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研究生:戚志揚
研究生(外文):Chih Yang Chi
論文名稱:半導體製造在製品存貨動態分配及控制方法
論文名稱(外文):A Dynamic Method for WIP Allocation and Control in a Semiconductor Manufacturing System
指導教授:劉志明劉志明引用關係
指導教授(外文):Chih Ming Liu
學位類別:碩士
校院名稱:國立清華大學
系所名稱:工業工程與工程管理學系
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2006
畢業學年度:94
語文別:英文
論文頁數:51
中文關鍵詞:在製品存貨量在製品分配與控制等候理論類神經網路
外文關鍵詞:WIP QuantityWIP Allocation and ControlQueuing TheoryNeural Networks
相關次數:
  • 被引用被引用:8
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  • 下載下載:191
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本研究探討如何求得一座半導體晶圓廠最適當的在製品存貨總量及其在各工作站與作業站的最適分配方法,以維持在最大產出的情況下達到最低的晶圓製造週期時間。本研究將整廠的在製品存貨分為瓶頸在製品存貨以及非瓶頸在製品存貨兩類,瓶頸在製品存貨與晶圓廠的產出以及整體在製品存貨之間擁有極強的關聯性,因此本研究利用類神經網路從繁瑣的資料中釐清這三者之間的關係,並訂下最適當的量。其次,本研究利用等候理論來探討非瓶頸在製品存貨與晶圓製造週期時間的關係,期望能有效的分配所有的在製品存貨到個別的工作站以及對應之作業站,作為調整整體生產線平衡的基準。最後參考相關文獻中所提出的派工法(MIVS),將本研究所提出的在製品存貨水準代入MIVS中,一方面利用MIVS使晶圓廠的物料流動能維持本研究所提出的在製品存貨水準,另一方面本研究所提出的在製品存貨水準也能夠強化MIVS的效益。
本研究利用模擬法來驗證此在製品存貨水準與MIVS所帶來的效益,結果發現MIVS在套用本研究提出的最適在製品存貨水準後,在相同產出量水準下,製造週期時間的平均值較對照組提昇了16%的效益,而且沒有增加製造週期時間的變異。
The function of WIP for different workstations of a semiconductor manufacturing system is analyzed, the required total WIP level of the system is estimated by using the neural networks, and then the total number of WIP is allocated to each workstation and operation by using the queuing theory to achieve the best overall throughput performance. The resulting WIP level for each workstation is then used to control the manufacturing system. Based on the difference between the planned and the actual WIP levels of different machines, an efficient control method is then developed to maintain robustness of the system.
The simulation result shown that the proposed method for allocating total WIP to workstations and operations can reduce 16% of mean cycle time and not increase the variation of cycle time in this manufacturing system.
1.Introduction 1
1.1 Background 3
1.2. Semiconductor manufacturing system 6
1.3 Overview of this thesis 7
2.Literature review 8
2.1 Importance of WIP 8
2.2 Determination of a standard WIP level in a fab 10
2.3 WIP balance 12
2.4 Neural networks 12
2.5 Summary 14
3.A WIP allocation model based on queuing theory and neural network 15
3.1 Estimate the WIP level in a fab and bottleneck 15
3.2 Allocate the total WIP to each workstation 17
3.3 Select a dispatching rule to maintain the WIP balance 20
3.4 The architecture of this methodology 21
4.The result of the modified WIP allocation method 23
4.1 Estimate the WIP level of bottleneck workstation by BPNN 23
4.2 Estimate the WIP level in a fab by BPNN 25
4.3 Allocate WIP to non-bottleneck workstations 28
4.4 Introduce the modified WIP allocation into MIVS 28
4.6 Sensitive analysis 39
5.Conclusion and future works 46
5.1 Conclusion 46
5.2 Limitations of this study 46
5.3 Future works 47
6.References 48
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