針對封裝測試業的生產交期短，在半導體產業中，屬於受長鞭效應影響最大的，供應鏈中最末端產業，且其特性受產品應用造成景氣面，形成訂單不準確性高的特性，尤以預測模式接單，如無特殊規範與定義則有更高的不準度，本研究是藉由不同的思考模式變換想法，應用生管領域中的冰凍模式做為非預測型接單基礎建立新冰凍模式，新模式延伸冰凍區間由生產週期更動為物料準備週期，用商業模式由商業談判，來取得新模式供給方與需求方雙方對訂單冰凍區間的共識，針對冰凍區內上下調升降部分，及預期比例的幅度在封測產業內做研究，用新模式增加準確度、降低損失、增加人調配能見度，減少固定期間內訂單波動，減緩長鞭效應。
本研究依照這種變形新冰凍模式在產業的模型，諮詢產業界之資深生管專家對上下調整升降的幅度，提供意見並探討意見背後之緣由，藉由訪談結果修改此模型，達到符合產業實際狀況，獲得相對預期區間。並以運用戴明循環PDCA藉由個案"N"公司對冰凍區與融冰區，上下調升降的幅度做實務驗證，看新冰凍模式的可靠度與實際運用修正模型中區間得到最適化。
運用本研究在個案"N"公司研究實證後得到之相關結果，得到業界最真實的冰凍區與融冰區期望區間，能讓業界對此新冰凍模式接單模式能有所運用及推廣，減少原沿用預測型接單不準確性造成的傷害與損失。

Due to the high uncertainty and short cycle time of order in the assembly testing industry, Assembly and Testing is a typical industry of “Bullwhip Effect” in semiconductor. The predictive forecast order model is much higher uncertainty if without special specification and definition. This study changes the mindset with different thinking modes by applying the production planning frozen zone model in the field of production planning as a non-predictive order model. The new model, through commercial negotiation, to obtain the consensus of the new model between the supplier and the demand side on the frozen zone of the order. This study shows the proportion of the up-and-down adjustment of the frozen zone in the industry, and increases the accuracy with the new frozen zone model. It will increase visibility of head count arrangement, reduce losses and order fluctuations during a longer fixed period.
To apply the new model and frozen zone in the industry, we consulted assembly and testing senior production control experts in on the magnitude of the downward adjustment for advice. We then modified the model based on the results of the interview to obtain the range of frozen zone and slushy zone based on real situation. We also applied the derived model on company “N”, with PDCA approach, to understand the reliability of the new model and obtain the most appropriate parameters for the model.
Based on the result obtained from company "N", we pointed out the most realistic frozen zone and slushy zone area expectation interval for the industry. Furthermore, the results also support that this model can help reduce the loss caused by the inaccuracy of the forecast order.

論文審定書 i
摘 要 ii
Abstract iii
謝誌 v
目錄 vi
圖目錄 vii
表目錄 viii
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 2
第三節 研究流程 3
第四節 研究範圍與限制 4
第二章 產業現況 5
第一節 半導體產業介紹 5
第二節 封裝測試產業國內外現況 12
第三節 個案公司所在的產業專業分類族群現況 24
第三章 文獻探討 31
第一節 長鞭效應 31
第二節 冰凍模式 35
第三節 戴明循環 37
第四章 研究設計 41
第一節 研究結構 41
第二節 創建新冰凍模式 43
第三節 研究方法第一階段 44
第四節 研究方法第二階段 47
第五章 實證分析 49
第一節 證結果彙整一、質性訪談歸納分析與研究目的相對應性 49
第二節 實證結果彙整二、個案公司實證結果 56
第六章 結論與建議 58
第一節 結論 58
第二節 建議 59
第三節 管理意涵 59
參考文獻 60
附錄 訪談(調查)問卷 63

一、 中文文獻
沈如鵬（民94）。多層垂直分工產業之動態長鞭效應分析-以台灣液晶顯示器產業為研究對象。高雄：國立中山大學企業管理學系研究所碩士論文。
林世宗（民102）。企業導入平衡記分卡前後之分析。高雄：國立中山大學企業管理學系研究所碩士論文。

二、 英文文獻
Stephen N. Chapman, J.R. Tony Arnold, Ann K. Gatewood, & Lloyd M. Clive (2016). Introduction to Materials Management(8th). Pearson.
Richard B Chase, F. Robert Jacobs, & Nicholas Aquilano (2003). Operations Management for Competitive Advantage(11th). New York: McGraw Hill-Irwin.
Jose Berengueres(2007). The Tokyo Production System Re-Contextualized,74.
Lee H, Padmanabhan V, &Whang S(1997). Information Distortion in a Supply Chain: The Bullwhip Effect. Management Science,43(4), 546-558.

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