Khursheed Ahmad Sheikh

Grey cast iron is extensively employed in tribological components owing to its excellent castability, and cost-effectiveness. However, its sliding wear behavior under varying sliding conditions requires systematic investigation and reliable predictive modeling. In the present study, the tribological performance of grey cast iron was systematically evaluated through experimental analysis under dry and oil-lubricated conditions. A total of 32 experimental datasets were generated under varying applied loads and sliding speeds to evaluate the wear behavior and frictional response of the test material. Microstructural characterization revealed randomly distributed graphite flakes embedded within a predominantly pearlitic matrix. The experimental results revealed significantly higher wear rate and coefficient of friction (COF) under dry sliding, whereas oil lubrication substantially reduced friction and material loss. A two-level stacking ensemble learning framework was developed to predict tribological responses. The stacking model demonstrated excellent predictive capability with R ² values of 0.99 for wear rate and 0.97 for COF. Subsequently, single-objective optimization using the Fruit Fly Optimization Algorithm (FOA) identified optimal operating parameters under oil-lubricated conditions, achieving a minimum wear rate of 1.633 × 10 ⁻¹⁴ m ³ /m and a minimum COF of 0.1077. Experimental validation confirmed a close agreement between the predicted and measured responses. The developed stacking–FOA framework provides an effective data-driven approach for prediction and optimization of tribological performance of grey cast iron.

Zinc-aluminum (ZA) based composites are widely recognized for their exceptional mechanical and tribological properties. The combination of low cost, ease of manufacturing, and tunable properties has made ZA alloys suitable for various industrial applications, particularly in the automotive sectors. The review paper focuses on the tribological performance of zinc-aluminum based composites and the effect of various reinforcement materials on their wear and friction properties. The influence of various factors and environmental conditions on the tribological behavior of ZA-based composites are analyzed in detail. Furthermore, the review presents a comparative evaluation of reinforced versus unreinforced ZA alloys and explores the underlying wear mechanisms. Recent advancements in predictive wear modeling using empirical, analytical, and machine learning techniques are also discussed. The paper concludes with insights into the key challenges and future trends in the development of high-performance tribological composites. The study aims to guide future development of ZA-based composites for advanced engineering applications under diverse tribological environments.

The study investigates AA5052alloy matrix composite (MMC) with varying cenosphere particle percentages. Compo-casting integrated cenosphere fly ash particles (2, 4 and 6) wt% into the alloy, improving distribution and wettability. Microhardness increased with higher reinforcement, peaking at 87 Hv with 6% addition. Corrosion resistance in 3.5 wt% NaCl solution showed improved values compared to the base alloy with lowest corrosion rate of 0.144 mmpy for the composite with 6% reinforcement. The study highlights importance of cenosphere reinforcement in enhancing microstructure, hardness, and corrosion resistance in AA5052 MMCs.

The dry sliding wear behaviour of composites based on ZA-27 alloy reinforced with titanium carbide (TiC) particles is discussed in current research. The incorporation of TiC particles to the ZA-27 alloy aims to enhance its wear resistance and improve its performance in applications subjected to sliding contact. The ZA-27 alloy was fabricated through stir casting technique and composites an in-situ technique, ensuring a homogeneous dispersion of TiC particles. This paper primarily studies the impact of three test factors, namely TiC weight percentage, load, and speed on the wear rate of ZA-27 alloy and its composites. A pin-on-disc tribometer was employed to carry out wear tests under dry sliding testing conditions at different loads and speeds. The results show that ZA-27 + 10 wt.% TiC composite demonstrated superior wear resistance in comparison to the ZA-27 + 5 wt.% TiC composite and ZA-27 alloy. The study uses machine learning and statistical techniques to examine the influence of test parameters on the wear rate. The ANOVA results highlight that the TiC weight percentage significantly influences the wear rate, followed by sliding speed and contact load. The artificial neural network (ANN) model exhibited superior performance (R² = 94.12%) compared to the design based on RSM. The results clearly indicate that the ANN outperforms RSM in accurately estimating outcomes. The current research provides novel insights for developing TiC-reinforced composites of ZA-27 alloy to enhance their dry sliding wear resistance, which is a relatively unexplored area in the scientific literature of bearings. Furthermore, optimizing the wear resistance of ZA-27 alloy is essential for improving component longevity, reducing costs, enhancing performance, minimizing downtime, and promoting sustainability.

Hybrid structures, incorporating both aluminum and steel, hold potential for applications in automobile, aerospace, and marine industries. This research delves into the effects of friction stir welding on dissimilar joints (AA2024-T3 and SS304), with a focus on microstructural, mechanical, and tribological aspects. The study identifies optimal welding conditions at (tool rotational speed 710 r/min, traverse speed20 mm/min, tool pin offset1.5 mm towards aluminum, and tilt angle of 1.75 deg) that yield a well-defined joint interface, contrasting with flaws observed at a 40 mm/min traverse speed due to insufficient heat input. Under optimal conditions at 20 mm/min, a well-clean serrated interface, defect-free microstructural evolution, improved surface characteristics; enhanced mechanical performance resulting in higher ultimate tensile strength of 319 MPa with joint efficiency of 72.5 and better tribological performance were achieved with lower wear rate of 1.1607 × 10 ⁻⁵ g/Nm compared to those at 40 mm/min, highlighting the crucial role of optimized friction stir welding parameters in achieving high-quality dissimilar joints with desirable properties.