GDP growth, investment growth, and construction growth by considering the optimistic and pessimistic projections. We found that, if demand grows 7 % annually, without capacity expansion, there would be a shortage capacity in 2011. By expanding the capacity 5 million tonnes, with demand growth 7 % annually, the firm can cover the market demand until 2017. On the other hand, under slow growth in economic condition, with planned capacity expansion, firm can always satisfy the demand at least until 2020.
The second case study is demand forecasting and terminal capacity expansion for the air passenger. This study is used to develop a model to forecast air passenger demand and to evaluate some scenarios related to runway and passenger terminal capacity expansion to meet the future demand. We combined between structure and parameter scenarios to generate more robust sensitivity analysis. In the structure scenario, we modified the structure of airfare impact and add new structure to determine the flow of passenger in terminal building. As parameter scenario, we developed optimistic and pessimistic scenarios to predict the future of air passenger demand. We found that airfare impact, level of service impact, GDP, population, number of flights per day and dwell time play an important roles in determining the air passenger volume.
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