A highly advanced thermo-electric machining technique called wire electrical discharge machining (WEDM) can effectively produce parts with varying hardness or complicated designs that have sharp edges and are very difficult to machine using standard machining procedures. This useful technology for the WEDM operation depends on the typical EDM sparking phenomena and makes use of the commonly used non-contact material removal approach. Since its inception, WEDM has developed from a simple approach for creating tools and grown to an outstanding option for creating micro-scale components having the greatest degree of dimensional precision and surface finish characteristics. The WEDM method has endured over time as an efficient and affordable machining alternative that can meet the stringent operating specifications enforced by rapid manufacturing cycles and increasing expense demands. The possibility of wire damage and bent, nevertheless, has severely hindered the process’ maximum potential and decreased the precision as well as effectiveness of the WEDM process. The article examines the wide range of investigations that have been done; from the WEDM through the EDM process’ spin-offs. It describes WEDM investigation that required variables optimization and an assessment of the many influences on machining efficiency and accuracy. Additionally, the research emphasizes adaptive monitoring and control of the process while examining the viability of multiple approaches to control for achieving the ideal machining parameters. Numerous industrial WEDM applications are described with the advancement of hybrid machining techniques. The paper’s conclusion examines these advancements and identifies potential directions for subsequent WEDM research. The investigation on WEDM of metal matrix composites (MMCs) is also reviewed; along with the impacts of various cutting variables like wire feed rate (F), voltage (V), wire tension (WT), and dielectric flow rate on cutting processes outcomes like material removal rate (MRR), kerf width (K_w) and surface roughness (SR). In the present article, future directions for WEDM research were also suggested.

Nanoparticles dispersed in lubricants are being studied for their ability to reduce friction and wear. This paper examines SAE 5W-30 oil enhanced with dispersed graphene nanoplates for tribological and rheological properties. Graphene nanoplate (GNs) concentration effects on the rheological and tribological properties of 5W-30 base oil (0.03, 0.06, 0.09, 0.12, and 0.15 wt percent) were tested. Under various loads, a four-ball testing model was used to conduct a tribological analysis (200, 400, 600, and 800 N). Kinematic viscosity is calculated, and base oil and nanofluid-added 5W30 lubricant are compared for thermal conductivity and flashpoint. Wear scar and coefficient of friction improved by 15% and 33% with nano-additives. When related to the base oil, the flashpoint, thermal conductivity, kinematic viscosity, and pour point all increased, by 25.4%, 77.4%, 29.9%, and 35.4%, respectively. The addition of GNs improved the properties of 5W30 engine oil.

Non-exhaust brake dust and pollution arising from metal, semi-metal, and ceramic brake pads have made recent research consider their replacement by potential natural fibers such as hemp, flax, sisal, etc. These natural fibers are lightweight, biodegradable, and cheap. This paper discusses the wear and friction analysis of hemp fiber reinforced polymer brake pad material. Three test specimens viz. HF4P20, HF5P20, and HF6P20 were prepared per ASTM G99 standards for the pin-on disc tribo-test. The test trials and validation were done using the Taguchi design of experiments and ANOVA. The optimum result showed a consistent coefficient of friction and lowered specific wear rate for HF6P20 brake pad material. Worn surface morphology was done using scanning electron microscopy.

The materials used in engineering have seen a significant transformation in the contemporary world. Numerous composites are employed to overcome these problems because conventional materials are unable to meet the needs of current applications. For quite some time, professional engineers and researchers have been captivated by the problem of choosing the best machining parameters for new composite materials. Wire electrical discharge machining is a popular unconventional machining process that is often used for making complex shapes. Numerous process parameters influence the WEDM process. Thus, to achieve affordable and high-quality machining, the right set of process parameters must be provided. Finding the wire cut EDM optimized settings for the fabricated LM5/ZrO₂/Gr composite is the main aim of this research. The chosen input parameters are the wire feed, pulse on and pulse off times, the gap voltage, and the reinforcing percentage. In this study, LM5/ZrO₂/Gr composites were made from stir casting with 6-weight percent ZrO₂ as the reinforcement and varying graphite percentages of 2, 3, and 4 wt%. Then they were machined in WEDM using L₂₇ OA to seek the best parameters for machining by adjusting the input parameters. The findings were analysed by means of grey relation analysis (GRA) to achieve the supreme material removal rate (MRR), lowest surface roughness (SR), and a smaller kerf width (K_w) simultaneously. GRA determines the impact of the machining variables on the standard characteristics and tests the impact of the machining parameters. Confirmation experiments were performed finally to acquire the best findings. The experimental findings and GRA show that the ideal process conditions for achieving the highest grey relational grade (GRG) are 6% ZrO₂ with 2% graphite reinforcement, a wire feed of 6 m/min, a pulse off time (T_off) of 40 µs, a pulse on time (T_on) of 110 µs, and a gap voltage (GV) of 20 V. The gap voltage (22.87%) has the greatest impact on the GRG according to analysis of variance (ANOVA), subsequent to the interaction between the pulse on time and the gap voltage (16.73%), pulse on time (15.28%), and pulse off time (14.42%). The predicted value of the GRG is 0.679; however, the experimental GRG value is 0.672. The values are well-aligned between the expected and the experimental results. The error is only 3.29%, which is really little. Finally, mathematical models were created for each response.