以系統模擬探討 陶瓷基板製造之派工法則

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：106

、訪客IP：3.144.244.222

姓名

黃進浩(Jin-Hao Huang) 查詢紙本館藏

畢業系所

工業管理研究所

論文名稱

以系統模擬探討陶瓷基板製造之派工法則
(Discussion of Dispatching Rules in Ceramic Substrate Manufacturing by System Simulation)

相關論文

★ 半導體化學材料銷售策略分析-以跨國B化工公司為例	★ TFT-LCD CELL製程P檢點燈不良解析流程改善之關聯法則應用
★ 金融風暴時期因應長鞭效應的策略 –以X公司為例	★ 勞動生產力目標訂定之研究-DEA 資料包絡法應用
★ 應用田口方法導入低溫超薄ITO透明導電膜於電容式觸控面板之研究	★ 多階不等效平行機台排程與訂單決策
★ 多準則決策之應用-以雷射半導體產業為例	★ 專案管理模式進行品管圈活動-以半導體機台保養測機流程改善為例
★ 應用e8D降低不合格品之效益分析-以快速消費品製造為例	★ 供應商評選模式之建構-以塑膠射出成型機製造為例
★ 應用協同規劃預測補貨於伺服器備品存貨改善之研究－以Q代工公司為例	★ 船用五金拋光作業之生產規劃
★ 以SCOR模型探討汽車安全輔助系統供應鏈-以A公司採購作業改善為例	★ 研發補助計畫執行成效評估之研究以「工業基礎技術專案計畫」為例
★ 運用生態效益發展永續之耳機產業	★ 失效模式設計審查(DRBFM)之應用-以筆記型電腦為例

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 ( 永不開放)

摘要(中)

從1970年代起，台灣開始著重於半導體產業的發展，至今，台灣的半導體產值佔了總台股的23%，根據工研院發表指出，在2004年半導體產值已經突破了新台幣一兆元，在2014年突破了新台幣兩兆元的好成績。台灣半導體產業已經發展的相當具有規模，且在全球供應鏈中，扮演了重要的角色，舉例來說，晶圓代工以及IC封裝產業為全球排名第一，IC設計為全球第二。半導體其實就是一些化合物以及元素，可經由一些特性來製造一些電路，進而解決一些較複雜的資訊問題。半導體產業鏈由三個部分組合而成，從IC設計到IC測試，分別在世界上佔有舉足輕重之地位。陶瓷基板就為半導體產業電路的一種，具有良好導熱性及耐熱性，也具有相當強的適應環境能力，所以處理程序也不盡相同，也因為這樣，作業流程相較於一般印刷電路板複雜許多，這時排程就扮演相當重要之角色。
本文以個案公司零工式生產之陶瓷機板製造進行探討，利用系統模擬建構出個案公司零工式生產之陶瓷機板製造模型，首先會先將不同訂單給予不同的權重，接著將這些資料在模擬之中運行，藉此找出個案公司主要瓶頸工作站。針對瓶頸工作站提出半導體常用的派工以及派工組合，而在其他非瓶頸工作站中，則以EDD法則進行測試。首先本文會先根據平均流程時間輸出結果選用兩種較好派工法則，接著在選用平均延遲時間以及瓶頸工作站等待時間較小之法則，最後挑選出五種派工法則，且將這五種派工法則進行排名。經過實驗結果證實，本文第一優先選擇派工為FIFO+EDD法則，而第二優先選擇派工選擇為SRPT+EDD法則。在選取FIFO+EDD法則時，能夠使得平均延遲時間以及瓶頸站平均等待時間為最好而在選取SRPT+EDD法則能夠使得平均延遲時間以及瓶頸站平均等待時間排名為二。

摘要(英)

