Sachithananthan J, Raviram R, Mohandass M, Gurusamy V
{"title":"Establishing Interconnections and Predictive Modelling for CMT Cladding on 316L Stainless Steel","authors":"Sachithananthan J, Raviram R, Mohandass M, Gurusamy V","doi":"10.12688/materialsopenres.17617.1","DOIUrl":null,"url":null,"abstract":"Background Austenitic stainless-steel cladding is vital for corrosion resistance in industries such as petrochemicals, marine, and nuclear. Weld bead geometry and dilution, governed by process parameters, impact cladding quality. This study examines weld bead geometry with welding current, speed, and nozzle-to-plate distance, creating equations to predict dimensions and control geometry. Method This research explores Cold Metal Transfer (CMT) cladding, emphasizing its interaction with parameters using ANOVA and orthogonal arrays. It uncovers patterns and correlations, leading to a robust mathematical model derived from a Definitive Screen Design in Surface Methodology. Results Process parameter changes particularly affect internal shape (bead width, dilution, penetration area) compared to external shape (penetration, reinforcement) using mathematical model. And the validity of the model is defined. Penetration is primarily affected by welding current and nozzle-to-plate distance, with higher current and smaller distances leading to deeper penetration. Reinforcement is minimally impacted by welding current, speed, and error but decreases with a larger nozzle-to-plate distance. Bead width increases with higher welding current and larger nozzle-to-plate distances, while the effects of welding speed and error are relatively small. Dilution is reduced by higher welding current and larger distances, but error can significantly increase dilution. Welding speed has minimal impact on dilution. Conclusion This study enhances the understanding of CMT cladding. By analyzing parameter interactions, it predicts and controls weld dimensions. Statistical tools reveal patterns, aiding in a strong mathematical model. Significant for industrial applications, it emphasizes the impact of parameters on the quality and structure of cladding using austenitic stainless steel.","PeriodicalId":29806,"journal":{"name":"Materials Open Research","volume":"109 9","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials Open Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12688/materialsopenres.17617.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background Austenitic stainless-steel cladding is vital for corrosion resistance in industries such as petrochemicals, marine, and nuclear. Weld bead geometry and dilution, governed by process parameters, impact cladding quality. This study examines weld bead geometry with welding current, speed, and nozzle-to-plate distance, creating equations to predict dimensions and control geometry. Method This research explores Cold Metal Transfer (CMT) cladding, emphasizing its interaction with parameters using ANOVA and orthogonal arrays. It uncovers patterns and correlations, leading to a robust mathematical model derived from a Definitive Screen Design in Surface Methodology. Results Process parameter changes particularly affect internal shape (bead width, dilution, penetration area) compared to external shape (penetration, reinforcement) using mathematical model. And the validity of the model is defined. Penetration is primarily affected by welding current and nozzle-to-plate distance, with higher current and smaller distances leading to deeper penetration. Reinforcement is minimally impacted by welding current, speed, and error but decreases with a larger nozzle-to-plate distance. Bead width increases with higher welding current and larger nozzle-to-plate distances, while the effects of welding speed and error are relatively small. Dilution is reduced by higher welding current and larger distances, but error can significantly increase dilution. Welding speed has minimal impact on dilution. Conclusion This study enhances the understanding of CMT cladding. By analyzing parameter interactions, it predicts and controls weld dimensions. Statistical tools reveal patterns, aiding in a strong mathematical model. Significant for industrial applications, it emphasizes the impact of parameters on the quality and structure of cladding using austenitic stainless steel.
期刊介绍:
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