Skip to main content
SpringerLink
Log in

Process modeling, optimization and control in electronics manufacturing

  • Chapter
Manufacturing Challenges in Electronic Packaging

Abstract

In the competitive electronics market of today, yield at each manufacturing step is a key measure of success. It defines cost and is often an indicator of device quality and reliability. With the unrelenting march towards miniaturization in device designs and concomitant packaging technologies, the process-control requirements are becoming more stringent and the attainment of higher yield requires a process engineer to control variability at each of the many processing steps in the microelectronic manufacturing processes. All the variables controlling the desired output in a given process need to be understood and optimized for tighter control. In addition, the process controller must be quick and responsive to the variations in the input parameters.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • AT&T Statistical Quality Control Handbook (1984) AT&T Technologies, Inc.

    Google Scholar 

  • Bhat, N. V. and McAvoy, T. J. (1992), Determining model structure for neural models by network stripping. Computers and Chemical Engineering, 16(4), 271.

    Article  Google Scholar 

  • Butler, S. W. and Stefani, J. A. (1994) Supervisory run-to-run control of polysilicon gate etch using in-situ ellipsometry. IEEE Trans. Semiconductor Manufacturing, 7,(2), 193.

    Article  Google Scholar 

  • Collins, D. and Strojwas, A. (1990) in Automated Integrated Circuits Manufacturing, ed. V. V. Atkins, PV. 90-93. p. 66; The Electrochemical Society Softbound Proceedings Series, Pennington NJ.

    Google Scholar 

  • Coltrin, M. E., Kee, R. J. and Miller, J. A. (1984) A mathematical model of the coupled fluid mechanics and chemical kinetics in a chemical vapor deposition reactor. Journal Electrochemical Society, 131(2), 425.

    Article  Google Scholar 

  • Coltrin, M. E., Kee, R. J. and Miller, J. A. (1986) A mathematical model of silicon chemical vapor deposition: Further refinements and effects of thermal diffusion. Journal Electrochemical Society, 133(6), 1206.

    Article  Google Scholar 

  • Czogala, E. and Pedrycz, W. (1981) Some problems concerning construction of decision making in fuzzy systems. International Journal Man-Machine Studies, 15, 201.

    Article  MathSciNet  MATH  Google Scholar 

  • DeNeyer, M., Gorez, R. and Barreto, J. (1993) Fuzzy integral action in model based control systems, IEEE, p. 172.

    Google Scholar 

  • Dorf, R. C. (1986) Modern Control Systems, Addison-Westley, Reading PA.

    MATH  Google Scholar 

  • Eftychiou, M., Bergman, T. L., Masada, G. Y. (1992) Thermal effects during infrared solder flow — Part II: A model of the reflow process. ASME-Journal Electronic Packaging, 114, 48.

    Article  Google Scholar 

  • Eftychiou, M., Bergman, T. L. and Masada, G. Y. (1993) A detailed thermal model of the infrared and reflow soldering process. ASME-Journal Electronic Packaging, 115, 55.

    Article  Google Scholar 

  • Elanayar, V. T. S. and Shin, Y. C. (1992) Robust tool wear monitoring via radial basis function neural network, ASME Winter Annual Meeting, November 8-13, Anaheim CA.

    Google Scholar 

  • Eversteyn, F. C, Severin, P. J. W., Brekel, C. H. J. V. D. and Peek, H. L. (1970) A stagnation layer model for the epitaxial growth of silicon from silane in a horizontal reactor Journal Electrochemical Society, 117(7), 925.

    Article  Google Scholar 

  • Fan, H. T. and Wu, S. M. (1992) Case studies on modeling manufacturing processes using artificial neural networks, ASME Winter Annual Meeting, November 8-13, Anaheim CA.

    Google Scholar 

  • Fasser, Y. and Brettner, D. (1992) Process Improvements in the Electronics Industry, John Wiley and Sons, Inc.

    Google Scholar 

  • Fernandes, N. J., Bergman, T. L. and Masada, G. Y. (1992) Thermal effects during infrared solder reflow — Part I: Heat transfer mechanism. ASME-Journal Electronic Packaging, 114, 41.

    Article  Google Scholar 

  • Guo, R.S. and Sachs, E. (1993) Modeling, optimization and control of spatial uniformity in manufacturing processes IEEE Transactions on Semiconductor Manufacturing, 6(1), 41.