Taiwan has focused on the development of the semiconductors manufacturing since 1970. Up to now, Output value of semiconductors manufacturing for 23% of the total Taiwan stocks. According to the Industrial Technology Research Institute statistics, the semiconductor output value has exceeded NT$1 trillion since 2004. The semiconductor output value has exceeded NT$2 trillion since 2014. Taiwanese semiconductors manufacturing has developed quite large scale and played an important role in the global supply chain. For example, wafer foundry and intergraded circuit package top of ranks in the world, and intergraded circuit design to ranks second in the world. In fact, semiconductor are chemical compositions and elements that can make electric circuit through its property can solve complicated information problems. Industry chain of semiconductors manufacturing consist of three parts. From intergraded circuit design to intergraded circuit testing play an important role in the world. Ceramic substrate is a kind of semiconductors manufacturing, which has good heat conduction, good heat tolerance and good acclimation. Owing to productive process is more complicated than Printed circuit board, scheduling needs to play an important role.
The purpose of the study discusses a study of ceramic substrate manufacturing for job shop scheduling of the case company. Using system simulation to construct a ceramic substrate manufacturing model of the case company. For one thing, different orders are given different weights, and then the data run in the system simulation. Finally, to find out the main bottleneck workstation of the case company. For the bottleneck workstation use the common dispatching rules of the semiconductors manufacturing and combination of dispatching rules while in other non-bottleneck workstations that use the EDD dispatching rules for testing. First of all, the study based on the average flow time output that select two better dispatching rules, and then based on the average tardiness time and the waiting time of the bottleneck workstation that select five better dispatching rules. Finally, Five dispatching rules are ranked. The experimental results show that the first priority of the study is FIFO+EDD dispatching rules, and the second choice is SRPT+EDD dispatching rules. FIFO+EDD dispatching rules is selected, the tardiness time and the average waiting time of the bottleneck station can rank the first, while SRPT+EDD dispatching rules is selected, the tardiness time and the average waiting time of the bottleneck station can rank the second.

關鍵字(中)

★ 派工法則
★ 系統模擬
★ 陶瓷基板製造

關鍵字(英)

★ Dispatching rules
★ System simulation
★ Ceramic substrate manufacturing

論文目次

摘要 i
Abstract ii
目錄 iv
圖目錄 vi
表目錄 vii
第一章緒論 1
1.1 研究背景與動機 1
1.2 研究目的 1
1.3 研究架構與流程 2
第二章產業介紹與研究問題 4
2.1 半導體產業介紹 4
2.2 陶瓷基板製造 7
2.3彈性零工式生產 9
2.4研究問題 10
第三章文獻探討 13
3.1排程 13
3.2排程相關文獻 18
3.3模擬相關文獻 21
第四章研究方法 23
4.1研究方法與架構 23
4.2 問題描述 23
4.3派工法則介紹 24
4.4系統模型資料設定 25
4.5 Arena模擬模型建構 31
4.6實驗設計 33
第五章實驗探討 34
5.1實驗結果與討論 34
5.2實驗結果統整 39
第六章結論與建議 45
參考文獻 46

