Due to growing environmental concerns and economical and social problems in manufacturing sectors, there is a huge demand for the substitution of existing cutting fluids. Further, the cutting fluids selected are expected to reduce the cutting force, improve the surface roughness and also minimize the tool wear during machining operations. Hence, this paper discusses the tribological and morphological behaviour of AISI 316L stainless steel while turning under minimum quantity lubrication (MQL) such as oil–water emulsion, mineral oil, simarouba oil, pongam oil and neem oil based on Taguchi L₂₅ orthogonal array. From the extensive experimentation, it was observed that neem oil MQL with cutting speed of (140, 140, 60 m/min), feed of (0.30, 0.20, 0.10 mm/rev) and depth of cut of (1.0, 1.0, 1.0 mm) resulted in the lowest surface roughness (0.36 µm),cutting force (235.34 N) and tool wear (100.32 microns), respectively. Further, main effects plots and analysis of variance (ANOVA)can be successfully used to identify the optimum process input parameters and their percentage of contribution (P%) on the output parameters during turning of AISI 316L steel under MQL applications. The results clearly indicate that from both an ecological and economical standpoint, neem oil is the most effective lubricant in reducing cutting forces, tool wear and surface roughness during turning of AISI 316L stainless steel under MQL.

Filament winding is a composite material fabrication technique that is used to manufacture concentric hollow components. In this study Carbon/Epoxy composite drive shafts were fabricated using filament winding process with a fiber orientation of [852/±452/252]s. Carbon in the form of multifilament fibers of Tairyfil TC-33 having 3000 filaments/strand was used as reinforcement with low viscosity epoxy resin as the matrix material. The driveshaft is designed to be used in SAE Baja All Terrain Vehicle (ATV) that makes use of a fully floating axle in its rear wheel drive system. The torsional strength of the shaft was tested and compared to that of an OEM steel shaft that was previously used in the ATV. Results show that the composite shaft had 8.5% higher torsional strength in comparison to the OEM steel shaft and was also lighter by 60%. Scanning electron microscopy (SEM) micrographs were studied to investigate the probable failure mechanism. Delamination, matrix agglomeration, fiber pull-out and matrix cracking were the prominent failure mechanisms identified.

In metal cutting industries, optimizing the thermal conductivity and viscosity of vegetable oil-based cutting fluids is critical for ensuring efficient heat dissipation, effective lubrication, and sustainability, directly influencing tool life and machining performance. This study presents a comprehensive experimental analysis employing statistical methods, particularly Taguchi’s Design of Experiments, to evaluate the thermal conductivity and viscosity of Pongamia pinnata, sunflower, and coconut oil incorporated with Silicon Dioxide (SiO₂), Hexagonal Boron Nitride (hBN), and Cupric Oxide (CuO) nanoparticles across different emulsion ratios and nanoparticle volume fractions. The results revealed that Pongamia pinnata oil containing 0.5 (Vol.%) SiO₂ nanoparticles at an emulsion ratio of 1:7 achieved the maximum thermal conductivity, measured at 0.637 W/mK. Additionally, the results revealed that Pongamia pinnata oil at an emulsion ratio of 1:13 exhibited the highest viscosity of 1.33 mPa·S, confirming that both the type of cutting oil and the emulsion ratio are the primary factors influencing viscosity. Further, the ANOVA analysis for thermal conductivity and viscosity highlights that the type of cutting fluid is the dominant factor, accounting for 90.58% of the total variance in thermal conductivity and 70.47% in viscosity, each with a highly significant p-value of 0.00, underscoring its decisive impact on the stability of both properties. Overall, this research offers important guidance for the selection and formulation of vegetable oil-based emulsions with nanoparticle additives. The results support the development of advanced nano lubricants with enhanced performance, catering to the increasing requirements of diverse industrial applications.

