臺灣博碩士論文加值系統

半導體產業必須持續提升技術以增加競爭力。經由技術不斷地改良與創新
可提升每片晶圓的利用率來降低產品成本。另一方面IC產品的生命週期太短，因此大部分公司都希望能夠快速地將產能轉換到新製程上生產，將所有產能投入到新製程前的這段期間，我們稱為新製程的ramp-up。然而在這段期間新製程的良率是非常不穩定且偏低，因此為了滿足客戶需求，新舊製程會同時在生產線上上線生產，新舊製程的產能分配成為公司面臨的重要議題。
本研究假設新製程的良率學習受到自我學習與實驗學習的影響，此兩因素分別受限於新製程的累積投料量與累積工程批量影響，並且假設已知新製程的生命週期，在瓶僅機台產能與滿足客戶需求下，以最大化利潤為目標，建構晶圓新、舊製程和工程的投料批量以及最適ramp-up區間的決策模式，並運用粒子群演算法求解。經由案例的敏感度分析，了解新製程的生命週期、良率學習模式參數，對新舊製程投料批量以及最適ramp-up區間之影響及其管理意涵。

Continuous improvement of process technology in a semiconductor firm is an important issue. A new production process is frequently introduced to the production line when its production process knowledge is incomplete for rapid product lifetime and expensive development cost. The period from the end of a new production process development to full capacity utilization with it to produce products is known as production ramp-up stage. During the beginning of this stage, the yield of the new production process is very unstable and low. Therefore, current production process is simultaneously existed with the new production process for meeting customer demands. The yield of a new production process is frequently improved by the accumulated production knowledge from the release lots in the production line. We call it as leaning. This creates a trade-off between the cost of production loss for low yield and the benefit of learning. In this study we formulate a mathematical model to determine the ramp-up time length , the capacity allocation for a new production process, current production process, and engineering lots during the ramp-up stage, for maximizing total profit during the life cycle of the new process. Then we propose a modified particle swarm approach to solve the problem.

摘要.....................................................i
Abstract...............................................ii
Figure Contents.........................................v
Table Contents.........................................iv
Chapter 1. Introduction.................................1
Chapter 2. Literature review............................3
2.1 Yield learning......................................3
2.2 Capacity planning...................................4
2.3 Particle swarm optimization.........................4
2.4 Features of our research............................5
Chapter 3. Problem definition...........................6
3.1 Problem statement...................................6
3.2 Assumptions.........................................7
3.3 Notations...........................................8
3.4 Problem formulations...............................10
Chapter 4. Numerical study and sensitivity analysis....14
4.1 PSO implementation.................................14
4.2 Case description...................................16
4.3 Sensitivity analysis...............................18
4.4 Managerial implications............................27
Chapter 5. Conclusions and future research.............29
References.............................................30

Chand, S., Moskowitz, H., Rekhi, I., and Sorger, G., 1996. Capacity allocation for dynamic process improvement with quality and demand. Operations Research, 44, 964-975.
Chen, T., 2009. Enhancing the yield competitiveness of a semiconductor fabrication factory with dynamic capacity re-allocation. Computers &; Industrial Engineering, 57, 931-936.
Gruber, H., 1994. The yield factor and the learning curve in semiconductor production. Applied Economics, 26, 837-843.
Hatch, N. W. and Mowery D. C., 1998. Process innovation and learning by doing in semiconductor manufacturing. Management Science, 44, 1461-1477.
Kennedy, J., and Eberhart, R. C., 1995. Particle swarm optimization. Proceedings., IEEE International Conference on Neural Networks, 1942-1948.
Mendes, R., Kennedy, J., and Neves, J., 2004. The fully informed particle swarm: Simpler, maybe better. IEEE Transactions on Evolutionary Computation, 8, 204-210.
Poli, R., Kennedy, J., and Blackwell T., 2007. Particle swarm optimization: An overview. Swarm Intelligence, 1, 33-57.
Terwiesch, C. and Bohn, R. E., 2001. Learning and process improvement during production ramp-up. International Journal Production Economics, 70, 1-19.
Wright, T.P., 1936. Factors affecting the cost of airplanes. Journal of Aeronautical Sciences, 3, 122-128.
洪正哲，「新製程導入階段新舊製程產能分配模式之建構」，國立交通大學工業工程與管理學研究所碩士論文，2011年。
陳俊穎，「Ramp-up階段新舊製程混製生產時的投料批量決策模式」，國立交通大學工業工程與管理學研究所碩士論文，2011年。