    Article  Google Scholar 

  • Han, S. S., Ceiler, M., Bidstrup, S. A., Kohl, P. and May, G. (1994) Modeling the properties of PECVD silicon dioxide films using optimized back-propagation neural networks. IEEE Transactions CPMT-Part A, 17(2), 174.

    Google Scholar 

  • Haykin, S. (1993) Neural Networks: A Comprehensive Foundation, MacMillan, New York, NY.

    Google Scholar 

  • Hill, D. (1956) Modified control limits, Applied Statistics, 5(1), 12.

    Article  Google Scholar 

  • Holmblad, L. P. and Ostergaard, J.J. (1982) Control of a cement kiln by fuzzy logic, in Fuzzy Information and Decision Processes, eds M. M. Gupta et al., North-Holland.

    Google Scholar 

  • Hornik, M., Stinchcombe, M. and White, H. (1989) Multilayer feed forward networks are universal approximators. Neural Networks, 2, 359.

    Article  Google Scholar 

  • Hotelling, H. (1947) Multivariate quality control, in Technique of Statistical Analysis, Eisenhart, Hastay and Wallis, eds, McGraw-Hill, New York.

    Google Scholar 

  • Hu, A., Sachs, E., Ingolfsson, A. and Langer, P. (1992) Run by run process control: Performance benchmarks, 1992 IEEE/SEMI Intl. Semiconductor Manufacturing Sci. Symp., p. 73.

    Google Scholar 

  • Hu, A., Zhang, X., Sachs, E. and Renteln, P. (1993) Application of run-by-run controller to the chemical-mechanical planerization process, Part I, 1993 IEEE/CHMT Int’l Electronics Manufacturing Symposium, p. 235.

    Google Scholar 

  • Huang, H. H. and Wang, H. P. (1992) Tandem artmap neural networks for feedback process control: A welding case, ASME Winter Annual Meeting, November 8-13, Anaheim CA.

    Google Scholar 

  • Irani, K. B., Cheng, J., Fayyad, U. M. and Qian, Z. (1990) Application of machine learning techniques to semiconductor manufacturing, Proceedings of the 8th SPIE Conference on Application of Artificial Intelligence, Orlando FL.

    Google Scholar 

  • Kalpakjian, S. (1992) Manufacturing Engineering and Technology, Addison and Westly Publishing Co.

    Google Scholar 

  • Kelkar, A. S., Mahajan, R. L. and Sani, R. L. (1996) Real-time physical-neural solutions for MOCVD, ASME Journal of Heat Transfer, 118, 814.

    Article  Google Scholar 

  • Kim, B. and May, G. S. (1994) An optimal neural network process model for plasma etching. IEEE Transactions on Semiconductor Manufacturing, 7(1).

    Google Scholar 

  • Lan, M. S., Lin, P. and Bain, L. J. (1992) Modeling and control of the lithographic offset color printing process using artificial neural networks, ASME Winter Annual Meeting, November 8-13, Anaheim CA.

    Google Scholar 

  • Li, Y., Mahajan, R. L. and Nikmanesh, N. (1996) Fine pitch stencil printing process meling and optimization ASME Journal Electronic Packaging, 118(1), p. 1.

    Article  Google Scholar 

  • Lucas, J. and Saccucci, M. S. (1990) Exponentially weighted moving average control schemes: Properties and enhancements. Technometrics, 32(1), p. 1.

    Article  MathSciNet  Google Scholar 

  • Mahajan, R. L. (1993) Process optimization and control in semiconductor manufacturing, Invited Paper, Proceedings ASME Winter Annual Meeting, New Orleans, November 30.

    Google Scholar 

  • Mahajan, R. L. (1996) Statistical neural network modeling for stencil printing, Proceedings, Surface Mount International Conference, San Jose CA, September 10-12, p. 573.

    Google Scholar 

  • Mahajan, R. L. (1996) Transport phenomena in chemical vapor deposition systems, Advances in Heat Transfer, 28, p. 339, Academic Press.

    Article  Google Scholar 

  • Mahajan, R. L. and Gupta, K. C. (1996) Physical-neural network modeling for electronic packaging applications, Proceedings 1996 Wireless Communications Conference, Boulder CO, p. 157.

