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Recent Research Trend of Resistance Spot Welding Quality Monitoring Technology in Korea: Young-Min Kim, Insung Hwang, Jason Cheon; J Weld Join. 2023;41(2):90-99. Published online April 30, 2023; DOI: https://doi.org/10.5781/JWJ.2023.41.2.2
Cited By 1; Full text PubReader ePub PDF

Recent Research Trend of Arc Welding Quality Monitoring Technology in Korea: Young-Min Kim, Jason Cheon; J Weld Join. 2023;41(2):81-89. Published online April 30, 2023; DOI: https://doi.org/10.5781/JWJ.2023.41.2.1; Full text PubReader ePub PDF

An Overview of Resistance Element Welding with Focus on Mechanical and Microstructure Joint and Optimization in Automotive Metal Joints: Ji Yeon Shim, Min Woo Park, Ill Soo Kim; J Weld Join. 2023;41(1):37-48. Published online February 21, 2023; DOI: https://doi.org/10.5781/JWJ.2023.41.1.4
Cited By 2; Full text PubReader ePub PDF

Analysis of Plasma Cutting Characteristics by the Vibration Signal of a Base Material: Seonmin Kim, Dae-Won Cho, Seung-Hoon Bae, Upendra Tuladhar, Sang-Hyun Ahn; J Weld Join. 2022;40(6):533-539. Published online December 30, 2022; DOI: https://doi.org/10.5781/JWJ.2022.40.6.9; Full text PubReader ePub PDF

Energy-based Beta Peak Extraction from Dynamic Resistance Curves: JaHun Ku, Youngdo Park, Namkug Ku; J Weld Join. 2022;40(5):401-409. Published online September 29, 2022; DOI: https://doi.org/10.5781/JWJ.2022.40.5.5
Cited By 1; Full text PubReader ePub PDF

Study on Effect of Process Variable on Fastening Quality Using Process Monitoring Data of Flow Drill Screwed 590DP Steel/AA5052 combination: Tae-Young Kang, Han-ju Lee, Karim Md Abdul et al.; J Weld Join. 2022;40(3):256-264. Published online June 2, 2022; DOI: https://doi.org/10.5781/JWJ.2022.40.3.7
Cited By 2; Full text PubReader ePub PDF

Study on Nugget Diameter Prediction of Resistance Spot Welding Using an Artificial Neural Network: Jongkyu Kim, JaHun Ku, Yeongdo Park et al.; J Weld Join. 2021;39(6):649-657. Published online December 6, 2021; DOI: https://doi.org/10.5781/JWJ.2021.39.6.10
Cited By 2; Full text PubReader ePub PDF

A Study on the Prediction of Real-Time Bead Width Using a DNN Algorithm in GTA Welding: Won-Bin Oh, Ill-Soo Kim, Tae-Jong Yun et al.; J Weld Join. 2020;38(6):593-601. Published online December 14, 2020; DOI: https://doi.org/10.5781/JWJ.2020.38.6.10
Cited By 6; Full text PubReader ePub PDF

Effect of Laser Power Feedback Control on Mechanical Properties of Stainless Steel Part Built by Direct Energy Deposition: ChiYen Kim, JiSung Kim, Ho Lee et al.; J Weld Join. 2020;38(2):197-202. Published online April 3, 2020; DOI: https://doi.org/10.5781/JWJ.2020.38.2.10
Cited By 3; Full text PubReader ePub PDF

Study on the Welding Mode Transition Phenomena in Monitoring Plasma-MIG Hybrid Welding: Jong Jung Lee, Young Whan Park; J Weld Join. 2017;35(3):75-81. Published online June 30, 2017; DOI: https://doi.org/10.5781/JWJ.2017.35.3.11
Cited By 1; Full text PubReader ePub PDF

A Study on Welding Process Algorithm through Real-time Current Waveform Analysis: Jin Young Yoon, Young Min Lee, Soon Cheol Shin, Hae Woon Choi; J Weld Join. 2015;33(4):24-29. Published online August 31, 2015; DOI: https://doi.org/10.5781/JWJ.2015.33.4.24
Cited By 2; PDF

Recent Trends of the Material Processing Technology with Laser - ICALEO 2014 Review -: Mokyoung Lee; J Weld Join. 2015;33(4):7-16. Published online August 31, 2015; DOI: https://doi.org/10.5781/JWJ.2015.33.4.7; PDF

A Study on Correlationship between the Induced Plasma and Emission Signals for In-process Monitoring in Stainless Steel Welding of Fiber Laser (Ⅱ) - Properties Changes of the Measured Signals in a Thick Plate Welding -: Chang-Je Lee, Jong-Do Kim; J Weld Join. 2014;32(6):606-610. Published online December 31, 2014; DOI: https://doi.org/10.5781/JWJ.2014.32.6.70
Cited By 1; PDF

A Study on Correlationship between the Induced Plasma and Emission Signals for In-process Monitoring in Stainless Steel Welding of Fiber Laser (Ⅰ) - Properties Changes of the Measured Signals in a Thin Plate Welding -: Chang-Je Lee, Jong-Do Kim; J Weld Join. 2014;32(6):600-605. Published online December 31, 2014; DOI: https://doi.org/10.5781/JWJ.2014.32.6.64; PDF

Defect Detection in Friction Stir Welding by Online Infrared Thermography: Igor Kryukov, Michael Hartmann, Stefan Böhm, Malte Mund, Klaus Dilger, Fabian Fischer; J Weld Join. 2014;32(5):480-487. Published online October 30, 2014; DOI: https://doi.org/10.5781/JWJ.2014.32.5.50
Cited By 2; PDF

Volume 41, No. 5

Journal of
Welding and
Joining

Print ISSN: 2466-2232
Online ISSN: 2466-2100

MOST VIEWED MOST CITED

6,383	Review on the Recent Welding Research with Application of CNN-Based Deep Learning Part I: Models and Applications
5,774	Growth Behavior of Intermetallic Compounds in Various Solder Joints Induced by Electromigration
4,581	Study on Laser Welding of Al-Cu Dissimilar Material by Green Laser and Weld Quality Evaluation by Deep Learning
4,274	Modeling of Laser Welds Using Machine Learning Algorithm Part I: Penetration Depth for Laser Overlap Al/Cu Dissimilar Metal Welds
4,237	Solidification Cracking Susceptibility of the Weld Metal of Additively Manufactured 316L Stainless Steel

Cited By 16	Review on the Recent Welding Research with Application of CNN-Based Deep Learning Part I: Models and Applications
Cited By 13	Solidification Cracking Susceptibility of the Weld Metal of Additively Manufactured 316L Stainless Steel
Cited By 13	Evaluating the Welding Pulses of Various Tool Profiles in Single-Pass Friction Stir Welding of 6082-T6 Aluminium Alloy
Cited By 10	Review on the Recent Welding Research with Application of CNN-Based Deep Learning Part II: Model Evaluation and Visualizations
Cited By 10	Modeling of Laser Welds Using Machine Learning Algorithm Part II: Geometry and Mechanical Behaviors of Laser Overlap Welded High Strength Steel Sheets

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