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Basic Study on Wire Arc Additive Manufacturing by using Pulse GMA
Jungho Cho(조정호),Hansol Kim(김한솔),Seungcheol Shin(신승철),Hojin Yoo(유호진),Gunho Lee(이건호),Jongho Jeon(전종호) 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.11
Due to the limitation of metal 3D printing technology caused by expensive machine and metal powder cost, wire arc additive manufacturing(WAAM) technique is catching attentions of related engineers and researchers. Although the WAAM technique produces much rougher surface with much lower precision, it has advances of extremely lower cost comparing to laser based metal 3D printer and much higher productivity. Most of the WAAM technology in these days are using CMT(cold metal transfer) welding technology of Fronius company. However, it also cost a lot comparing to general GAMW(gas metal arc welding) machines. Typically saying, CMT machine cost 4-10 times higher than general GMA machine. In this research, economical WAAM technique is proposed by using general pulse GMAW machine. Through various experiments, process parameter such as welding current, welding speed, CTWD(contact tip to workpiece distance), shield gas and its flow rate are optimized to produce additive manufactured shape of metal. As a result, shallow pipe shaped structure with 105mm diameter and 100mm height with 5.5mm thickness is produced through pulse GMA machine. Comparing to usual metal 3D printer, it showed extremely higher productivity and lower cost for production.
유전자 알고리즘을 이용한 GMA 필릿 용접 비드형상 예측에 관한 연구
김영수,김일수,이지혜,정성명,이종표,박민호,Kim, Young-Su,Kim, Ill-Soo,Lee, Ji-Hye,Jung, Sung-Myoung,Lee, Jong-Pyo,Park, Min-Ho,Chand, Reenal Ritesh 대한용접접합학회 2012 대한용접·접합학회지 Vol.30 No.6
The GMA welding process involves large number of interdependent variables which may affect product quality, productivity and cost effectiveness. The relationships between process parameters for a fillet joint and bead geometry are complex because a number of process parameters are involved. To make the automated GMA welding, a method that predicts bead geometry and accomplishes the desired mechanical properties of the weldment should be developed. The developed method should also cover a wide range of material thicknesses and be applicable for all welding position. For the automatic welding system, the data must be available in the form of mathematical equations. In this study a new intelligent model with genetic algorithm has been proposed to investigate interrelationships between welding parameters and bead geometry for the automated GMA welding process. Through the developed model, the correlation between process parameters and bead geometry obtained from the actual experimental results, predicts that data did not show much of a difference, which means that it is quite suitable for the developed genetic algorithm. Progress to be able to control the process parameters in order to obtain the desired bead shape, as well as the systematic study of the genetic algorithm was developed on the basis of the data obtained through the experiments in this study can be applied. In addition, the developed genetic algorithm has the ability to predict the bead shape of the experimental results with satisfactory accuracy.
Gas Metal Arc Fillet 용접 구조물의 최적화 공정을 위한 연구
김종환(Jong-Hwan Kim) 산업기술교육훈련학회 2013 산업기술연구논문지 (JITR) Vol.18 No.2
GMA welding process is a production process to improve productivity for the provision of higher quality of material. These includs numerous process variables that could affect welding quality, productivity and cost savings. Recently, the welding part of construction equipment had frequent failure of major components in the welding part of each subsidiary material due to shock which is very poor according to the welding part. Therefore, the implementation of sound welding procedure is the most decisive factor for the reliability of construction machinery. The data generated through experimens conducted in this study has validated its effectiveness for the optimization of bead geometry and process variables is presented. The criteria to control the process parameters, to achieve a healthy bead geometry. This study has developed mathematical models and algorithms to predict or control the bead geometry in GMA fillet welding process.
