| DC 欄位 |
值 |
語言 |
| DC.contributor | 工業管理研究所 | zh_TW |
| DC.creator | 盧羿君 | zh_TW |
| DC.creator | Yi-Chun Lu | en_US |
| dc.date.accessioned | 2022-7-28T07:39:07Z | |
| dc.date.available | 2022-7-28T07:39:07Z | |
| dc.date.issued | 2022 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=109456021 | |
| dc.contributor.department | 工業管理研究所 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 現今是一個強調低庫存高利潤的時代，在企業中如何平衡庫存與銷售需求的數量，一直是供應鏈的一大課題。因為台灣先天島國資源因素限制，在化工製造業生產上原料進口依賴度非常高，導致原材料上的進口需求龐大，進口庫存與實際銷售產生落差的話即會產生庫存過量或是短缺。
而2019年爆發新冠肺炎疫情後，全球運輸不穩，各國因疫情嚴峻陸續推出封城、邊境管制等政策與人力問題導致全球物料運輸中斷，而仰賴進口生存的台灣製造業因難以即時調整，導致供應鏈斷鏈長鞭效應產生。在此不穩定的狀況下，相對地增加許多物流與庫存成本，也凸顯出企業對於需求和供應的預測非常重要，因為企業不論原物料或是成品的庫存都是由訂單需求而來。
因此本研究將針對企業內部訂單需求預測的方法分析，比較移動平均法、指數平滑法、類神經網路三種預測手法的預測準確度找出適合企業訂單預測使用的工具優化預測方法，並搭配生產模式策略分析，以期將企業的存貨計畫以更有效的預測來做規劃，可以降低庫存成本和長鞭效應影響並提升供應鏈績效。
| zh_TW |
| dc.description.abstract | How to balance inventory and sales demand has always been a topic in the supply chain in target of low inventory and high profit. The chemical manufacturing industry is highly dependent on raw material imports in Taiwan due to the resource constraints of Taiwan′s congenital island.
The severity of the epidemic impacted by COVID-19 outbreak in 2019. Various countries have successively published restriction policies such as city closures and border control that global traffic status has been interrupted. Manpower issues have disrupted the movement of supplies around the world which caused supply chain’s difficulty to adjust in time resulting in a bullwhip effect. In this unstable situation, a large number of logistics and inventory costs are relatively increased, and it also highlights the importance of supply and demand forecasting for enterprises, because enterprises′ raw material or finished product inventory is based on order demand.
Therefore, this research will analyze the forecasting methods of the internal order demand of enterprises, compare the forecasting accuracy of the three forecasting methods of moving average method, exponential smoothing method, and neural network method, and find out the tool optimization forecasting method which is suitable for enterprise order forecasting. Strategic analysis to forecasting method and company′s production type with more effective model can reduce inventory costs and the impact of the bullwhip effect, and improve supply chain performance.
| en_US |
| DC.subject | 供應鏈管理 | zh_TW |
| DC.subject | 訂單需求預測 | zh_TW |
| DC.subject | 移動平均法 | zh_TW |
| DC.subject | 指數平滑法 | zh_TW |
| DC.subject | 類神經網路 | zh_TW |
| DC.subject | 存貨生產 | zh_TW |
| DC.subject | 訂單生產 | zh_TW |
| DC.subject | Supply chain management | en_US |
| DC.subject | Forecasting | en_US |
| DC.subject | Moving average method | en_US |
| DC.subject | Exponential smoothing method | en_US |
| DC.subject | Neural network | en_US |
| DC.subject | Make-to-Stock, MTS | en_US |
| DC.subject | Make-to-Order, MTO | en_US |
| DC.title | 供應鏈訂單需求預測優化與策略分析 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |