Skip to main content

Manufacturing Plant Layout Supported with Data Mining Techniques

  • Chapter

Abstract

The question of plant layout is central in a manufacturing process. This question becomes even more important in a mass customization context, when a large product diversity has to be managed. The manufacturing process, and specifically the plant layout, has to be designed taking into account this characteristic. When all products are similar, manufacturing plant layouts are relatively easy to design; difficulties come when all products are different and require specific manufacturing operations.

This paper proposes a methodology based on data mining techniques. Different steps are proposed to achieve this goal. The methodology considers:(1) identification of representative sets of products;(2) identification of representative sets of relevant manufacturing processes(for each product family);(3) categorization of new products(identification of the closest product family and the relevant layout). The focus is on data transformations that enable to extract relevant information for the manufacturing plant layout.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. B.-J. Pine II, Mass Customization, The New Frontier in Business Competition, Harvard Business School Press, Boston, Massachusetts, 1993.

    Google Scholar 

  2. B. Agard and M. Tollenaere, Méthodologie de conception des familles de produits, Journal Européen des Systèmes Automatisés 37(6), 2003, 755–777.

    Article  Google Scholar 

  3. P. Child, R. Diederichs, F.-H. Sanders and S. Wisniowski, The management of complexity, Sloan Management Review, Fall, 1991, 73–80.

    Google Scholar 

  4. E.J. Phillips, Manufacturing Plant Layout — Fundamentals and Fine Points of Optimum Facility Design, Society of Manufacturing Engineers, 1997.

    Google Scholar 

  5. A.G. Büchner, S.S. Anand and J.G. Hugues, Data mining in manufacturing environments: Goals, techniques and applications, Studies in Informatics and Control 6(4), 1997, 319– 328.

    Google Scholar 

  6. U.M. Fayyad, G. Piatetsky-Shapiro, P. Smyth and R. Uthurusamy, Advances in Knowledge Discovery and Data Mining, AAAI Press/The MIT Press, 1996.

    Google Scholar 

  7. A.J.A. Berry and G. Linoff, Data Mining Techniques: For Marketing, Sales, and Customer Support, Wiley, New York, 1997.

    Google Scholar 

  8. B. Agard and A. Kusiak, Computer Integrated Manufacturing: A Data Mining Approach, in R.C. Dorf(Ed.), The Engineering Handbook, 2nd edition, CRC Press &IEEE Press, Boca Raton, FL, 2005, pp. 192.1–192.11(Chapter 192).

    Google Scholar 

  9. R. Muther, Systematic Layout Planning, 2nd edition, CBI Publishing Company Inc., 1973.

    Google Scholar 

  10. J.M. Apple, Plant Layout and Material Handling, 3rd edition, John Wiley, New York, 1977.

    Google Scholar 

  11. J.A. Tompkins, J.A. White, Y.A. Bozer and J.M.A. Tanchoco, Facilities Planning, 3rd edition, John Wiley &Sons, 2002.

    Google Scholar 

  12. K.C. Lam, C.M. Tang and W.C. Lee, Application of the entropy technique and genetic algorithms to construction site layout planning of medium-size projects, Construction Management &Economics 23(2), 2005, 127–145.

    Article  Google Scholar 

  13. F. Karray, E. Zaneldin, T. Hegazy, A. Shabeeb and E. Elbeltagi, Computational intelligence tools for solving the facilities layout planning problem, in Proceedings of the American Control Conference, 2000, pp. 3954–3958.

    Google Scholar 

  14. Z. Li, M. Anson and G.M. Li, A procedure for quantitatively evaluating site layout alternatives, Construction Management and Economics 19, 2001, 459–467.

    Article  Google Scholar 

  15. T.D. Mavridou and P. Pardalos, Simulated annealing and genetic algorithms for the facility layout problem: A survey, Computational Optimization and Applications 7, 1997, 111–126.

    Article  MATH  MathSciNet  Google Scholar 

  16. A. Kusiak, Engineering Design: Products, Processes, and Systems, Academic Press, San Diego, CA, 1999.

    Google Scholar 

  17. A.M.A. Al-Ahmari, Part feature selection and family design in group technology using a fuzzy approach, International Journal of Computer Applications in Technology(IJCAT) 21(3), 2004.

    Google Scholar 

  18. J.R. King, Machine-component grouping in production flow analysis: An approach using a rank order clustering algorithm, International Journal of Production Research 18(2), 1980, 213–232.

    Article  Google Scholar 

  19. Z. Albadawi, H.A. Bashir and M. Chen, A mathematical approach for the formation of manufacturing cells, Comput. Ind. Eng. 48(1), 2005.

    Google Scholar 

  20. A. Kusiak, Non-traditional applications of data mining, in D. Braha(Ed.), Data Mining for Design and Manufacturing Kluwer, Boston, MA, 2001, pp. 401–416.

    Google Scholar 

  21. C. Westphal and T. Blaxton, Data Mining Solutions, John Wiley, New York, 1998.

    Google Scholar 

  22. E.S. Buffa, G.C. Armour and T.E. Vollman, Allocating facilities with CRAFT, Harvard Business Review 42(2), March/April 1964, 136–159.

    Google Scholar 

  23. C.E. Donaghey and V.F. Pire, Solving the facility layout problem with BLOCPLAN, Industrial Engineering Department, University of Houston, TX, 1990.

    Google Scholar 

  24. C. da Cunha, B. Agard and A. Kusiak, Improving manufacturing quality by re-sequencing assembly operations: A data-mining approach, in 18th International Conference on Production Research – ICPR 18, University of Salerno, Fisciamo, Italy, July 31—August 4, 2005.

    Google Scholar 

  25. B. Agard and A. Kusiak, Data mining in selection of manufacturing processes, in O. Maimon and L. Rokach(Eds.), The Data Mining and Knowledge Discovery Handbook, Springer, 2005, pp. 1159–1166.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bruno Agard .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer

About this chapter

Cite this chapter

Agard, B., Cunha, C.D. (2007). Manufacturing Plant Layout Supported with Data Mining Techniques. In: Tichkiewitch, S., Tollenaere, M., Ray, P. (eds) Advances in Integrated Design and Manufacturing in Mechanical Engineering II. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6761-7_25

Download citation

  • DOI: https://doi.org/10.1007/978-1-4020-6761-7_25

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-6760-0

  • Online ISBN: 978-1-4020-6761-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics