Investigation into features of graphite nanofluid synthesized using electro discharge process

This paper presents a partitioning around medoid (PAM)-based novel method to realize the recognition of the tool wear state in milling. In PAM, the representative objects called medoids are used to define clusters and average dissimilarities are applied to assess the medoids, which make PAM robust to outliers and therefore improve the clustering performance. Meanwhile, locality preserving projections (LPP) method is utilized to further increase the clustering accuracy by dimension reduction. To show the effectiveness of the proposed method, end milling experiment of Ti-6Al-4V alloy were carried out and the commonly used k-means and fuzzy c-means (FCM) algorithm are introduced to make a comparison with PAM algorithm by using five clustering evaluation indicators. The results show that PAM performs higher accuracy and robustness than the other two clustering algorithm.     

Experimental investigation and 3D finite element prediction of the white layer thickness, heat affected zone, and surface roughness in EDM process

An axisymmetric three-dimensional model for temperature distribution in the electrical discharge machining process has been developed using the finite element method to estimate the surface integrity characteristics of AISI H13 tool steel as workpiece. White layer thickness, depth of heat affected zone, and arithmetical mean roughness consisting of the studied surface integrity features on which the effect of process parameters, including pulse on-time and pulse current were investigated. Additionally, the experiments were carried out under the designed full factorial procedure to validate the numerical results. Both numerical and experimental results show that increasing the pulse on-time leads to a higher white layer thickness, depth of heat affected zone, and the surface roughness. On the other hand, an increase in the pulse current results in a slight decrease of the white layer thickness and depth of heat affected zone, but a coarser surface roughness. Generally, there is a good agreement between the experimental and the numerical results.     

Investigation into the performance of eco-friendly graphite nanofluid as lubricant in MQL grinding

In this study, the lubrication and cooling properties of eco-friendly graphite nanofluids in MQL grinding were investigated. Grinding forces, subsurface temperature of workpiece, surface roughness, micro-hardness and metallographic observations of ground surfaces were employed to evaluate the performance of synthesized nanofluids as lubricant under different grinding parameters. The results were also compared with grinding in dry, pure MQL and flood cooling conditions. The results showed that the tangential forces and force ratios in grinding using graphite nanofluid MQL are lower than that of other lubricating methods especially at extreme cutting parameters. Also, application of graphite nanofluid MQL reduced the grinding temperature at high velocities of workpiece. These reductions could be attributed to the formation of a tribofilm on the ground surface by the present of graphite nanoparticles in the wheel-workpiece interface. Additionally, the presence of this tribofilm in the contact area generated a smooth surface even at high depth of cut and velocity of workpiece. Furthermore, the micro-hardness of ground surfaces increased in graphite nanofluid MQL grinding because of infiltration of graphite nanoparticles in the grinding surface and the plastic deformation of subsurface of workpiece.     

Investigation on tribological performance of CuO vegetable-oil based nanofluids for grinding operations

With ball-bearing and tribofilm lubrication effects, CuO vegetable oil-based nanofluids have exhibited excellent anti-wear and friction reduction properties. In this study, CuO nanofluids were synthesized by a one-step electro discharge process in distilled water containing polysorbate-20 and vegetable oil as a nanoparticle stabilizer and source of fatty-acid molecules in the base fluid, respectively. Pin-on-disk tribotests were conducted to evaluate the lubrication performance of synthesized CuO nanofluids between brass/steel contact pairs under various loadings. Surface grinding experiments under minimum lubrication conditions were also performed to evaluate the effectiveness of the synthesized nanofluids in improving the machining characteristics and surface quality of machined parts. The results of pin-on-disk tests revealed that adding nanofluids containing 0.5% and 1% (mass fraction) CuO nanoparticles to the base fluid reduced the wear rate by 66.7% and 71.2%, respectively, compared with pure lubricant. The lubricating action of 1% (mass fraction) CuO nanofluid reduced the ground surface roughness by up to 30% compared with grinding using lubricant without nano-additives. These effects were attributed to the formation of a lubrication film between the contact pairs, providing the rolling and healing functions of CuO nanoparticles to the sliding surfaces. The micrography of ground surfaces using a scanning electron microscope confirmed the tribological observations.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00314-1