A Review on Optimizations of Welding Parameters in GMA Welding Process
Ill-Soo Kim,Min-Ho Park 대한용접·접합학회 2018 대한용접·접합학회지 Vol.36 No.1
With the increase of automatic welding system employed in the manufacturing industries, the selection of optimal welding parameters must be more specific to ensure that quality is obtained. Furthermore, it is necessary to have a suitable model that establishes the interrelationship between welding parameters and bead geometry to get the desired weld ability as quality since it is a complicated process, which involves interactions of thermal, mechanical, electrical and metallurgical phenomenon. Many researchers have reported theoretical, numerical, empirical and AI models to give the optimal welding conditions for GMA(Gas Metal Arc) welding process. In addition, controlling the welding parameters plays an important role in ensuring the quality of the weld. However, there is a need to comprehensively review the GMA welding process in terms of different independent and dependent welding parameters for the purpose of modeling and optimization of GMA process. In this paper, several experimental design and optimization methodologies are reviewed and discussed with current literature on experimental design, multiple regressions analysis, the neural network, fuzzy logic, and genetic algorithm to improve the quality of weldments. This review underlines the need of development of appropriate nature inspired algorithm for the optimization of such advanced manufacturing process.
정재원,김일수,김인주,손성우,심지연,Jeong, Jae-Won,Kim, Ill-Soo,Kim, In-Ju,Son, Sung-Woo,Shim, Ji-Yeon 대한용접접합학회 2009 대한용접·접합학회지 Vol.27 No.5
Welding deformation during the assembly process is affected by not only local shrinkage due to rapid heating and cooling, but also root gap and misalignment between parts to be welded. Therefore, the prediction and control of welding deformation have become of critical importance. In this study, it was focused on the development of the 3-axis apparatus for real-time measurement of the welded deformation. To achieve the objective, a D-H algorithm has been carried out to check the behavioral and performance evaluation for the developed robot. The sequence experiments were taken the base materials of $400{\times}200{\times}4.5mm$ plate for butt welding. The real-time experimental measurements are in good agreement with the measured results.
A Study on the Real-Time Measurement of Welding Deformation
( Chang Eun Park ),( Jae Won Jeong ) 조선대학교 공학기술연구원 2009 공학기술논문지 Vol.2 No.1
Welding deformation during the assembly process is affected by not only local shrinkage due to rapid heating and cooling, but also root gap and misalignment between parts to be welded. Therefore, the prediction and control of welding deformation have become of critical importance. In this study, it was focused on the development of the 3-axis robot for real-time measurement of the welded deformation. To achieve the objective, a forward and inverse kinematics analysis using D-H algorithm has been carried out to check the behavioral and performance evaluation for the developed robot.
합성곱 신경망을 이용한 단락이행의 용접 스패터 발생량 예측
이상아,유회,서강명 대한용접접합학회 2023 대한용접·접합학회지 Vol.41 No.1
In this study, a machine learning method is proposed to predict the weld spatter generation rate, regardless of the type of short-circuit waveform. Short-circuit waveform data are collected at a high sampling rate of 10–20 kHz, and then, compressed using a new preprocessing method to effectively process the data at a high sampling rate. To predict the spatter generation rate, the welding waveform is converted into an image using the proposed data pre- processing method, and the converted data are fed into the convolutional neural network (CNN). A parametric study on data augmentation and data resolution is conducted concurrently to enhance the prediction accuracy with limited amount of data.
신경회로망을 이용한 용접잔류응력 예측 및 최적의 용접조건 선정에 관한 연구
차용훈,김하식,이연신,김덕중,성백섭 朝鮮大學校 機械技術硏究所 2000 機械技術硏究 Vol.3 No.1
The objective of the study is the development of the system for effective prediction of residual stresses using the back propagation algorithm from the neural network. The achieve of this goal, the series experiment were carried out and measured the residual stresses using sectional method. Using the experimental results, the optional control algorithms using a neural network should be developed in order to reduce than the effect of the external distribution during GMA welding processes. Also, comparison with the measured and the calculated results from the FEM(finite element method) and verification of the developed system was carried out. This system can not only help to understand the interaction between the process parameters and residual stress, but also, improve the quantity control for welded structures. Then the results obtained from this study are as follows. Through comparison between the measured and calculated results, the neural network based on back propagation algorithm is the best techniques to predict the process parameter. A new techniques which predict the process parameter such as welding voltage, arc current, welding speed using the training the raw dates, will be proposed.