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전광석(Kwang-Suk Chon),이희관(Jun-Hyoung kim),김준형(Hi Koan Lee),장동규(Dong-Kyu Jang),양균의(Gyun-Eui Yang) 한국자동차공학회 1996 한국자동차공학회 춘 추계 학술대회 논문집 Vol.1996 No.6_2
In cutting conditions machine tool, cutting tool and workpiece are most significant factors. Of the conditions, selection of cutting tool is related with machining technology. Semi-finish cutting removes uncut material for finish cutting not to clear large cusp after rough cutting. In spite of this advantage the cutting method is not used in field environments, since the tool selection needs machining experience. Manufacturing field uses rough cutting and finish cutting to produce parts without supporting the need in current manufacturing.<br/> The paper looks into appropriate diameter of cutting tool in rough. semi-finish, finish cutting for each objectives. Tool dimension is selected on cutting force and cutting speed in the rough cutting. on deflection of cutting tool and accuracy of surface in finish and on uncut removal in semi-finish. For semi-finish cutting the uncut after rough cutting, rough cutting can elevate efficiency of cutting and finish cutting accuracy of surface without cutting force considered.<br/>
전광석(Kwang-Suk Chon) 산업기술교육훈련학회 2020 산업기술연구논문지 (JITR) Vol.25 No.1
The current manufacturing environment is changing rapidly. Various products are being designed and manufactured using computer-aided design/computer-assisted manufacturing and computer numerical control machines. Granting cutting conditions in machining and selecting cutting tools is related to machining technology. In this study, experiments were conducted to select the appropriate length of a cutting tool for machining to obtain the optimal precision straightening surface. The correct tool length was determined relative to the tool diameter by measuring the surface roughness of the straightened machined part based on different lengths of the tool. It was found that the values of surface roughness vary depending on the length of the tool. Based on current practice, the experiments with tool length of machining confirmed that the machining surface for a short tool, which is less than 5 times the diameter, exhibited good surface roughness.
김일수,전광석,손준식,서주환,김학형,심지연,Kim, Ill-Soo,Chon, Kwang-Suk,Son, Joon-Sik,Seo, Joo-Hwan,Kim, Hak-Hyoung,Shim, Ji-Yeon 대한용접접합학회 2006 대한용접·접합학회지 Vol.24 No.5
The robotic arc welding is widely employed in the fabrication industry fer increasing productivity and enhancing product quality by its high processing speed, accuracy and repeatability. Basically, the bead geometry plays an important role in determining the mechanical properties of the weld. So that it is very important to select the process variables for obtaining optimal bead geometry. In this paper, the possibilities of the Infrared camera in sensing and control of the bead geometry in the automated welding process are presented. Both bead width and thermal images from infrared thermography are effected by process parameters. Bead width and isotherm radii can be expressed in terms of process parameters(welding current and welding speed) using mathematical equations obtained by empirical analysis using infrared camera. A linear relationship exists between the isothermal radii producted during the welding process and bead width.
손준식(Joon-Sik Son),전광석(Kwang-Suk Chon),김일수(Ill-Soo Kim),서주환(Joo-Hwan Seo),장경천(Kyeung-Cheun Jang) 한국생산제조학회 2005 한국공작기계학회 추계학술대회논문집 Vol.2005 No.-
The robotic CO₂ welding is widely employed in the fabrication industry for increasing productivity and enhancing product quality by its high processing speed, accuracy and repeatability. Reprogramming techniques have proved to be inadequate in taking into consideration of the component distortion due to heat imperfections during the welding process. Basically, the bead geometry plays an important role in determining the mechanical properties of the weld. So that it is very important to select the process variables for obtaining optimal bead geometry. However, it is difficult for the traditional identification methods to provide an accurate model because the optimized welding process is non-linear and time-dependent. In this paper, the possibilities of the Infrared camera in sensing and control of the bead geometry in the automated welding process are presented. Bead width and isotherm radii can be expressed in terms of process parameters using mathematical equations obtained by empirical analysis using infrared camera.
신경회로망과 수학적 방정식을 이용한 최적의 용입깊이 예측에 관한 연구
김일수(Kim Ill-Soo),전광석(Chon Kwang Suk) 한국공작기계학회 1999 한국공작기계학회지 Vol.8 No.5
Adaptive control in the robotic GMA(Gas Metal Arc) welding is employed to monitor the information about weld characteristics and process parameters as well as modification of those parameters to hold weld quality within the acceptable limits. Typical characteristics are the bead geometry, composition, microstructure, appearance and process parameters which govern the quality of the final weld. The main objectives of this paper are to realize the mapping characteristics of penetration through the learning. After learning, the neural network can predict the penetration desired from the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) were chosen from an error analysis. Partial-penetration, single-pass, bead-on-plate welds were fabricated in 12㎜ mild steel plates in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the penetration with reasonable accuracy and guarantee the uniform weld quality.
손준식(Joon-Sik Son),김일수(Ill-Soo Kim),유관종(Kwan-Jong Yu),전광석(Kwang-Suk Chon) 대한기계학회 2006 대한기계학회 춘추학술대회 Vol.2006 No.9
The GMA welding process involves large number of interdependent variables which may affect product quality, productivity and cost effectiveness. The relationship between process parameters for a fillet welding and bead geometry is complex because a number of process parameters are involved. To make the automated GMA welding, it is essential that a mathematical model that predicts bead geometry and accomplishes the desired mechanical properties of the weldment is developed. In this paper, an attempt has been made to develop a neural network model and two regression equations (linear and curvilinear) to predict a bead width on fillet welding and to compare the neural network model and the two regression equations in order to select an optimal prediction model.
민감도 분석을 이용한 겹치기 필릿용접의 용접변수 선정에 관한 연구
정재원,김일수,김학형,손성우,전광석 한국공작기계학회 2008 한국공작기계학회 추계학술대회논문집 Vol.2008 No.-
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 mathematical models for parameter prediction and quality control. Problems with parameter settings and quality control occur frequently in the GMA(Gas Metal Arc) welding process because of the large number of interactive 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 multiple regression method, and finally select the most accurate model in order to control the weld quality(bead reinforcement area, bead penetration area) for lap joint fillet welding.
민감도 분석을 이용한 필릿용접용 용접변수 선정에 관한 연구
정재원,김일수,김학형,손성우,김인주,전광석 한국공작기계학회 2008 한국공작기계학회 춘계학술대회논문집 Vol.2008 No.-
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 mathematical models for parameter prediction and quality control, Problems with parameter settings and quality control occur frequently in the GMA(Gas Metal Arc) welding process because of the large number of interactive 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 qua1ity(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.
GMA 용접의 윗면 비드폭 선정을 위한 최적 공정변수들
김일수,Prasad,전광석 한국공작기계학회 2002 한국생산제조학회지 Vol.11 No.4
This paper aims to develop an intelligent model for predicting top-bead width for the robotic GMA(Gas Metal Arc) welding process using BP(Back-propagation) neural network and multiple regression analysis. Firstly, based on experimental data, the basic factor affecting top-bead width are identified. Then, BP neural network model and multiple regression models of top-bead width are established. The modeling methods and procedure are explained. The developed models are then verified by data obtained from the additional experiment, and the predictive behaviors of the two kind of models are compared and analysed. Finally the modeling methods, predictive behaviors and the advantages of each models are discussed.