    Google Scholar 

  • Mahajan, R. L. and Wang, X. A. (1993) Neural network models for thermally based microelectronic manufacturing processes. Journal Electrochemical Society, 140(8), p. 2287.

    Article  Google Scholar 

  • Mahajan, R. L. and Wei, C. (1991), Buoyancy, Soret, Dufour and variable property effects in silicon epitaxy. ASME-Journal of Heat Transfer, 113, 688.

    Article  Google Scholar 

  • Mahajan, R. L., Hopper, P. and Atkins, W. (1995a) Neural nets and fuzzy logic for semiconductor manufacturing; Part I: Basic concepts. Semiconductor International, July issue, p. 217.

    Google Scholar 

  • Mahajan, R. L., Hopper, P. and Atkins, W. (1995b) Neural nets and fuzzy logic for semiconductor manufacturing; Part II: Process optimization and control. Semiconductor International, August issue, p. 111.

    Google Scholar 

  • Mamdani, E. H. (1976) Advances in the linguistic synthesis of fuzzy control, International Journal of Man-Machine Studies, 8, p. 119.

    Article  Google Scholar 

  • Mamdani, E. H. (1993) Twenty years of fuzzy control: Experiences gained and lessons learned, IEEE, p. 172.

    Google Scholar 

  • Mamdani, E. H. and Assilian, S. (1975) An experiment with linguistic synthesis with a fuzzy logic controller. International Journal Man-Machine Studies, 7, p. 1.

    Article  MATH  Google Scholar 

  • Marwah, M. (1996) Neural Network Modeling Techniques for Electronics Manufacturing Processes, M. S. Thesis, University of Colorado, Boulder.

    Google Scholar 

  • Marwah, M., Li, Y. and Mahajan, R. L. (1996), Integrated neural network modeling for electronic manufacturing. Journal Electronic Manufacturing, 6(2), p.79.

    Article  Google Scholar 

  • McClelland, J. L. and Rumelhart, D. E. (1988) Parallel Distribution Processing, MIT Press, Cambridge MA.

    Google Scholar 

  • Moffat, H. and Jensen, K. F. (1988) Three-dimensional flow effects in silicon CVD in horizontal reactors. Journal Electrochemical Society, 135, p. 459.

    Article  Google Scholar 

  • Montgomery, D. C. (1991) Introduction to Statistical Quality Control, Wiley, New York NY.

    Google Scholar 

  • Mozumder, P. K. and Barna, G. D. (1994) Statistical feedback control of a plasma etch process. IEEE Transactions on Semiconductor Manufacturing, 7(1), p. 1.

    Article  Google Scholar 

  • Ostergaard, J. J. (1977) Fuzzy logic control of a heat exchanger process, in Fuzzy Automata and Decision Processes, (eds. M. M. Gupta, G. N. Saridis and B. R. Gaines), North-Holland, Amsterdam p. 285.

    Google Scholar 

  • Page, E. S. (1954) Continuous inspection schemes. Biometrica, 41, p. 100.

    MathSciNet  MATH  Google Scholar 

  • Pedrycz, W. (1988) Approximate solutions of fuzzy relational equations, Fuzzy Sets Systems, 28(2), p. 183.

    Article  MathSciNet  MATH  Google Scholar 

  • Quinlan, J. R. (1986) Induction of decision trees. Machine Learning, 1(1), p. 81, Kluwer Academic Publishers.

    Google Scholar 

  • Rangwala, S. S. and Dornfield, D. A. (1989) Learning and optimization of maching operations using computing abilities of neural networks. IEEE Transactions on Systems, Man and Cybernetics, 19(2), p. 299.

    Article  Google Scholar 

  • Reusch, B. (1993) Industrial applications of fuzzy logic in North-Rhine Westphalia, 2nd IEEE Int. Conference on Fuzzy Systems, San Francisco, March 28-April 1, 1, p. 200.

    Google Scholar 

  • Ristorcelli, J. R. Jr and Mahajan, R. L. (1987) Silicon deposition and dopant incorporation in epitaxial processes, Proceedings 2nd ASME-JSEM Thermal Engineering Joint Conference, Hawaii, March 22–27.

