• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 1999.08a
• /
• pp.438-446
• /
• 1999

Crop minimization of the top and bottom ends of hot rolled plate, in a plate, in a plate mill, has been investigated. The existing model to determine the edging pattern at the finishing rolling pass was not reasonable to get high width accuracy and rolling yields. New models including width prediction have been formulated by using neural network model of back propagation learning algorithm and statistical analysis based on the actual production rolling data to give the optimal pattern for minimizing trimming loss. Using these models, at a given rolling condition of broadside pass and finishing pass and the permissible condition of width variation, it was possible to minimize crip at the top and bottom ends according to optimum procedure in plate mill. An application to improve the plan view pattern reduced width variation by 23% and crop length by 30% on average with an effective fishtail crop shape.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.4
• /
• pp.296-303
• /
• 2007

This paper proposes a new width control system composed of an ANWC(Automatic Neural network based Width Control) and a fuzzy-PID controller in hot strip finishing mills which aims at obtaining the desirable width. The ANWC is designed using a neural network based width prediction model to minimize a width variation between the measured width and its target value. Input variables for the neural network model are chosen by using the hypothesis testing. The fuzzy-PlD control system is also designed to obtain the fast looper response and the high width control precision in the finishing mill. It is shown through the field test of the Pohang no. 1 hot strip mill of POSCO that the performance of the width margin is considerably improved by the proposed control schemes.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2004.05a
• /
• pp.70-73
• /
• 2004

The approach in this thesis is for prediction of deformed strip profile in hot rolling mill. This approach shows how to make an expression as a mathematical form in predicting strip profile. This approach is based on the velocity field, shear stress and material flow on the strip edge along width direction and lateral displacement and stress along width are analytically calculated. Roll force is calculated in each section and then combined together to show roll force distribution along width. All the assumptions to make equation form for this approach are supported by FEM simulation result and the result of model is verified by FEM result. So, this model will supply very useful tool to the researcher and engineers which takes less time and has similar accuracy in predicting roll force profile comparing to FEM simulation. This model has to be combined with deformed roll profile model, which include thermal crown prediction and wear prediction model to predict deformed strip profile.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2007.05a
• /
• pp.223-225
• /
• 2007

Online models predicting roll force and forward slip of roughing mill was developed using nondimensional parameters. Using the effective inlet thickness, roll force model take into account the effect of inlet dog-bone shape of slab which take places after width reduction through edger rolling in roughing mill. The prediction accuracy of the proposed model is examined through comparison with measurements.

• Journal of computational fluids engineering
• /
• v.13 no.1
• /
• pp.1-6
• /
• 2008

Direct Write Technologies are being utilized in various industrial fields such as antennas, engineered structures, sensors and tissue engineering. With Direct Write Technologies, producing features have the mesoscale range, from 1 to 100 microns. One form of the Direct Write Technologies is based on aerosol dynamics. The shape of deposited aerosols determine the form of products in the Direct Write Technology based on aerosol dynamics. To predict shape of deposited aerosol, a prediction model is created. In this study, we estimated Line-Width and Line-Thickness from the prediction model. Results of prediction model is valid from comparison with experimental results.

• Transactions of Materials Processing
• /
• v.25 no.4
• /
• pp.235-241
• /
• 2016

Dimensional accuracy of hot coil is improved by precise control of thickness profiles, flatness, width and winding profile. Especially, precise width control is important because yield could be increased significantly. Precise width control can be improved by predicting the amount of width spread. The purpose of this study is to develop the advanced prediction model for width spread in hot finish rolling for controlling width precisely. FE-simulations were performed to investigate the effect of process variables on width spread such as reduction ratio, forward and backward tension and initial width at each stand. From the statistical analysis of simulated data, advanced model was developed based on the existing models for strip width spread. The experimental hot rolling trials showed that newly developed model provided fairly accurate predictions on the strip width spread during the whole hot finishing rolling process.

• Proceedings of the KWS Conference
• /
• 2006.10a
• /
• pp.271-273
• /
• 2006

This paper focuses on the developed empirical models for the prediction on top-bead width in GMA(Gas Metal Arc) welding process. Three empirical models have been developed: linear, curvilinear and an intelligent model. Regression analysis was employed fur optimization of the coefficients of linear and curvilinear model, while Genetic Algorithm(GA) was utilized to estimate the coefficients of intelligent model. Not only the fitting of these models were checked, but also the prediction on top-bead width was carried out. ANOVA analysis and contour plots were respectively employed to represent main and interaction effects between process parameters on top-bead width.

• Journal of Korean Institute of Industrial Engineers
• /
• v.31 no.4
• /
• pp.334-340
• /
• 2005

A mouse is an important input device that is used in most of all computer works. A mouse control time prediction model was proposed in this study. Especially, the model described the time of mouse control that made a cursor to move within path constraints. The model was developed by a laboratory experiment. Cursor movement times were measured in 36 task conditions; 3 levels of path length, 3 levels of path width and 4 levels of target's width. 12 subjects participated in all conditions. The time of cursor movement with path constraints could be better explained by the combination of Fitts' law with steering law($r^2=0.947$) than by the other models; Fitts' law($r^2=0.740$), Steering law($r^2=0.633$) and Crossman's model($r^2=0.897$). The proposed model is expected to be used in menu design or computer game design.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.7
• /
• pp.1841-1857
• /
• 2023

CenterNet, a novel object detection algorithm without anchor based on key points, regards the object as a single center point for prediction and directly regresses the object's height and width. However, because the objects have different sizes, directly regressing their height and width will make the model difficult to converge and lose the intrinsic relationship between object's width and height, thereby reducing the stability of the model and the consistency of prediction accuracy. For this problem, we proposed an algorithm based on the regression of the diagonal half-length and the center angle, which significantly compresses the solution space of the regression components and enhances the intrinsic relationship between the decoded components. First, encode the object's width and height into the diagonal half-length and the center angle, where the center angle is the angle between the diagonal and the vertical centreline. Secondly, the predicted diagonal half-length and center angle are decoded into two length components. Finally, the position of the object bounding box can be accurately obtained by combining the corresponding center point coordinates. Experiments show that, when using CenterNet as the improved baseline and resnet50 as the Backbone, the improved model achieved 81.6% and 79.7% mAP on the VOC 2007 and 2012 test sets, respectively. When using Hourglass-104 as the Backbone, the improved model achieved 43.3% mAP on the COCO 2017 test sets. Compared with CenterNet, the improved model has a faster convergence rate and significantly improved the stability and prediction accuracy.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 1999.08a
• /
• pp.429-437
• /
• 1999

Width variation of the top and bottom ends of steel at finishing rolling in a plate, has been investigated. It was found that width variation after finishing rolling is affected by edging, broadside rolling ratio, longitudinal rolling ratio, width shape after broadside rolling, temperature, width-to-thickness ratio, and so on. A neural network modelling of back propagation has been conducted on the width variation during rolling. Based on these prediction models, a width control system, by which the roll opening and closing of the hydraulic AWC edger can be adjusted during edge rolling in finishing rolling passes, has been developed. Compared to conventional width model, the neural network model is much accurate in a model. The width control system is applied to a newly built production mill.