| Issue |
EPJ Web Conf.
Volume 345, 2026
4th International Conference & Exposition on Materials, Manufacturing and Modelling Techniques (ICE3MT2025)
|
|
|---|---|---|
| Article Number | 01011 | |
| Number of page(s) | 17 | |
| DOI | https://doi.org/10.1051/epjconf/202634501011 | |
| Published online | 07 January 2026 | |
https://doi.org/10.1051/epjconf/202634501011
Effect of process parameters on strength and hardness of AA1100 fabricated by friction stir additive manufacturing
Department of Mechanical Engineering, Vidya Jyothi Institute of Technology, Aziznagar, Hyderabad, India
* Corresponding author: baridula@gmail.com
Published online: 7 January 2026
This study investigates the process–property relationships in AA1100 aluminium alloy fabricated via Friction Stir Additive Manufacturing (FSAM), with a focus on optimising ultimate tensile strength (UTS) and Vickers microhardness through parameter tuning. A Taguchi L4 orthogonal array was employed to systematically vary tool rotational speed (900 and 1120 RPM), feed rate (25 and 40 mm/min), and tilt angle (1° and 2°), enabling quantitative analysis of main effects via analysis of means (ANOM). Results reveal that tilt angle is the most influential factor for UTS (Δ = 2.73 MPa), with a 1° setting delivering the highest UTS of 91.89 MPa by promoting symmetric stirring and defect‐free interlayer bonding. Conversely, rotational speed dominates hardness evolution (Δ = 1.2 HV), where 1120 RPM enhanced dynamic recrystallization and yielded a peak average hardness of 36.63 HV. The UTS variation across runs was limited to approximately 3 MPa and hardness fluctuation was within 1.4 HV and this proved the process stability of FSAM for AA1100 and its capability to produce dimensionally and structurally consistent builds. The interplay between parameters highlights a trade‐off: settings optimal for strength differ from those maximising surface hardness, necessitating application‐ specific process selection. These findings position FSAM as a viable, energy‐efficient route for manufacturing dimensionally precise, mechanically stable, corrosion‐resistant aluminium components, especially for aerospace, marine, and structural applications. Future work can focus on advanced microstructural characterisation, fatigue analysis and machine learning based predictive modelling for FSAM of aluminium alloys.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

