A Process Parameters Determination Model by Integrating Artificial Neural Network and Ant Colony Optimization

整合神經網路與螞蟻群聚最佳化的製程參數決策模式設計

10.29977/JCIIE.200507.0008

蘇純繒(Chwen-Tzeng Su)；翁瑞聰(Jui-Tsung Wong)；鄒尚峻(Shang-Chun Tsou)

螞蟻群聚最佳化 ； 類神經網路 ； 資料挖掘 ； 化學機械研磨製程 ； Ant Colony Optimization ACO ； Artificial Neural Network ANN ； Data Mining ； Chemical Machine Polishing CMP

工業工程學刊

22卷4期（2005 / 07 / 01）

346 - 354

英文

本研究主要提出一製程參數最佳化的方法。其方法以螞蟻群聚最佳化與資料挖掘為主；此外以類神經網路來做為製程模擬的技術。然而類神經網路整個建模的過程為黑箱作業，使得需靠著能見度(visibility)進行找解的螞蟻群聚最佳化，在發展演算法時會遇到瓶頸。因此，本研究目的在於以類神經網路為模擬工具下的螞蟻群聚最佳化演算架構，主要藉由資料挖掘中的決策樹來萃取出類神經網路的輸入與輸出關係，以此克服黑箱作業，藉此找出製程參數的最佳組合。最後以半導體化學機械研磨製程來進行測試。

In this paper, a methodology which integrates data mining (DM) and ant colony optimization (ACO) is proposed for process parameters determination of the chemical mechanical polishing (CMP) processes in semiconductor manufacturing. In the proposed method, an Artificial Neural Network (ANN) is first studied to realize the training process between inputs and outputs of network. However, due to the invisibility in the solution procedures of ANN, the decision tree approach of Data Mining is adopted to analyze and provide the necessary information for ACO. The simulation results demonstrated the proposed method provides an efficient tool for parameters selection for the initial CMP process.

1. Yeh. J. Y.,B. H. Huang(2003).Genetic algorithm based semiconductor manufacturing process controller for chemical mechanical planarization.Journal of the Chinese Institute of Industrial Engineers,20(6),625-635.
   連結：
2. Bauer. A.,B. Bullnheinner,R. F. Hartl,C. Strauss(1999).An Ant Colony Optimization approach for the single machine total tardiness problem.Proceedings of the 1999 Congress on Evolutionary Computation,1445-1450.
3. Bode, C. A.,B. S. Ko,T. F. Edgar.(2004).Run-to-run control and performance monitoring of overlay in semiconductor manufacturing.Control Engineering Practice,12(7),893-900.
4. Carvalho. D. R.,A. A. Freitas.(2004).A hybrid decision tree/genetic algorithm method for data mining.Information Science,163(1),13-35.
5. Del Castillo. E.,J. Y. Yeh.(1998).An adaptive run-to-run optimizing controller for linear and nonlinear semiconductor processes.IEEE Transactions on Semiconductor Manufacturing,11(2),285-295.
6. Dorigo M.,V. Maniezzo,A. Colorni(1996).Ant system: optimization by a colony of cooperating agents.IEEE Transaction on systems,26(1),29-41.
7. Dorigo, M.(1992).Optimization, learning and natural algorithms.PhD thesis, Politecnico di Milano
8. Dorigo, M.,V. Maniezzo,A. Colorni.(1997).Ant colony system: a cooperative approach to the traveling salesman problem.IEEE Transaction on Evolutionary Computation,1(1),63-66.
9. Dorigo. M.,L. M. Gambardella.(1997).Ant colonies for the traveling salesman problem.Bio Systems,43(2),73-81.
10. Kesgin. U.(2004).Genetic algorithm and artificial neural network for engine optimisation of efficiency and NOx emission.Fuel,83(7),885-895.
11. Kim. D. J.,Y. C. Kim,B. M. Kim.(2001).Optimization of the irregular shape rolling process with an artificial neural network.Journal of Materials Processing Technology,113(1),131-135.
12. Kuriakose, S.,K. Mohan,M. S. Shunmugam.(2003).Data mining applied to wire-EDM process.Journal of Materials Processing Technology,142(1),182-189.
13. Maniezzo. V.(1998).Exact and approximate nondeterministic tree-search procedures for the quadratic assignment problem.Technical Report CSR 98-I, C.L.
14. Maniezzo. V.,A. Colorni.(1999).The Ant System applied to the quadratic assignment problem.IEEE Transactions on knowledge and data engineering,11(5),769-778.
15. McMullen. P. R.(2001).An ant colony optimization approach to addressing a JIT sequencing problem with multiple objectives.Artificial Intelligence in Engineering,15(3),309-317.
16. Moyne J.,E. Del Castillo(2001).Run-to-run control manufacturing.CRC Press.
17. Qin. K.,B. Moudgil,C. W. Park.(2004).A chemical mechanical polishing model incorporating both the chemical and mechanical effects.Thin Solid Films,446(2),277-286.
18. Sohn S. Y.,T. H. Moon.(2004).Decision Tree based on data envelopment analysis for effective technology commercialization.Expert System with Applications,26(2),279-284.
19. Verikas. A.,M. Bacauskiene.(2003).Using artificial neural networks for process and system modeling.Chemometrics and Intelligent Laboratory Systems,67(2),187-191.
20. Vijayakumar. K.,G. Prabhaharan. P. Asokan,R. Saravanan.(2003).Optimization of multi-pass turning operations using ant colony system.International Journal of Machine Tools and Manufacture,43(15),1633-1639.

1. (2011).Ant colony optimization for railway driver crew scheduling: from modeling to implementation.工業工程學刊,28(6),437-449.
2. (2012).Manufacturing intelligence for early warning of key equipment excursion for advanced equipment control in semiconductor manufacturing.工業工程學刊,29(5),303-313.
3. (2012).Prediction of surface roughness in turning of PEEK cf30 by using an artificial neural network.工業工程學刊,29(5),337-347.