基于捷徑重試規則晶圓帶式搬運系統性能優化

周炳海; 陳立揚

doi:10.13374/j.issn2095-9389.2019.02.014

基于捷徑重試規則晶圓帶式搬運系統性能優化

doi: 10.13374/j.issn2095-9389.2019.02.014

同濟大學機械與能源工程學院上海 201804

基金項目:

國家自然科學基金資助項目 71471135

詳細信息

通訊作者:
周炳海, E-mail: bhzhou@#edu.cn

中圖分類號: TP29
計量
- 文章訪問數: 1046
- HTML全文瀏覽量: 525
- PDF下載量: 14
- 被引次數: 0
出版歷程
- 收稿日期: 2017-12-30
- 刊出日期: 2019-02-01

Performance optimization of the wafer conveyor handling system using the crossover retrial rule

School of Mechanical Engineering, Tongji University, Shanghai 201804, China

More Information

Corresponding author: ZHOU Bing-hai, E-mail: bhzhou@#edu.cn

摘要

摘要: 開口管樁由于其承載力高、質量可靠、施工方便等優點得到越來越廣泛的應用.土塞的生成使得開口管樁沉樁阻力不同于閉口管樁, 不僅包括樁外側摩阻力、樁端阻力, 樁內側摩阻力亦是其重要組成部分.針對開口管樁沉樁受力特性, 采用自主研發的大尺度模型試驗裝置, 進行不同樁靴形式下開口管樁的貫入試驗, 并與閉口管樁進行對比分析.研究表明, 開口管樁隨沉樁深度的增加趨于閉塞, 沉樁阻力隨沉樁過程基本呈線性增加, 樁內、外側單位摩阻力均存在“側阻退化”效應; 樁體貫入時樁周地表隆起量隨徑向距離增加逐漸減小, 隆起速率隨沉樁深度增加逐漸變緩, 樁周土影響范圍約為5 ~ 7倍樁徑; 樁靴對開口管樁土塞生成、沉樁阻力和擠土效應均有重要影響, 內30°樁靴土塞生成高度、樁內側摩阻力及其所占總沉樁阻力比例最大, 樁周土地表隆起量最小, 外30°樁靴與內30°樁靴情況相反, 直角樁靴居中; 閉口管樁沉樁阻力、外側摩阻力與擠土程度均大于開口管樁.
- 晶圓制造 /
- 捷徑優化 /
- 自動物料搬運系統 /
- 重試排隊模型 /
- interbay系統
Abstract: The semiconductor wafer fabrication system is one of the most complex discrete manufacturing systems owing to its great number of production steps, heavy re-entry production flow, various kinds of products, etc. The automatic material handling system plays a key role in improving the production efficiency, reducing the work in process (WIP), and shortening the production cycle time of the semiconductor factory. To rapidly and effectively evaluate the impact of crossover systems on the overall performance of transport systems in wafer production, a performance analysis model was built by mathematical analysis and a decision-making method of crossovers was established. In the modeling procedure, the retrial transportation rule was first introduced. Then, considering the change in retrial rate affected by the crossovers strategy and referencing the related retrial queuing model, the mathematical expression of the expected WIP was constructed. Simultaneously, according to the cost of each crossover, the mathematical expression of the cost of crossovers was built. The optimization analysis model was obtained with the objective of minimizing the number of crossovers and WIP. Furthermore, the constraint conditions based on the length of the conveyor belt were introduced, so that the number of WIP products on each conveyor belt and crossover would not exceed the capacity limit of the conveyor belt. Finally, the NSGA-Ⅱ algorithm was used to solve the multi-objective optimization problem. The relation between the number of WIP and cost of crossovers under different logistics loads was investigated, and Pareto frontier charts were drawn up for comparative analysis. The influence of parameter settings on the objective function of the system was studied, and the solution set was classified by clustering the analysis algorithm. Based on the aboveanalysis results, the best strategy of system crossovers was summarized. By comparing the proposed system with the existing system and transportation strategy, the effectiveness of the strategy in reducing cost and WIP was confirmed.
- wafer fabrications /
- crossover-optimization /
- automatic material handling system /
- retrial queuing model /
- interbay system

HTML全文

圖 1 基于捷徑的AMHS布局圖

Figure 1. AMHS layout with crossover

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圖 2 交叉遺傳操作

Figure 2. Cross-genetic operation

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圖 3 NSGA-Ⅱ流程圖

Figure 3. Flow chart of NSGA-Ⅱ

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圖 4 不同搬運負荷下的pareto前沿

Figure 4. Pareto fronts of different handling loads

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圖 5 μ=15 s時系統的平衡性分析曲線

Figure 5. Balance analysis curve of the system of μ=15 s

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圖 6 不同寬放系數下的pareto前沿

Figure 6. Pareto fronts of different allowances

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表 1 基于重試搬運策略的AMHS與傳統AMHS的比較

Table 1. Comparison of AMHS with crossover retrial rule and traditional AMHS

μ/s	傳統AMHS		基于重試策略AMHS
μ/s	WIP	捷徑成本	WIP	捷徑成本
13	92	1834	97	1101
15	113	1834	116	1118
17	163	1834	164	1320

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表 2 μ=15 s情況下的系統各項性能指標與分類

Table 2. Performance index and classification of the system of μ=15 s

編號	捷徑使用策略	WIP	捷徑成本	SD	類別
1	1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0	116	1118	267.9829	1
2	1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0	122	1068	277.4077	1
3	1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0	125	953	303.7867	1
4	0, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0	133	779	235.0052	2
5	0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0	139	767	201.8698	2
6	0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0	142	665	219.7616	1
7	1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0	153	625	154.0412	2
8	0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0	154	573	136.7715	2
9	0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0	158	499	208.8783	1
10	0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0	171	439	136.3487	2
11	1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0	242	415	233.6606	1
12	0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0	271	229	211.319	2

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