{"title":"Investigation and multi-objective optimization of friction stir welding of AA7075-T651 plates","authors":"Vaibhav S. Gaikwad, S. Chinchanikar, Omkar Manav","doi":"10.1080/09507116.2023.2177568","DOIUrl":"https://doi.org/10.1080/09507116.2023.2177568","url":null,"abstract":"Abstract The present study investigates and comparatively evaluates different evolutionary algorithms for multi-objective optimization of friction stir welding (FSW) of AA7075-T651 plates. The FSW parameters are optimized for obtaining the joint with higher tensile strength, microhardness and lower surface roughness using particle swarm optimization, strength Pareto-based evolutionary algorithm II, differential evolution and teaching learning-based optimization techniques. The validation experiments showed better prediction accuracy with the SPEA II technique. This study finds maximum tensile strength and microhardness of 187.45 MPa and 142.47 HV, respectively, and minimum surface roughness of 15.93 µm for FSW joint when using a welding speed and tool rotation, of 40 mm/min and 1923 rpm, respectively. The FSW joint obtained at these optimized parameters showed the homogeneous material mixing with the equiaxed fine-grain distribution at the weld nugget with fewer voids, as confirmed by the scanning electron microscopic images with energy-dispersive X-ray spectroscopic analysis.","PeriodicalId":23605,"journal":{"name":"Welding International","volume":"37 1","pages":"68 - 78"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48283825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Performance of ANN in predicting the depth to width ratio and tensile strength of UNS S32750 laser weld joints","authors":"S. Saravanan, K. Kumararaja","doi":"10.1080/09507116.2023.2191805","DOIUrl":"https://doi.org/10.1080/09507116.2023.2191805","url":null,"abstract":"Abstract The effectiveness of the pulsed mode laser weld joint is characterized by the supply of optical energy to the interface. The laser welding process parameters, such as laser power, pulse duration, travel speed and focus, determine the efficacy of the weld, which is defined by full penetration and free of pores and defects. However, expressing the relationship between various process parameters and mechanical strength is intricate due to the prevalence of non-linear relationship. The development of computational approaches aids in optimizing the laser welding parameters and reducing trial and error. Hence, the artificial neural network (ANN) model is developed, in a python environment, to predict the optimum process parameter values for a desirable depth to width ratio and maximum tensile strength of UNS S32750 laser butt weld joints. The developed model was assessed by experiments, not utilized for training. The ANN model predicts the depth to width ratio and tensile strength of the weld joints with an accuracy of 90% and less than 10% divergence from the experimental result. Furthermore, for the process, parametric conditions are: (power: 550 W, focus: –1 mm, pulse duration: 13 Hz and travel speed: 136 mm/min) to attain maximum tensile strength.","PeriodicalId":23605,"journal":{"name":"Welding International","volume":"37 1","pages":"111 - 117"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44306219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Huy Huu Ho, Hao Dinh Duong, Quan Minh Nguyen, Tra Hung Tran
{"title":"Mechanical performance of dissimilar friction stir welded lap-joint between aluminium alloy 6061 and 316 stainless steel","authors":"Huy Huu Ho, Hao Dinh Duong, Quan Minh Nguyen, Tra Hung Tran","doi":"10.1080/09507116.2023.2190475","DOIUrl":"https://doi.org/10.1080/09507116.2023.2190475","url":null,"abstract":"Abstract The dissimilar lap-joint of the AA6061 to 316 stainless steel was produced by friction stir welding. Changing microstructure, joint interface, and mechanical performances via welding rate were revealed. A wave interface pattern was found at the low welding rate with a free oxide layer. The interface became flat at the high welding rate with the oxide film formation. The diffusion and intermetallic compounds (IMCs) layers were formed on the interface and their thickness decreased via increasing the welding rate. The highest joint strength was obtained at the welding rate of 75 mm/min but strongly reduced with growing the welding rate. The strength was dramatically correlated with the bonding area, diffusion thickness and interface morphology instead of the IMCs layer thickness. At the low welding rate, the joint was fractured via ductile behaviour with a lot of dimples found on the fracture surface of 316 stainless steel.","PeriodicalId":23605,"journal":{"name":"Welding International","volume":"37 1","pages":"101 - 110"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44725787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effect of heat input on mechanical and metallurgical properties of AISI 304L stainless steel by using TIG welding","authors":"Angshuman Roy, N. Ghosh, S. Mondal","doi":"10.1080/09507116.2023.2185169","DOIUrl":"https://doi.org/10.1080/09507116.2023.2185169","url":null,"abstract":"Abstract In this research, we examine the ways in which heat treatment affects TIG-welded joints made from austenitic AISI 304 L stainless steel. TIG welding was performed on austenitic 304 L stainless steel at low (0.57 KJ/mm), medium (0.63 KJ/mm), and high (0.69 KJ/mm) heat. TIG welding was used to join together AISI 304 L stainless steel samples here. A consistent 3 mm thick plates were