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Data Mining using Genetic Programming for Construction of a Semiconductor Manufacturing Yield Rate Prediction System

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Abstract

The complexity of semiconductor manufacturing is increasing due to the smaller feature sizes, greater number of layers, and existing process reentry characteristics. As a result, it is difficult to manage and clarify responsibility for low yields in specific products. This paper presents a comprehensive data mining method for predicting and classifying the product yields in semiconductor manufacturing processes. A genetic programming (GP) approach, capable of constructing a yield prediction system and performing automatic discovery of the significant factors that might cause low yield, is presented. Comparison with the results then is performed using a decision tree induction algorithm. Moreover, this research illustrates the robustness and effectiveness of this method using a well-known DRAM fab’s real data set, with discussion of the results.

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References

  • M.J. Berry G. Linoff (1997) Data Mining Techniques Wiley New York

    Google Scholar 

  • C.C. Bojarczuk H.S. Lopes A.A. Freitas E.L. Michalkiewicz (2004) ArticleTitleA constrained-syntax genetic programming system for discovering classification rules. Application to medical data sets Artificial Intelligence in Medicine 30 IssueID1 27–48 Occurrence Handle10.1016/j.artmed.2003.06.001

    Article  Google Scholar 

  • D. Braha A. Shmilovici (2002) ArticleTitleData mining for improving a cleaning process in the semiconductor industry IEEE Transactions on Semiconductor Manufacturing 15 IssueID1 91–101 Occurrence Handle10.1109/66.983448

    Article  Google Scholar 

  • D. Braha (2001) Data mining for design and manufacturing: Methods and applications Kluwer Academic Boston, MA

    Google Scholar 

  • S.P. Cunningham C.J. Spanos K. Voros (1995) ArticleTitleSemiconductor yield improvement: results and best practices IEEE Transactions on Semiconductor Manufacturing 8 IssueID2 103–109 Occurrence Handle10.1109/66.382273

    Article  Google Scholar 

  • I. Falco ParticleDe A. Della Cioppa E. Tarantino (2002) ArticleTitleDiscovering interesting classification rules with genetic programming Applied Soft Computing 1 IssueID4 257–269

    Google Scholar 

  • Fayyad U., Piatetsky-Shapiro G., & Smyth P. (1996). From data mining to knowledge discovery: An overview. In Advances in knowledge discovery and data mining. Cambridge, MA: MIT Press

  • Gardner, R., Bieker, J., & Elwell, S. (2002). Solving tough semiconductor manufacturing problems using data mining. Proceedings of IEEE/SEMI Advanced Semiconductor Manufacturing Conference 46–55

  • D. Goldberg (1989) Genetic algorithms in search, optimization and machine learning Addison-Wesley Reading MA

    Google Scholar 

  • J. Han M. Kamber (2001) Data mining: concepts and techniques Morgan Kaufmann Publishers San Francisco, CA

    Google Scholar 

  • J.H. Holland (1975) Adaption in natural and artificial systems The University of Michigan Press Ann Arbor

    Google Scholar 

  • B.S. Kang J.H. Lee C.K. Shin S.J. Yu S.C. Park (1998) ArticleTitleHybrid machine learning system for integrated yield management in semiconductor manufacturing Expert Systems with Applications. 15 123–132 Occurrence Handle10.1016/S0957-4174(98)00017-7

    Article  Google Scholar 

  • J.R. Koza (1992) Genetic programming: On the programming of computers by means of natural selection The MIT Press MA

    Google Scholar 

  • Lee F. (1997). Advanced yield enhancement integrated yield analysis. Proceedings of IEEE/SEMI Advanced Semiconductor Manufacturing Conference, 67–75

  • M. Mitchell (1996) An introduction to genetic algorithms MIT Press MA

    Google Scholar 

  • T.M. Mitchell (1997) Machine Learning McGraw-Hill New York

    Google Scholar 

  • J.R. Quinlan (1986) ArticleTitleInduction of decision trees Machine Learning 1 IssueID1 81–106

    Google Scholar 

  • J.R. Quinlan (1993) C4.5: Programs for machine learning Morgan Kaufmann Publishers San Francisco, CA

    Google Scholar 

  • P. Rastogi M.N. Kozicki (1993) ArticleTitleExPro- an expert system based process management system IEEE Transaction on Semiconductor Manufacturing 6 IssueID3 207–218

    Google Scholar 

  • K.C. Tan Q. Yu C.M. Heng T.H. Lee (2003) ArticleTitleEvolutionary computing for knowledge discovery in medical diagnosis Artificial Intelligence in Medicine 27 IssueID2 129–154 Occurrence Handle10.1016/S0933-3657(03)00002-2

    Article  Google Scholar 

  • A. Teller M.P. Veloso (1996) A new learning architecture for object recognition K. Ikeuchi M. Veloso (Eds) Symbolic visual learning Oxford University Press Oxford 81–116

    Google Scholar 

  • Wong, A.Y. (1996). A statistical parametric and probe yield analysis methodology. Proceedings of the IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems, 131–139

Download references

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Correspondence to Cheng-Lung Huang.

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Received: November 2004 / Accepted: September 2005

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Li, TS., Huang, CL. & Wu, ZY. Data Mining using Genetic Programming for Construction of a Semiconductor Manufacturing Yield Rate Prediction System. J Intell Manuf 17, 355–361 (2006). https://doi.org/10.1007/s10845-005-0008-7

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  • DOI: https://doi.org/10.1007/s10845-005-0008-7

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