AUTHOR=Zindani Divya , Lakshminarayanan A. K. , Joshua A. , Čep Robert , Logesh K. 

TITLE=Acoustic emission approach to optimize friction stir additive manufacturing process for magnesium alloy ZE41

JOURNAL=Frontiers in Mechanical Engineering

VOLUME=Volume 11 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/mechanical-engineering/articles/10.3389/fmech.2025.1412251

DOI=10.3389/fmech.2025.1412251

ISSN=2297-3079

ABSTRACT=IndroductionMagnesium alloy ZE41 is highly valued in industrial applications due to its superior properties such as high strength-to-weight ratio, corrosion resistance, and low density. However, the welding of magnesium alloys poses significant challenges. Friction Stir Additive Manufacturing (FSAM) offers a promising alternative to traditional welding methods, especially for ZE41 alloy. Among the FSAM process parameters, tool overrun—the distance the tool travels beyond the joint interface—plays a critical role in influencing joint integrity and overall performance. A research gap exists in integrating mechanical output parameters and acoustic signal features for the optimization of FSAM in magnesium alloys. Addressing this gap requires a robust Decision Support System (DSS).MethodsThis study proposes a dedicated DSS to optimize the FSAM process for ZE41 alloy. The DSS incorporates expert linguistic evaluations modeled using T-spherical fuzzy sets and determines experiment rankings using the TODIM (an acronym in Portuguese for Interactive Multi-Criteria Decision Making) method. The experiments systematically varied three transverse speeds (20, 40, and 60 mm/min), two rotational speeds (500 and 1200 rpm), and two tool overruns (0.5 and 1 day). The evaluation criteria included mechanical properties—tensile strength, percentage elongation at break, and Brinell hardness—as well as acoustic emission (AE) signal features such as peak amplitude, absolute energy, and centroid frequency.ResultsThe DSS effectively ranked the experimental runs by integrating mechanical performance and AE signal analysis. Among the configurations, the setup with a transverse speed of 40 mm/min, rotational speed of 500 rpm, and tool overrun of 1 day emerged as the best performing. The output metrics showed improved mechanical integrity and consistent AE characteristics under this setting.DiscussionThe proposed DSS demonstrated robustness, maintaining a consistent ranking of experimental results even when the weights and the attenuation factor in the TODIM method were varied. This confirms the reliability of the DSS for optimizing FSAM process parameters. The integration of fuzzy logic and multi-criteria decision-making provides a comprehensive framework for addressing the complexities of FSAM in magnesium alloys, and can be extended to similar materials and processes in further studies.