taken for the joints. All of the joints were butt-welded. In order to conduct tensile tests, hardness tests, and microstructural analyses, samples were cut and machined to the appropriate dimensions. Once the joints are ready, visual inspection and X-rays were conducted. This study examined the effects of applying different levels of heat on AISI 304 L stainless steel butt joints. The material’s tensile properties were tested and analysed after being butt-joined. Welded samples’ microstructures were examined with a Leica DM LM metallurgical microscope. Consistent with the microstructural characteristics, the tensile test findings were also consistent. The research found that compared to joints prepared with low and high heat input, those prepared with medium heat input exhibited greater tensile strength, percentage elongation and micro hardness value.","PeriodicalId":23605,"journal":{"name":"Welding International","volume":"37 1","pages":"91 - 100"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41877855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Investigating the effect of residual stresses and distortion of laser welded joints for automobile chassis and optimizing weld parameters using random forest based grey wolf optimizer","authors":"Sanjay S. Surwase, S. Bhosle","doi":"10.1080/09507116.2023.2174915","DOIUrl":"https://doi.org/10.1080/09507116.2023.2174915","url":null,"abstract":"Abstract The present investigation analyses the selection of the right welding method and joint and advanced testing methods (NDT) for highly durable automotive frames. Moreover, the present investigation analysis suggests the best machine learning (ML) algorithm for selecting the best weld method and optimal solution. The experiment was performed based on the response surface methodology (RSM) based design of the experimental approach. As a result, laser beam welding (LBM) and cross joint are the significant weld methods for automotive frames. The proposed ML algorithm successfully optimized the LBM input parameters as laser power = 1277 W, welding speed (WS) = 32.2 mm/s, focal point: 1 mm and working angle = 0.14 Rad with an average error of approximately 0.033. Based on the results, the optimum output weld parameters are bead width = 4322.7 µm, penetration depth (PD) = 3157.9 µm, total strain = 0.0098 mm/mm and residual stress = 645.2340 MPa, respectively.","PeriodicalId":23605,"journal":{"name":"Welding International","volume":"37 1","pages":"46 - 67"},"PeriodicalIF":0.0,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45113051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Microstructural and wear properties of mild steel cladded with AISI 316L stainless steel using pulsed current gas metal arc welding process","authors":"Mani Jayavelu, Srinivasan Kasi, Balasubramanian Visvalingam, Prasanna Nagasai Bellamkonda, Malarvizhi Sudersanan","doi":"10.1080/09507116.2023.2169085","DOIUrl":"https://doi.org/10.1080/09507116.2023.2169085","url":null,"abstract":"Abstract The main objective of this study is to study the microstructure and wear resistance of mild steel (MS) of grade IS 2062 that has had an austenitic stainless steel (AISI 316L) coating applied utilizing the pulsed current gas metal arc welding (PC-GMAW) technique. The PC-GMAW method was used to overcome issues with the conventional gas metal arc welding (CC-GMAW) method used for cladding AISI 316L steel over mild steel, such as a larger heat affected zone (HAZ), coarse-grained deposited weld metal microstructure, less penetration depth and higher dilution and reinforcement height. Optical microscopy (OM) was used to examine the microstructural characteristics of the clad region. Using the pin-on-disc testing machine, the wear rate of cladded specimens was recorded, and scanning electron microscopy (SEM) was used to examine the morphology of wear surfaces. The microhardness distribution of the cladded region was examined, and the wear characteristics of the cladded specimens were correlated. According to the findings, PC-GMAW cladding is harder and more resistant to wear than a mild steel substrate. The PC-GMAW cladding exhibited higher weld metal deposition and lower dilution. Weld overlay hardness was 15.83% higher in the PC-GMAW cladding than in the mild steel substrate. The wear rate was decreased by an average of 20.18% as compared to the mild steel substrate with PC-GMAW cladding.","PeriodicalId":23605,"journal":{"name":"Welding International","volume":"37 1","pages":"34 - 45"},"PeriodicalIF":0.0,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43924520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vishwath Ramachandran, Susan Elias, B. Narayanan, Ayyappan Uma Chandra Thilagam, Niyanth Sridharann
