一般而言，工廠會照著週計劃或日計劃進行生產，由於環境變化快速，如此對於突發狀況沒有辦法立即反應，可能造成訂單延誤交期的問題，降低顧客滿意度。為了防止前述的問題發生，公司會以大量的存貨來維持服務水準，如此即提高公司營運的風險。精實生產中的拉式策略對於環境變化的應變速度快，藉由Kanban向前工程傳遞領料及生產指令，可針對需求變動來調整生產量，控制存貨數量以減少不必要的浪費。
由於Information Technology (IT)的基礎日趨成熟，以往利用人工來記錄生產資料的狀況已經無法滿足現況。藉由IT技術傳遞精實拉式生產系統的Kanban指令即形成e-Kanban的應用，本研究乃執行e-Kanban系統於實際案例－半導體拉晶製程，善用生產現場及訂單資訊的電子形式，在傳遞指令時亦能夠進一步結合精實拉式系統。
本研究以精實觀點，針對案例公司拉晶製程繪製價值流圖（Value Stream Map，VSM）進行流程分析，辨識系統中浪費所在，將後補充拉式系統、順序拉式系統與混合拉式系統等設計嘗試導入案例，並考慮平行機台排程方法、機台生產限制與堝爐資源使用限制等數個決策因子。並由田口方法設計實驗，並考慮三個干擾因子，分別為晶棒重熔機率、工作負荷與訂單比例調整等，最後由田口兩階段最佳化程序求得最佳參數設計以找出最穩健（robust）的系統。由於未來系統尚不存在，故以離散事件模擬將未來模式建立後，以模擬模式進行實驗，並以模擬最佳化求解超級市場上限最佳數量配置。本論文所發展之精實拉式系統，以少量的成品庫存達到較高的服務水準（改善約6.93%）；因破除現況機台生產能力限制，雖在尺寸間互換增加換模時間，但可大幅度提高製程能力的彈性，更能快速回應顧客需求；且本研究提出之派工法則，以累積製程負荷（Cumulated，CPL）為指標，表現優於考慮等待時間（Waiting Time In Queue，WTIQ）指標與生產優先權指標（Production Priority Index）。
以e-Kanban實際執行於案例的現況為基礎，與未來精實拉式模式做敏感度分析實驗結果發現，當工作負荷大於80%時，屬於負荷較高的情況，現況與未來的系統皆有明顯下降的趨勢，但未來系統的服務水準仍能維持在95.98%~97.71%，而現況系統的服務水準則是下降至86.32%~90.85%，平均改善幅度有10%，則說明未來e-Kanban系統仍適用於工作負荷較高的環境，且即時反應的能力使得系統彈性較大。本研究導入未來e-Kanban系統除了決策資訊能夠即時傳達外，亦改變機台限制與批量大小的限制，以服務水準為主要目標，亦可被證明在環境變動的情況下，此改善方法優於現況作法，且系統較具穩健性。

In generally, factory will work according with the production planning of daily or weekly. With the environment change quickly, such a sudden incident there is no way to react immediately, and there may cause orders delay the delivery then reduce the customer satisfaction. In order to prevent the aforementioned problems, the company will hold a lot of inventory to maintain a certain service level, but that will raise the risk of the company's operation. The pull strategy of lean production will react immediately in the quickly changed environment. Transfer the with-drawal and production-ordering instruction to forward work station by kanban, it can adjust the production and control the inventory for the changes demand then reduce unnecessary waste, it doesn’t cause aforementioned problems.
Because the basis of the Information Technology (IT) matures, the use of artificial to record the status of production be unable now. The Kanban instruction passed by IT technology becomes an application of e-Kanban. The study is the implementation of e-Kanban system in a real case – the semiconductor crystal pulling manufacturing. Make the best use of the production and order information in electronic form, can also combine lean pull production system further while delivering instruction.
This research draws the value stream map of the pulling process case based on lean philosophy to analyzed the process, and identified the waste in the system, then try to implement post-replenishment pull system, sequenced-pull system, and combined pull system in the case study. Considering several decision factors as parallel machine scheduling method, machine production restrict, and the boiler service life, then designed the experience by Taguchi method, considering three noise factors as ingot re-melt probability, work load, and the proportion of the orders. Finally, using Taguchi two-stage optimization method to optimize the parameters to find the most robust system design. Because of the future system didn’t exist yet, we execute the experience by using discrete-event simulation to construct the future system, and using simulation optimization to find the optimized supermarket upper-limit amount. The lean pull system we proposed using less finished inventory to reach the better service level( improved about 6.93%). Breaking the machine restrict as the future state, system would be more flexible of the process capability by additional setup time between size changeovers, and the system would be better to response customer demand. The Cumulated Process Load(CPL) dispatching rule of the research purposed is proved better than the other dispatching index as waiting time in queue(WTIQ) and production priority index(PPI).
The results indicate that, at the workload which greater than 80%, the service level of e-Kanban system is better than the present situation, and it can be maintained from 95.98% to 97.71%, and be improved from 6.93%~11.58%. At the different level of ingot remelting rate, the service level can maintain up to 98% and can be improved by 4.97%, and the cycle time can be improved up to 74.36%. For the different proportion of orders, it can change the ratio of supermarket, and then meet with the current situation. The e-Kanban system not only transfer data real- time but also change the machine limits and the batch size limit, and can be proved that it is a good and robust system.

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