Abstract
In this research work, hybrid AA2024–SiC/Si3N4 alloy composites were designed and prepared through a semi-automatic stir casting route, following industrial procedure. The ceramic (SiC/Si3N4) particulates were reinforced in the complementary manner (0–4 wt% @ step of 1%), leading to five composite specimens, namely CN04, CN13, CN22, CN31, and CN40. The samples of each composition were analyzed for their physical, mechanical, thermal conductivity, fracture toughness, and tribological behavior (steady-state sliding wear analysis) adopting ASTM standards. The Taguchi methodology was applied to optimize experimental simulations and input operating variables (like sliding velocity, sliding distance, normal load, composition, and environment temperature) with ANOVA. Worn-out surface micrograph studies were performed using a scanning electron microscope (SEM) and energy-dispersive X-ray spectroscopy (EDS) to understand wear mechanisms and elemental presence/dispersion over the surface. Further, a decision-making tool like a hybrid AHP-TOPSIS method was applied to rank the hybrid alloy composites based upon performance measures. The hybrid alloy composites shows some peculiar properties like density ~ 2.495–2.772 g/cc, voids content ~ 0.63–10.49%, Rockwell hardness (HRB) ~ 76.6 to 92.8 HRB, tensile strength ~ 191–277 MPa, flexural strength ~ 291–419 MPa, Impact strength ~ 24–100 J, thermal conductivity ~ 141–152 W/mK, fracture toughness ~ 6–41 MPa √m. Taguchi’s factorial design of the experiment shows an error of 3.5% for the S/N ratio of wear rate that validates the robustness of the experiential design. The wear rate and friction coefficient improve with sliding velocity irrespective of composition across the formulation. Further, it has been found that CN22 hybrid alloy composite having an equal amount of both ceramics tends to optimize the overall physical and mechanical properties along with steady-state sliding behavior, which is in-tune-with the results of ranking obtained hybrid AHP-TOPSIS method. The sensitivity analysis of performance criteria gives robust/stable ranking order whenever the criteria’s weight varies within ± (10–15)%.
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Acknowledgements
The authors express their sincere gratitude to the Department of Mechanical Engineering of Malaviya National Institute of Technology, Jaipur-302017, Rajasthan, INDIA for their all kinds of financial as well as other miscellaneous infrastructural support. The authors also acknowledge the aid and facilities provided by the Advanced Research Lab for Tribology and Material Research Centre of the Institute for experimentation and characterization work.
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MK—Supervisor, conceptualization, methodology, editing the manuscript. RK—M.Tech. student, original or first draft of the manuscript. SB—Editing and some characterization work. AK—Methodology and editing of the manuscript. SH—Hybrid AHP-TOPSIS method and its calculations.
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Kumar, M., Kumar, R., Bhaskar, S. et al. Parametric Optimization and Ranking Analysis of Hybrid AA2024–SiC/Si3N4 Alloy Composites Based on Mechanical and Sliding Wear Performance. J Bio Tribo Corros 8, 24 (2022). https://doi.org/10.1007/s40735-021-00619-z
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DOI: https://doi.org/10.1007/s40735-021-00619-z