An automotive sealed chain consisting of an elastomeric seal between chain plates prevents the entry of external contaminants. But, the presence of a seal induces high transmission loss due to the frictional force. In the present study, a comparative transmission loss test between two ANSI-B29.1 520 series sealed chains of equal geometric dimensions (5/8” pitch) was carried out. The tests revealed a significant difference of 38% in their transmission losses between the chains. To understand these observed differences in the chain performance, the material analysis of the seals (nitrile butadiene rubber) was performed, which showed a significant difference in their composition. The increased seal hardness due to difference in chemical properties resulted in a 21% increase in friction coefficient between the seal and the plates. The seal thickness reduction, the effect of lubricant, and the difference in the frictional forces between chains yielded differences in the transmission losses. GRAPHICAL ABSTRACT

AISI 1040 medium-carbon steel offers a favourable combination of strength and toughness but presents notable machinability challenges for manufacturing industries. This study investigates metal turning operations on AISI 1040 using vegetable oil-in-water nanofluid lubrication to evaluate cutting, feed, and thrust forces. Using Taguchi L ₂₇ orthogonal array, the research analyses the effects of lubricant types, nanoparticle additives, feed rate, depth of cut, and cutting speed. PP, CC, and SF oils were employed as base lubricants, with SiO ₂ , Hexagonal hBN, and CuO as tribological additives. The nanofluid cutting fluids were prepared by ultrasonication of the respective vegetable oil-in-water emulsions containing the dispersed nanoparticles for 60 min to ensure homogeneous and stable nanoparticle dispersion prior to machining. Results demonstrated that forces increased with higher feed rates and depths of cut but decreased with increased cutting speeds, likely due to thermal softening and enhanced lubricant penetration at the tool-chip interface. Among the cutting fluids, PP consistently yielded the lowest forces. Incorporating nanoparticles further improved load-bearing capacity, with SiO ₂ proving most effective. Overall, the combination of PP oil and SiO ₂ nanoparticles provided the maximum force reduction (cutting: 261 N, thrust: 42.2 N, feed: 86.6 N), highlighting its potential as a high-performance bio-based cutting fluid. Furthermore, ANOVA results revealed cutting fluid type as the dominant factor affecting force variation (75.83% for cutting, 87.33% for feed, and 85.26% for thrust). Nanoparticles contributed moderately (18.42%, 10.12%, and 11.40%, respectively), while standard machining parameters had minimal influence. Ultimately, nanoparticle-enhanced bio-based cutting fluids significantly reduce machining forces by improving interfacial tribological characteristics.

AISI 1040 steel is extensively used in structural and automotive applications, where surface integrity plays a significant role in service performance and coating adhesion. Furthermore, the selected cutting fluids are expected to effectively reduce surface roughness and tool wear by improving lubrication at the tool and workpiece interface. This study investigates the influence of SiO₂ nanoparticle-assisted Pongamia pinnata oil on surface roughness and tool wear during the machining of AISI 1040 steel using an uncoated tungsten carbide tool by varying nanoparticle concentration (Vol.%), cutting speed (m/min), depth of cut (mm), and feed rate (mm/rev). The incorporation of 0.5 (Vol.%) SiO₂ nanoparticles significantly enhances machining performance by improving surface finish and reducing tool wear. Further, a minimum surface roughness value of 1.95 microns and tool wear value of 0.047 mm were achieved at a cutting speed of 101 m/min, feed rate of 0.11 mm/rev, depth of cut of 0.25 mm and 0.5 (Vol.%) SiO₂ nanoparticle concentration. ANOVA results indicate that nanoparticle concentration is the most dominant parameter affecting both surface roughness and tool wear, contributing 85.35% to the variation in surface roughness and 82.2% to the total variation in tool wear. Cutting speed is the second most influential factor, accounting for 11.63% of surface roughness variation and 11.07% of tool wear variation, while feed rate and depth of cut exhibit minimal influence in both cases. A second-order RSM model was developed to predict surface roughness and tool wear, showing excellent agreement with experimental results. The model predicted surface roughness with an average error below 2.43%, while the second-order model for tool wear exhibited an average prediction error of 4.95%, confirming its statistical significance and predictive reliability. Desirability Function Method (DFM) analysis yielded a desirability value of 1.000, confirming the optimal combination of machining parameters at 0.5354 (Vol.%) nanoparticle concentration, a cutting speed of 45 m/min, a depth of cut of 0.50 mm, and a feed rate of 0.1298 mm/rev. Overall, this study demonstrates that 0.5 (Vol.%) SiO₂ nanoparticle-incorporated Pongamia pinnata oil is an effective and sustainable cutting fluid, significantly improving surface integrity and machining performance of AISI 1040 steel during machining. Under these settings, the predicted tool wear was 0.0614 mm, accompanied by a high composite desirability value of 0.92786, indicating excellent overall performance. Moreover, the close agreement between experimental, response surface model and BP-ANN-predicted tool wear and surface roughness confirms that the ANN model reliably and robustly captures the complex, nonlinear effects of machining parameters with minimal systematic error.