A Study of Technical Challenges in Relocation of a Manufacturing Site

  • Guangming Zhang
  • Sameer Athalye
Part of the Massive Computing book series (MACO, volume 3)


Data mining for information gathering has become a critical part in decision-making. Manufacturers today are competing in a global market. Staying in competition calls for the fullest use of information related to design and manufacturing to assure products with high quality, low cost and on-time delivery. In this chapter, a business strategy is set forth to relocate a manufacturing site that is closer to customers and a low-cost labor market. The study presented focuses on technical challenges related to the relocating process. To secure a smooth and productive transition, efforts have been made to review the current manufacturing process and establish a new production plan system that will be in place for controlling the production of new products. Case studies are presented in the area of route sheet preparation, shop floor layout design, animation based assembly training and parametric design assistance, demonstrating the impact of data mining on the production realization process.


Data Mining Total Unit Cost Injection Molding Machine Operation Operation Data Mining Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Amirouche, Farid M.L., Computer-Aided Design and Manufacturing, Prentice Hall Publication, 1994.Google Scholar
  2. Thuraisingham, Bhavani M., Data mining: technologies, techniques, tools and trends, Boca Raton: CRC Press, 1999.zbMATHGoogle Scholar
  3. Michalski, Ryszard S., Machine Learning and Data mining: methods and applications, New York, J. Wiley, 1998.Google Scholar
  4. Beranek, John M. et al., “Automatic Generation of Assembly Sequences for Polyhedral Assemblies”, ASME Conference on Flexible Assembly, pp. 31–40, 1991.Google Scholar
  5. Chang, Tien-Chien, Richard A. Wysk and Hsu-Pin Wang. Computer Aided Manufacturing, Prentice Hall International Series in Industrial and Systems Engineering, 1991.Google Scholar
  6. Davis, James R. and Adelaide B. Davis, Effective training strategies: A comprehensive guide to maximizing learning in organizations, Berrett-Koehler Publishers, 1998.Google Scholar
  7. Famili, A. (Fazel), Dana S. Nau and Steven H. Kim, Artificial Intelligence applications in Manufacturing, AAAI Press/ MIT Press Publishing, 1994.Google Scholar
  8. Ireson, William Grant, Factoy planning and plant layout, Prentice-Hall 1982.Google Scholar
  9. Jakupec, Viktor, John Garrick, Flexible learning, human resource and organizational development: putting theory to work, Routledge, London, 2000.Google Scholar
  10. Juran, J.M. and Frank M. Gryna, Quality Planning and Analysis, Mc-Graw Hill Inc.Google Scholar
  11. Kalpakjian, Serope, Manufacturing Processes for engineering materials, Addison-Wesley Publishing, 1996.Google Scholar
  12. Marquardt, Michael J. and greg Kearsley, Technology-based learning: maximizing human performance and corporate success, St. Lucie Press, 1999.Google Scholar
  13. Rehg, James A., Computer Integrated Manufacturing, Prentice Hall Career and Technology Publishing, 1991.Google Scholar
  14. Tlusty, George, Manufacturing Processes and Equipment, Prentice Hall Publishing, 1994.Google Scholar
  15. Rosato, Dominic V. and Donald V. Rosato, Injection Molding Handbook, Van Nostrand Reinhold Publishing, 1986.Google Scholar
  16. Senker, Peter, Towards the automatic factory: the need for training, IFS Publications, 1986.Google Scholar
  17. Yokota, K. and D.R. Brough, Assembly/Disassembly Sequence Planning, Flexible Automation, pp. 31–38,Vol. 12, 1993.Google Scholar
  18. Zhang, G.M., Quality Management in Systems, The Commercial Press, Beijing, People’s Republic of China, 1998.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2001

Authors and Affiliations

  • Guangming Zhang
    • 1
  • Sameer Athalye
    • 1
  1. 1.Department of Mechanical Engineering and Institute for Systems ResearchUniversity of Maryland at College ParkUSA

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