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An intelligent decision-support system for rough mills

Author

Listed:
  • Eman Elghoniemy
  • Ozge Uncu
  • William A. Gruver
  • Dilip B. Kotak
  • Martin Fleetwood

Abstract

A rough mill is where wood components are cut from lumber to produce wooden doors and windows. Because lumber is a natural material it contains various types of defects (e.g. knots and splits) but their distribution is not known in advance. Furthermore, only the approximate content and dimension of each board in a load are known ahead of time. Thus, producing required components from different types of lumber in a rough mill is quite a complex challenge. Several operations that occur in the rough mill are closely related and are analysed in this paper. An Intelligent Decision-Support System (IDSS) is proposed to improve the overall performance of the rough mill by presenting recommendations to operators. A rough mill simulator helps operators view the effect of these recommendations before implementing them on the production floor. Two key challenges for rough mills are identified, namely: selection of appropriate jags and cut-list scheduling and alternative solutions are proposed.

Suggested Citation

  • Eman Elghoniemy & Ozge Uncu & William A. Gruver & Dilip B. Kotak & Martin Fleetwood, 2006. "An intelligent decision-support system for rough mills," International Journal of Manufacturing Technology and Management, Inderscience Enterprises Ltd, vol. 8(1/2/3), pages 203-225.
    • Handle: RePEc:ids:ijmtma:v:8:y:2006:i:1/2/3:p:203-225
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