Metal matrix composites (MMCs) have achieved significant attention in engineering applications because of their exceptional properties, like increased strength-to-weight ratiosand resistance to wear. However, their manufacturing processes pose challenges for industries, such as oxidation, porosity, and chemical reactions. To address these challenges, this study investigates the processing and sintering (500 °C) of Ti-6Al-4V-SiC_p composites and their mechanical properties, particularly hardness, wear and frictional force using a statistical approach. The main objective of this research is to identify optimal processing conditions for Ti-6Al-4V-SiC_p composites that yield maximum hardness, minimal wear and frictional force. Thisstudy varies three key parameters, namely compaction pressure (Ton/sq.inch), SiC (wt.%), and PVA binder (wt.%) using Taguchi’s design of experiments (TDOE). Further, the response surface methodology (RSM) is used to develop second-order models to predict the output values under different processing conditions, by correlating with the values obtained from TDOE. The results indicate that the most significant influence on the output is exerted by SiC (wt.%), followed by PVA binder (wt.%) and compaction pressure (Ton/sq.inch). To achieve higher hardness with minimal wear and frictional force during processing, SiC_p (15 wt.%), compaction pressure (4 Ton/sq.inch), and PVA binder (3 wt.%) arerecommended. Finally, microstructural analysis using (SEM) scanning electron microscope images, optical macrographs and (AFM) atomic force microscopy revealed that the inclusion of 15 wt.% SiC_p resulted in improved hardness, wear and frictional force compared to 20 wt.% SiC_p. In conclusion, this study provides valuable insights into optimizing the processing parameters of Ti-6Al-4V-SiC_p samples, enabling the production of materials with enhanced hardness and wear resistance.

Die Sink Electric Discharge Machining is a widely used manufacturing process for shaping hard and electrically conductive materials. This study investigates the effects of various electrode materials such as, Ti-6Al-4V-SiCp, Brass and Copper on the machining performance of AISI 316 l Stainless Steel workpieces using EDM. The methodology involved optimizing parameters such as Electrode Material, Discharge Current, Gap Voltage, Spark Gap, Pulse-on Time, and Pulse-off Time. From the extensive experimantation it was observed that the combination of Ti-6Al-4V-SiCp electrode material, 8Amp Discharge Current, 90 V Gap Voltage, 75 μm Spark Gap, 100 μs Pulse-on Time and 15 μs Pulse-off Time has resulted in lowest electrode eear rate, higher machining time, and low electrode surface roughness ratio. Ti-6Al-4V-SiCp electrodes possess higher hardness and electrical conductivity compared to Brass and Copper Electrodes leading to higher wear resistance against repeated thermal shocks during electric discharge machining operation. Feed Forward Artificial Neural Network is successfully applied to predict the output characteristics of the experimentation with high accuracy of 98.3% (Electrode Wear Rate), 94.6% (Machining Time) and 93.8% (Electrode Surface Roughness Ratio). Further, microstructure analysis concludes that lowest wear is observed in Ti-6Al-4V-SiCp electrodes compared to Brass and Copper electrodes.

Incorporation of natural fibers with Fiber Reinforced Polymers (FRPs) is a promising avenue for sustainable and high-performance composite materials. The fibers, derived from outer bark portion of plants, offer significant merits such as renewability, low cost, and eco-friendly. Unique mechanical and physical properties, and widespread availability of Hibiscus Rosa-sinensis have made them subject of intense research interest. The present study investigated the chemically treatment of HRS Fibers using Sodium Hydroxide (NaOH), Potassium Permanganate (KMnO₄), and Acetic Acid (CH₃COOH) bat varying weight percentages (3, 4, 5 Wt%) and solutionizing times (1, 2, 3 h) based on Taguchi’s L27 orthogonal array. Fourier Transform Infrared (FT-IR) analysis revealed significant changes in O–H, C–H stretching, C=O moiety, aromatic ring, and C–O/C–C stretching. Potassium Permanganate treatment at 4 Wt% and 3 h of solutionizing time has yielded the best results. Multi-Layer Perceptron Artificial Neural Network (MLP-ANN) has been successfully applied to accurately predict the output physical characteristics of chemically treated HRS fibers using experimental data. Further Single Fiber Pull-out test results in Potassium Permanganate at 4 Wt% and 3 h solutionizing time as best sample with highest Tensile Strength and Modulus. This research underscores the effectiveness of the chemical treatment process in enhancing the properties of HRS plant fibers for potential composite applications.

The present study examines the effect of trace additions of copper (up to 1 wt.%) and zinc (0.5 wt.%) as the alloying elements on the microstructure, hardness, and wear behaviour of T6 treated A356 (Al-7Si) alloy. Wear tests were conducted using a pin-on-disc tribometer under a constant sliding speed of 200 RPM, varying applied load (20–40 N), and sliding distance (0–3000 m) to determine the wear rate and the coefficient of friction. The results indicated a minimum of 1 wt.% of copper was required to form the Al₂Cu intermetallic phase, resulting in a finer grain structure and improved hardness. However, the role of zinc as a trace element was not observed on the microstructure; the observed changes may be the combined effect of copper and zinc as a whole. The highest hardness of 107 VHN (98% increase) was achieved with 1 wt.% copper addition during peak aging at 100 °C. Also, wear tests showed that adding 1 wt.% copper to the A356 alloy and a 100 °C precipitation hardening (T6) treatment improved the wear resistance by 150–182% with a reduced coefficient of friction.