半導體測試廠應用派工法則之模擬研究

The simulation study of dispatching rules in a semiconductor testing factory

楊璨隆(Tsan-Long Yang)

指導教授 ： 張玉鈍

國立臺北科技大學/管理學院/工業工程與管理研究所/碩士(2008年)

https://doi.org/10.6841/NTUT.2008.00172

摘要

本研究以北台灣某半導體廠的溫度測試部門為研究對象，利用模擬方式建構模型。在溫度測試製程中，機台設置時間相當冗長，對於物料的上機測試的順序是影響生產週期時間的關鍵因素，所以本研究考量設置時間的因素發展一派工法則。針對案例公司派工法則(FIFO)及本研究發展之派工法則設計4種派工方法。並針對機台數設計兩種情境，分別為案例公司實際機台數及產能規劃分配機台數。實驗在不同情境下，以IC device子批平均生產週期時間、設置次數及設置時間為績效指標，將各派工方法與案例公司採用之派工方法1進行比較。實驗結果發現，以IC device子批平均生產週期時間績效衡量，在情境1與情境2的生產環境下，皆以派工方法3得較佳解，其改善率分別介於18.31%~45.10%及20.59%~49.97%。以設置時間為績效衡量，在情境1與情境2之生產環境下，派工方法3在各機台群組之設置時間改善比率分別介於26.18%~43.77%及34.49%~42.56%。以設置次數為績效衡量，在情境1與情境2之生產環境下，派工方法3在各機台群組之設置次數，其改善比率分別介於25.00%~41.49%及33.20%~41.26%。進一步發現應用產能規劃配置機台數也有助於改善IC device平均生產週期時間、設置次數及設置時間。

關鍵字

半導體測試 ； 同族派工 ； 派工法則 ； 模擬

並列摘要

The subject of this research is the testing department of a semiconductor company in the northern Taiwan. We use system simulation to construct our model. machine has long setup time in the temperature department. The order of testing of materials is a key point that influence the cycle time performance. To consider the factor of setup time, this study develop a dispaching rule. Bssed on FIFO dispaching rule and developed dispatching rule, We design four dispatching methods. We also design two scenarios in machine number. They are corresponding to machine number in our case company and used capacity planning calculate machine number in four machine groups. Compare the method one and the other methods used in two scenarios with performance indicator average cycle time(ACT), total setup times and total setup time.
The result shows that in scenario one and scenario two, the method three performs well. Compare method one and method three in scenario one and scenario two with ACT performance, method three performs in four machine groups in scenario one with ACT improvement rate between 18.31%~45.10% and 20.59%~49.97%. . Compare method one and method three in scenario one and scenario two with setup time performance, method three performs in four machine groups in scenario one with ACT improvement rate between 26.18%~43.77% and 34.49%~42.56%. Compare method one and method three in scenario one and scenario two with setup times performance, method three performs in four machine groups in scenario one with ACT improvement rate between 25.00%~41.49% and 33.20%~41.26%. We find that used capacity planning help reduce ACT , setup times and setup time further.

並列關鍵字

Semiconductor Testing ； family-based Dispaching Rule ； Dispaching Rule ； Simulation

參考文獻

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