{"title":"Multi-class semantic segmentation for identification of silicate island defects","authors":"Vishwath Ramachandran, Susan Elias, B. Narayanan, Ayyappan Uma Chandra Thilagam, Niyanth Sridharann","doi":"10.1080/09507116.2022.2163937","DOIUrl":"https://doi.org/10.1080/09507116.2022.2163937","url":null,"abstract":"Abstract In the automotive industry, it is necessary to identify the edge and center silicate island weld defects formed during Gas metal arc welding. These inspections of the weld are typically performed manually by visually inspecting the weld and identifying regions where the defect concentration is greater than a set threshold. Such a system is prone to errors and can be time-consuming. A novel deep-learning neural network is required to meet the industry’s demand for high-quality welded products. To achieve this, a deep learning U-Net model for multi-class semantic segmentation was designed. The model was trained with a dataset of less than a hundred images and can achieve over 98% accuracy.","PeriodicalId":23605,"journal":{"name":"Welding International","volume":"37 1","pages":"12 - 20"},"PeriodicalIF":0.0,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49572884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modeling and optimization of tool parameters in friction stir lap joining of aluminum using RSM and NSGA II","authors":"M. Akbari, Hossein Rahimi Asiabaraki","doi":"10.1080/09507116.2022.2164530","DOIUrl":"https://doi.org/10.1080/09507116.2022.2164530","url":null,"abstract":"Abstract Friction stir welding (FSW) success depends heavily on the temperature and strain the FSW/FSP tool induces. This study examined the influence of FSW tool characteristics like shoulder and probe diameter and probe height on temperature, forces and failure load of welding of AA5083 alloy using the response surface methodology (RSM). The study’s setup consisted of three factors, three levels, and 17 experimental runs. In order to determine the welding temperature, a thermocouple was placed inside the samples. Also, the force during the process was measured using a fixture designed for this purpose. The generated model’s suitability at a 95% confidence level was assessed using an analysis of variance. Using RSM, a relationship was discovered between input parameters, including tool settings and output responses, such as temperature, force, and joint mechanical properties. This relationship was then used to discover the best process parameters using a hybrid multiobjective optimization. Hybrid multiobjective optimization recommends a probe diameter of 5.1 mm, a shoulder diameter of 17.63 mm, and a probe height of 3.86 mm as the optimum tool. This study discovered that the most important factors influencing temperature force and failure load were shoulder diameter, probe diameter, and probe height, respectively.","PeriodicalId":23605,"journal":{"name":"Welding International","volume":"37 1","pages":"21 - 33"},"PeriodicalIF":0.0,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47076512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Study of joining copper-mild steel using microwave energy","authors":"S. Singh, R. M. Belokar","doi":"10.1080/09507116.2022.2162460","DOIUrl":"https://doi.org/10.1080/09507116.2022.2162460","url":null,"abstract":"Abstract In the present work, joining of dissimilar metals using electromagnetic energy has been successfully achieved. A 900 W multimode microwave applicator at the fixed frequency of 2450 MHz was used to generate the required heat energy for joining. Copper (Cu) and mild steel (MS) were chosen as the base material to be joined. Copper metal powder in the form of the thick slurry was prepared and used as a joining agent between two bulk interfaces. The joining process was carried out through the controlled emission of microwaves at a particular area for a particular period of time. Due to these controlled emissions of microwaves, the slurry of metal powder got melted and produced a fine bond with the bulk interfaces on cooling. To understand the nature of the joint formation, joints were characterized by using an optical microscope, SEM, X-ray diffractometer, microhardness tester, and Universal testing machine. Analysis of SEM resulted in a well-defined, merged, and fused joint. The microhardness at the joint zone was recorded to be 73 ± 4 HV and 78 ± 6 HV on copper side and MS side respectively. Strength test results showed the UTS of 170 MPa with 13.25% elongation.","PeriodicalId":23605,"journal":{"name":"Welding International","volume":"37 1","pages":"1 - 11"},"PeriodicalIF":0.0,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48696138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Experimental evaluation of longitudinal tensile properties of ferritic stainless-steel weldment joined by metal inert gas, pulse metal inert gas, and tungsten inert gas welding","authors":"S. Hussain, A. K. Pathak","doi":"10.1080/09507116.2022.2154718","DOIUrl":"https://doi.org/10.1080/09507116.2022.2154718","url":null,"abstract":"Abstract In this work, ferritic stainless steel (FSS) weldments were prepared by tungsten inert gas (TIG), metal inert gas (MIG), and pulsed-MIG welding. Pure argon and a mixture of argon + 2% oxygen were utilized as shielding gas in each type of welding. The FSS (ER430) and austenitic stainless steel (ASS) (ER309L) wires were used as filler consumable wires during all the three types of welding. The effects of varying welding processes, shielding gases, and consumable electrodes on the longitudinal tensile properties of weldments were investigated. The universal tensile testing machine was used to evaluate longitudinal ultimate tensile strength and percentage elongation experimentally in each case. The maximum tensile strength of FSS weldment was obtained in the case of (Ar + 2% O2) mixture of shielding gas and ASS filler wire in each welding process. Heat treatment was also carried out for samples prepared by MIG and TIG welding. The reduction in tensile strength and enhancement in percentage elongation was observed for both MIG and TIG welding after heat treatment.","PeriodicalId":23605,"journal":{"name":"Welding International","volume":"36 1","pages":"744 - 755"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45402172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}