    Google Scholar 

  • Sachs, E., Guo, R. S., Ha, S. and Hu, A. (1991) Process control system for VLSI fabrication, IEEE Transactions on Semiconductor Manufacturing, 4(2), p. 134.

    Article  Google Scholar 

  • Shewhart, W. A. (1931) Economic Control of Quality Manufactured Products, Van Nostrand.

    Google Scholar 

  • Smith, M., (1989) Neural Networks for Statistical Modeling, Van Nostrand, Reinhold, New York, NY.

    Google Scholar 

  • Spanos, C. J. (1992) Statistical process control in semiconductor manufacturing. Proceedings of the IEEE, 80, p. 819.

    Article  Google Scholar 

  • Spanos, C. J., Guo, H. F., Miller, A. and Levine-Parrill, J. (1992), Real-time statistical process control using tool data IEEE Transactions on Semiconductor Manufacturing, 5(4), p. 308.

    Article  Google Scholar 

  • Spiegel, M. R. (1968) Mathematical Handbook, McGraw-Hill, New York NY.

    Google Scholar 

  • Subbarayan, G., Li, Y. and Mahajan, R. L. (1996) Reliability simulations for solder joint using Stochastic Finite Element and Artificial Neural Network Models. ASME-Journal Electronic Packaging, 118, p. 148.

    Article  Google Scholar 

  • Sugeno, M. (1985) Industrial Applications of Fuzzy Control, North-Holland.

    Google Scholar 

  • Sugen, M. and Kang, G. T. (1986) Fuzzy modeling and control of multilayer incinerate. Fuzzy Sets and Systems, 18, p. 329.

    Article  Google Scholar 

  • Taguchi, G. (1986) Introduction to Quality Engineering, Asian Productivity Organization, p. 181.

    Google Scholar 

  • Takagi, T. and Sugeno, M. (1985) Fuzzy identifications of systems and its applications to modeling and control. IEEE Transactions on Systems, Man and Cybernetics, SMC-15(1), p. 116.

    Article  Google Scholar 

  • Tong, R. (1978) Synthesis of fuzzy models for industrial purposes: Some recent results. International Journal General Systems, 4, p. 143.

    Article  MATH  Google Scholar 

  • Umbers, I. and King, P. (1980) An analysis of human decision making in cement kilm control and the implications for automation. International Journal General Systems, 12, p. 11.

    Google Scholar 

  • Vander Wiel, S. A., Tucker, W. T., Faltin, F. W. and Duganaksoy, N. (1992) Algorithmic statistical process control: Concepts and an application. Technometrics, 34(3), p. 286.

    Article  Google Scholar 

  • Wang, X. A. and Mahajan, R. L. (1995) CVD epitaxial deposition in a vertical barrel reactor: Process modeling and optimization using neural network models. Journal of Electrochemical Society, 142(9), p. 3123.

    Article  Google Scholar 

  • Wang, X. A. and Mahajan, R. L. (1996) Artificial neural network model-based run-to-run process controller. IEEE Transactions on CPMT-Part C, 19, p. 19.

    Google Scholar 

  • Wang, Y. C. (1993) Adaptive Fuzzy Controller, Ph.D. Dissertation, University of Colorado, Boulder, CO.

    Google Scholar 

  • Wasserman, P. D. (1989) Neural Computing: Theory and Practice, Van Nostrand Reinhold, New York NY.

    Google Scholar 

  • Xie, H., Mahajan, R. L. and Lee, Y. C. (1995) Fuzzy logic models for thermally based microelectronic manufacturing processes. IEEE Transactions on Semiconductor Manufacturing, 8(3), p. 219.

    Article  Google Scholar 

  • Xie, H., Lee, Y.C., Mahajan, R. L. and Su, R. (1994) Process optimization using a fuzzy logic response surface method. IEEE CPMT-Part A, 17(2), p.202.

    Google Scholar 

  • Zadeh, L. (1965) Fuzzy sets. Information and Control, 8, p. 338.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Authors
  1. R. L. Mahajan
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Mahajan, R.L. (1998). Process modeling, optimization and control in electronics manufacturing. In: Manufacturing Challenges in Electronic Packaging. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5803-3_5

Download citation

  • DOI: https://doi.org/10.1007/978-1-4615-5803-3_5

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-7659-0

  • Online ISBN: 978-1-4615-5803-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation