Advances in Friction Stir Welding in the Light of Industry 4.0

A special issue of Journal of Manufacturing and Materials Processing (ISSN 2504-4494).

Deadline for manuscript submissions: closed (6 June 2022) | Viewed by 8788

Special Issue Editor


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Guest Editor
Department of Manufacturing Engineering, Brigham Young University, Provo, UT 84602, USA
Interests: friction stir welding; smart manufacturing
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Special Issue Information

Dear Colleagues,

With 30 years of friction stir welding research and development now available to the scientific community, the tools available to aid current research have greatly expanded. Novel approaches to the application of machine learning, modeling tools, and real-time data are changing how we control, predict, and apply friction stir technologies to a myriad of use cases. While initially friction stir welding was applied much like many other bespoke metallurgical process, the aid of real-time data acquisition has provided the impetus to evaluate and predict in-process changes that enable significant improvements in properties, reduction in cycle times, and consistency in application.

This Special Issue seeks papers that focus on the use of data to improve the control, understanding, quality, and process conditions of friction stir technologies, specifically in the following areas:

  • in-process quality monitoring applied modeling tools that aid improved quality;
  • predictive modeling tools that aid in process improvements;
  • the application of machine learning to friction stir technologies; real-time control of friction stir technologies;
  • the application of data-based model validation.

Prof. Dr. Yuri Hovanski
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Manufacturing and Materials Processing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • friction stir welding
  • friction stir process
  • additive friction stir
  • refill friction stir spot welding
  • machine learning
  • non-destructive evaluation
  • closed-loop control
  • in-process control
  • real-time evaluation
  • process modeling

Published Papers (4 papers)

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Research

16 pages, 6360 KiB  
Article
Microstructural and Mechanical Properties of AZ31B to AA6061 Dissimilar Joints Fabricated by Refill Friction Stir Spot Welding
by Venukumar Sarila, Harisivasri Phanindra Koneru, Muralimohan Cheepu, Bharat Kumar Chigilipalli, Venkata Charan Kantumuchu and Muthukumaran Shanmugam
J. Manuf. Mater. Process. 2022, 6(5), 95; https://doi.org/10.3390/jmmp6050095 - 30 Aug 2022
Cited by 14 | Viewed by 1754
Abstract
Dissimilar friction stir spot welds (FSSW) between the magnesium and aluminum alloys are joined, using a novel approach called refill friction stir spot welding. The present work aims to evaluate the macrostructural and mechanical properties of refill friction stir spot welded AZ31B and [...] Read more.
Dissimilar friction stir spot welds (FSSW) between the magnesium and aluminum alloys are joined, using a novel approach called refill friction stir spot welding. The present work aims to evaluate the macrostructural and mechanical properties of refill friction stir spot welded AZ31B and AA 6061-T6 alloys in two combinations, i.e., identical Mg-to-Mg and dissimilar Mg-to-Al joints, and the results are compared with the results obtained in conventional friction stir spot welding. The hardness profiles of the similar welds had the appearance of a W-shape, and the Thermo mechanically affected zone and heat-affected zone of both methods had lower hardness values than the rest of the weld. Along with the interface between the aluminum and magnesium sheets, a thin intermetallic compound layer of Al12Mg17 has been identified, which has led to an increase in hardness. The static shear strength of both similar and dissimilar refill spot friction welds was much greater than that of traditional spot friction welds. In both similar and dissimilar spot friction welds, two distinct failure scenarios are discovered. Full article
(This article belongs to the Special Issue Advances in Friction Stir Welding in the Light of Industry 4.0)
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15 pages, 6852 KiB  
Article
2D Axisymmetric Modeling of Refill Friction Stir Spot Welding and Experimental Validation
by Evan Berger, Michael Miles, Andrew Curtis, Paul Blackhurst and Yuri Hovanski
J. Manuf. Mater. Process. 2022, 6(4), 89; https://doi.org/10.3390/jmmp6040089 - 18 Aug 2022
Cited by 5 | Viewed by 1818
Abstract
The development of the simulation of refill friction stir spot welding (RFSSW) is critical to be able to predict the behavior of aluminum in the process under specific parameters. A two-dimensional axisymmetric thermo-mechanical model of the RFSSW process for 7075-T6 aluminum alloy sheet [...] Read more.
The development of the simulation of refill friction stir spot welding (RFSSW) is critical to be able to predict the behavior of aluminum in the process under specific parameters. A two-dimensional axisymmetric thermo-mechanical model of the RFSSW process for 7075-T6 aluminum alloy sheet was developed and validated with experimental data. Welding temperatures and material flow, including defect formation, were accurately predicted by the model. While these results are encouraging, further development of bonding criteria is needed for simulation models, in order to enable the prediction of properties such as joint strength. The simulation was validated by a comparison of temperatures measured in the weld, which were demonstrated to be accurate at all positions in and around the weld nugget, within 10% of measured values. Additional validation of material flow was performed with post-weld optical microscopy where the simulation is shown to be able to predict the presence or absence of internal volumetric defects based on the variation in process parameters. Finally, the prediction of the tool process forces during the welding cycle were evaluated; however, both probe and shoulder forces were overestimated using the standard flow stress data for AA 7075-T6. Full article
(This article belongs to the Special Issue Advances in Friction Stir Welding in the Light of Industry 4.0)
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14 pages, 3646 KiB  
Article
A Generalized Method for In-Process Defect Detection in Friction Stir Welding
by Johnathon B. Hunt, Brian A. Mazzeo, Carl D. Sorensen and Yuri Hovanski
J. Manuf. Mater. Process. 2022, 6(4), 80; https://doi.org/10.3390/jmmp6040080 - 31 Jul 2022
Cited by 4 | Viewed by 2135
Abstract
Friction stir welding (FSW) is an advantageous solid-state joining process that is suitable for many materials in multiple industries. In an industrial setting, manufacturers are actively seeking faster welding speeds to increase throughput. Increasing welding speed limits the size of defect-free parameter windows, [...] Read more.
Friction stir welding (FSW) is an advantageous solid-state joining process that is suitable for many materials in multiple industries. In an industrial setting, manufacturers are actively seeking faster welding speeds to increase throughput. Increasing welding speed limits the size of defect-free parameter windows, which may increase the frequency of defects. The push for faster welding speeds emphasizes the need for economical non-destructive evaluation (NDE) for FSW, like any other type of welding. This work introduces a generalized defect detection method that recognizes the stochastic nature of the FSW process, and that can be generally applied to FSW of a material across a dynamic range of process parameters and welding conditions. When applied to aluminum friction stir-welded blanks at speeds ranging from 1500 to 3000 mm/min with varying ranges of tool tilts, the methodology proved 100% effective at positive detection when defects were present with zero scrap rate. Furthermore, additional development demonstrated the proposed stochastic approach can be used to detect the spatial location of a defect within a weld with 94% detection accuracy and a 4.2% scrap rate. Full article
(This article belongs to the Special Issue Advances in Friction Stir Welding in the Light of Industry 4.0)
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14 pages, 3570 KiB  
Article
Numerical Simulation of the Thermo-Mechanical Behavior of 6061 Aluminum Alloy during Friction-Stir Welding
by Vasiliy Mishin, Ivan Shishov, Alexander Kalinenko, Igor Vysotskii, Ivan Zuiko, Sergey Malopheyev, Sergey Mironov and Rustam Kaibyshev
J. Manuf. Mater. Process. 2022, 6(4), 68; https://doi.org/10.3390/jmmp6040068 - 24 Jun 2022
Cited by 8 | Viewed by 2430
Abstract
In this work, a finite-element model was elaborated to simulate the thermomechanical behavior of 6061 aluminum alloy during friction-stir welding (FSW). It was shown that FSW-induced deformation is a two-stage process. In addition to the stirring action exerted by the rotating tool probe, [...] Read more.
In this work, a finite-element model was elaborated to simulate the thermomechanical behavior of 6061 aluminum alloy during friction-stir welding (FSW). It was shown that FSW-induced deformation is a two-stage process. In addition to the stirring action exerted by the rotating tool probe, the material in the near-surface area of the stir zone also experienced a secondary deformation by the shoulder edge after passage of the welding tool. Both deformation steps were found to be comparable in terms of temperature and strain, but the secondary deformation was primarily concentrated in the near-surface layer. The effects of tool rotation and translation rates on FSW temperature and strain were also systematically examined. Depending on particular welding conditions, the peak welding temperature was predicted to vary from 360 to 500 °C, while the cumulative effective strain was from 12 to 45. Full article
(This article belongs to the Special Issue Advances in Friction Stir Welding in the Light of Industry 4.0)
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