• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.6
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• pp.49-55
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• 2008

Arc welding process is one of the most important technologies to join metal plates. Robotic welding offers the reduced manufacturing cost sought, but its widespread use demands a means of sensing and correcting for inaccuracies in the part, the fixturing and the robot. A number of problems that need to be addressed in robotic arc welding processes include sensing, joint tracking, and lack of adequate models for process parameter prediction and quality control. Problems with parameter settings and quality control occur frequently in the GMA(Gas Metal Arc) welding process due to the large number of interactive process parameters that must be set and accurately controlled. The objectives of this paper are to realize the mapping characteristics of bead width using a sensitivity analysis and develop the neural network and multiple regression method, and finally select the most accurate model in order to control the weld quality(bead width) for fillet welding. The experimental results show that the proposed neural network estimator can predict bead width with reasonable accuracy, and guarantee the uniform weld quality.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.8 s.185
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• pp.195-202
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• 2006

High-speed machining (HSM) with excellent quality and dimensional accuracy has been widely used to create 3D structures of metal and plastics. However, the high-speed machining process is not suitable for the rapid realization of 3D thin-walled product because it consumes considerably long time in fixturing process of a work piece. In this paper, an effective rapid manufacturing process is proposed to fabricate 3D thin-walled products directly using HSM, phase change filling and ultrasonic welding. The filling process is useful to hold the thin-walled product during the machining step. The ultrasonic welding process is introduced to make one piece product from two piece parts that are machined by HSM and filling process. The proposed rapid manufacturing (RM) process has been shown that the RM process enables to fabricate the 3D thin-walled products using ABS plastics and aluminum metals from 3D CAD data to functional parts.

• Transactions of the Korean Society of Mechanical Engineers
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• v.9 no.5
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• pp.590-597
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• 1985

A recursive geometric adaptive control method to compensate for machining straightness error in the finished surface due to tool deflection and guideway error generated by end milling process is developed. The relationship between the tool deflection and the feedrate is modeled by a modified Taylor's tool life equation. Without a priori knowledge on the variations off cutting parameters, time varying parameters are then estimated by an exponentially windowed recursive least squares method with only post-process measurements of the straightness error. The location error is controlled by shifting the milling bed in the direction perpendicular to the finished surface and adding a certain amount of feedrate with respect to the tool deflection model before cutting. The waviness error is compensated by adjusting the feedrate during machining. Experimental results show that location error is controlled within a range of fixturing error of the bed on the guideway and that about 60% reduction in the waviness error can be achieved within a few steps of parameter adaption under wide operating ranges of cutting conditions even if the parameters do not converge to fixed values.