有限資金下多資源產能之擴充與分派--以半導體封裝測試廠為例

MULTI-RESOURCES CAPACITY EXPANSION AND ALLOCATION FOR A SEMICONDUCTOR TESTING FACILITY UNDER CONSTRAINED BUDGET

林聖修(Sheng-Hsiu Lin)

指導教授 ： 王孔政

中原大學/工學院/工業工程研究所/碩士(2001年)

https://doi.org/10.6840/cycu200100277

摘要

半島體測試產業中，顧客待測產品必須在測試機台與其他相關輔助設備可互相搭配後，才得以進行工作。鑑於現階段在有限資金下多資源產能擴充與分派問題之研究極為需要，仍待產學業界更進一步探討。另鑑於此一問題之高複雜度，本研究期望透過人工智慧方法，解決半導體測試廠中多資源產能擴充與分派問題。
本研究發展一套以基因演算法為基礎之有限資金下單資源及多資源產能擴充與分派系統雛形，以作為快速的電腦輔助決策支援工具。吾人所建構之產能擴充與分派系統，乃架構於有限資金限制下，先探討單資源限制情況後，再針對購買成本較高之測試機台與測試時所需使用送料器搭配，進行多資源問題之研究。如何在有限資金下，進行單資源與多資源限制的產能擴充與分派，除期望能決定購買機台之種類與數量，以應付顧客訂單需求外，並決定送料器資源限制如何搭配，使訂單能順利生產，其問題以獲得利潤最大化為目標。
本研究以ASP程式語言搭配SQL資料庫實作有限資金下單資源及多資源產能擴充與分派系統。並以整數規劃法所得解為參考解，與本系統所得解進行比較，單資源時直接探討不同基因演算法參數所得結果之差異；在多資源限制時，利用田口方法找出最佳參數組合，再透過確認實驗顯示參數之再現性。並以最佳組合執行後所得解與整數規劃啟發法解進行比較與分析，其結果皆與整數規劃法相當接近。

關鍵字

多資源限制 ； 晶圓封裝測試 ； 基因演算法 ； 產能規劃 ； 半導體

並列摘要

Semiconductor manufacturing and testing requires intensive capital investment. Practical experiences in this industry indicate that a few saving on capacity may result in millions of benefit per year. This paper focuses on the issues pertaining to (i) what type of and how many testers should be invested for forthcoming orders for wafer and chip of a semiconductor testing facility under budget constraint? (ii) how to allocate tester capacity for the orders so that the profit of a company can be maximized?(iii) how to allocate tester and handler capacity for the orders so that customers’ requests can be satisfied?
This research develops a genetic algorithm simultaneously to resolve the three issues. A mathematical model is constructed and its answer serves as a benchmark. We solved the single resource problem first, and then focused on multi-resources problem with testers and handlers constrain. In this research, the goal is to make the benefit maximum.
The experimental results show that the proposed algorithm is robust to the change of budgets and algorithm parameters, and the performances are close to the ones provided by the mathematical model.

並列關鍵字

Multi-resources Constrain ； Semiconductor ； Capacity expansion and allocation ； Wafer and chip testing ； Genetic Algorithm

參考文獻

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