• International Journal of Precision Engineering and Manufacturing
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• 제6권3호
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• pp.19-23
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• 2005

To minimize the weld defect in manufacturing of the welded tube by using $CO_2$ laser, the monitoring of the welding quality and the seam tracking along the butt-joint lengthwise to the tube axis are studied. The longitudinal butt-joint is shaped from $60kgf/mm^2$ grade steel sheet by 2 roll bending method, and welded by the $CO_2$ laser welding system equipped with the seam tracker and plasma sensor. The laser welded tube has the thickness of 1.5mm, diameter of 105.4mm and length of 2000mm. The precise positioning of the laser beam on the butt-joint to be assembled is obtained within $200{\mu}m$ by the laser vision sensor. The artificial defects in the butt-joint are well observed by the signal of plasma intensity measured from the plasma sensor of UV wavelength range within 400nm. The developed $CO_2$ laser tube welding system has the function of the precision seam tracking and the real-time monitoring of the welding quality. In conclusion, the laser welded tube can be used for manufacturing of automobile chassis and components after hydro-forming.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.392-392
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• 2000

This study performs optimization of paper mill scheduling using MINLP(Mixed-Integer Non-Linear Programming) method and 2-step decomposing strategy. Paper mill process is normally composed of five units: paper machine, coater, rewinder, sheet cutter and roll wrapper/ream wrapper. Various kinds of papers are produced through these units. The bottleneck of this process is how to cut product papers efficiently from raw paper reel and this is called trim loss problem or cutting stock problem. As the trim must be burned or recycled through energy consumption, minimizing quantity of the trim is important. To minimize it, the trim loss problem is mathematically formulated in MINLP form of minimizing cutting patterns and trim as well as satisfying customer's elder. The MINLP form of the problem includes bilinearity causing non-linearity and non-convexity. Bilinearity is eliminated by parameterization of one variable and the MINLP form is decomposed to MILP(Mixed-Integer Linear programming) form. And the MILP problem is optimized by means of the optimization package. Thus trim loss problem is efficiently minimized by this 2-step optimization method.