參考文獻

1. 蕭佑和（2016）。或躍在淵，淺談台灣半導體產業今昔。
https://dahetalk.com/2016/08/05/%E6%88%96%E8%BA%8D%E5%9C%A8%E6%B7%B5%EF%BC%8C%E6%B7%BA%E8%AB%87%E5%8F%B0%E7%81%A3%E5%8D%8A%E5%B0%8E%E9%AB%94%E7%94%A2%E6%A5%AD%E4%BB%8A%E6%98%94%EF%BD%9C%E5%A4%A7%E5%92%8C%E6%9C%89%E8%A9%B1%E8%AA%AA/ （上網日期12月3日）
2. 徐宏宇（2015）。中國LED封裝陶瓷基板發展現狀。http://www.libnet.sh.cn:82/gate/big5/www.istis.sh.cn/list/list.aspx?id=9702，第一情報資訊產業。
3. 台灣陶瓷學會（2011）。LED電子領域用陶瓷基板現狀與發展分析。 http://www.tcers.org.tw/news-tw/ceramic-technology/204-led，台灣陶瓷學會：臺南市，臺灣。（上網日期12月3日）
4. 健策精密工業股份有限公司網站（2018）。陶瓷基板。http://www.tr.jentech.com.tw/ceramic-substrate，桃園市，臺灣（上網日期2018年12月9日）。
5. 富力天晟科技有限公司（2017）。陶瓷基板種類及其特性普及。 https://zhuanlan.zhihu.com/p/32003811，武漢市，中國大陸。（上網日期2018年12月9日）
6. 台灣證卷交易公司（2015）。產業價值鏈資訊平台，半導體產業鏈簡介。http://ic.tpex.org.tw/introduce.php?ic=D000&stk_code=2455，台北市，台灣。（上網日期12月8日）
7. 經濟部工業局（2018）。經濟部工業局智慧電子產業計畫推動辦公室，半導體產業現狀。https://www.sipo.org.tw/industry-overview/industry-status-quo/semiconductor-industry-status-quo.html，台北市，台灣。（上網日期12月23日）
8. 鴻揚國際興業股份有限公司（2018）。IC半導體及LED發光二極體製程應用。http://www.gextend.com/process.html，台北市，台灣。（上網日期12月15日）
9. MoneyDJ理財網（2018）。陶瓷基板。https://www.moneydj.com/KMDJ/News/NewsViewer.aspx?a=e3387a13-2b72-4a9f-afcd-a853a0bf7778 ，（上網日期12月23日）
10. 陳建良（1995），排程概述，機械工業雜誌，153 期: 122-137
11. 新加坡商森瓷科技有限公司（2018）。氮化鋁陶瓷基板。https://www.pcbshop.org/tw/supplier/product_details.asp?ProID=185&SupID=687，苗栗縣，台灣。（上網日期12月16日）
12. Bang J-Y and Kim Y-D (2011). Scheduling algorithms for a semiconductor probing facility. Computers & Operations Research 38 (3): 666-673.
13. Carlier J and Pinson E (1989). An algorithm for solving the job-shop problem. Management science 35 (2): 164-176.
14. Chan F-T-S, Chan H-K, Lau H-C-W and Ip R-W-L (2003). Analysis of dynamic dispatching rules for a flexible manufacturing system. Journal of Materials Processing Technology 138 (1-3): 325-331.
15. Chen B, Potts C-N and Woeginger G-J (1998). A review of machine scheduling: Complexity, algorithms and approximability. In Handbook of combinatorial optimization. Springer: Boston MA: 1493-1641
16. Dauzere-Peres S and Paulli J (1997). An integrated approach for modeling and solving the general multiprocessor job-shop scheduling problem using tabu search. Annals of Operations Research 70: 281-306.
17. Graham, R-L, Lawler E-L, Lenstra J-K, and Kan, A-R (1979). Optimization and approximation in deterministic sequencing and scheduling: a survey. In Annals of discrete mathematics. Elsevier 5: 287-326.
18. Hertz A and Widmer M (1996). An improved tabu search approach for solving the job shop scheduling problem with tooling constraints. Discrete Applied Mathematics 65(1-3): 319-345.
19. Heger J and Voß T (2019). Dynamic priority based dispatching of AGVs in flexible job shops. Procedia CIRP 79: 445-449.
20. Holthaus O and Rajendran C (1997). Efficient dispatching rules for scheduling in a job shop.International Journal of Production Economics 48(1): 87-105.
21. Huang K-L and Liao C-J (2008). Ant colony optimization combined with taboo search for the job shop scheduling problem.Computers & operations research 35(4): 1030-1046.
22. Jackson J-R(1957). Simulation research on job shop production. Naval Research Logistics Quarterly 4(4): 287-295.
23. Kesen S-E and Baykoc Ö-F (2007). Simulation of automated guided vehicle (AGV) systems based on just-in-time (JIT) philosophy in a job-shop environment. Simulation Modelling Practice and Theory, 15(3): 272-284.
24. Kim S, Meng C and Son Y-J (2017). Simulation-based machine shop operations scheduling system for energy cost reduction. Simulation Modelling Practice and Theory 77:68-83.
25. Loukil T, Teghem J and Fortemps P (2007). A multi-objective production scheduling case study solved by simulated annealing. European journal of operational research 179(3): 709-722.
26. Mazdeh M-M, Shashaani S, Ashouri A, and Hindi K-S (2011). Single-machine batch scheduling minimizing weighted flow times and delivery costs. Applied Mathematical Modelling 35(1): 563-570.
27. Ozguven C, Ozbakır L, and Yavuz Y (2010). Mathematical models for job-shop scheduling problems with routing and process plan flexibility. Applied Mathematical Modelling 34(6): 1539-1548.
28. Pezzella F, Morganti, G, and Ciaschetti G (2008). A genetic algorithm for the flexible job-shop scheduling problem. Computers & Operations Research 35(10): 3202-3212.
29. Sang H-Y, Duan P-Y and Li J-Q (2018). An effective invasive weed optimization algorithm for scheduling semiconductor final testing problem. Swarm and Evolutionary Computation 38: 42-53.
30. Steinhofel K, Albrecht A, and Wong C-K (1999). Two simulated annealing-based heuristics for the job shop scheduling problem. European Journal of Operational Research 118(3): 524-548.
31. Tavakkoli-Moghaddam R, and Daneshmand-Mehr M (2005). A computer simulation model for job shop scheduling problems minimizing makespan. Computers & Industrial Engineering 48(4): 811-823.
32. Vinod V and Sridharan R (2008). Dynamic job-shop scheduling with sequence-dependent setup times: simulation modeling and analysis. The International Journal of Advanced Manufacturing Technology 36(3-4): 355-372.
33. Yu X and Ram B (2006). Bio-inspired scheduling for dynamic job shops with flexible routing and sequence-dependent setups. International Journal of Production Research 44(22): 4793-4813.

指導教授

王啟泰

審核日期

2019-8-19

推文