Surface Review and Letters

The Ti-6Al-4V alloy is known as materials with high hardness and good mechanical properties. However, the machining process of this material faces many difficulties due to unfavorable machining conditions. When the machining parameters are not selected in accordance with the Ti-6Al-4V alloy, the surface quality of workpieces does not meet technical requirements. Therefore, the appropriate machining parameters are needed to upgrade the surface roughness of workpieces in high-speed machining (HSM) conditions. The main cutting forces Py and Pz, and surface roughness Rz during turning of Ti-6Al-4V alloy in HSM were investigated and evaluated in this study. The response surface method (RSM) was used to conduct experiments and establish the models of Rz, Py, and Pz under various cutting conditions of feed rate (S), tool nose radius (R), and approach angle ($\phi$). As a result, the S value has the largest impact on the Pz. Moreover, the machining parameters such as S, R, and $\phi$ have a great influence on the Py. The magnitude of Rz is mainly affected by R value. Based on the optimal parameters, the average value of the force Pz has decreased from 238N to 169N, corresponding reduction of about 29%. The value of the force Py has reduced from 184N to 118N, corresponding reduction of about 36%. In addition, the surface roughness of the workpiece has been improved significantly from Rz of 5.6 $\mu$m to 2.7 $\mu$m under optimal parameters condition. The surface roughness of the workpiece after processing in high speed machining was reduced of 52% compared with cutting under non-optimal parameters condition. The best surface quality and minimum cutting force could be achieved under optimal processing parameters in high speed cutting method.

Herein, a biomimetic coating of hydroxyapatite (HA)–Al₂O₃ and HA–ZrO₂ was deposited on Ti–6Al–4V-alloy using vacuum plasma spray (VPS) technique. The bond-coat of ZrO₂ has been introduced between the substrate and reinforced HA coatings to study the effect of bond-coat on structural, mechanical properties and electrochemical corrosion performance of the developed coatings. In addition, the impact of thermal treatment of coating was investigated on these properties too. Coating characteristics, such as morphology, porosity, surface roughness, and crystallinity were investigated. The corrosion performance of coatings was tested in Hank’s-based salt solution (HBSS). Significant enhancement in crystallinity and surface-hardness has been witnessed after heat treatment; nevertheless, porosity reduced. The electrochemical corrosion study revealed that the corrosion resistance of heat-treated samples was better than the as-sprayed coatings samples. The intensity of XRD peaks of all coatings increased after 24h immersion in HBSS for the electrochemical test in comparison to the intensity of peaks before the corrosion test.

Microwave cladding is one of the latest surface engineering techniques, which has been used to improve the surface properties of a material. This technique overcomes almost all limitations of the existing methods. In this study, Ni-based+10% Cr₃C₂ composite clads have been developed in domestic microwave oven of 2.45-GHz frequency and 900-W power. The developed composite clads have been characterized using various standard mechanical and metallurgical techniques like SEM/EDS, XRD and Vickers microhardness tester. Cavitation erosion resistance of developed composite clads has also been examined at different parametric conditions. The microstructure analysis exhibits that the developed composite clads of 730-$\mu$m thickness are free of cracks (solidification and interfacial) and less porous. The presence of various intermetallic and hard carbide phases like FeNi₃, CrSi₂, Cr₃Ni₂SiC, SiC and NiC is confirmed from the XRD analysis. The Vickers microhardness study reveals that the average microhardness of clad region is $430\pm 65$ HV${}_{0.3}$. The cavitation erosion study (at different parametric conditions using vibratory cavitation erosion testing) reveals that the developed composite clads perform much better under cavitation erosion environment than the SS-316 substrate. The stand-off distance is found to be the most dominating factor followed by amplitude and immersion depth.

In metal-cutting operations, the surface roughness of the end product plays a significant role. It not only affects the aesthetic appearance of the end product but also signifies the product’s performance in the long run. Products with a high surface finish have higher endurance limits with negligible local stresses. On the other hand, products with rough surfaces are subjected to high stresses when they are engaged in various mechanical operations with varying loads. Surface roughness depends on various machining factors such as feed rate, depth of cut, cutting speed, or spindle speed. Therefore, it is required to predict surface roughness for the given machining parameters to reduce the cost and increase the life of the end product. In this work, an attempt has been made to evaluate the surface roughness of AZ91 alloy during the end milling operation. In this regard, various state-of-the-art ensemble learning models have been adopted and compared with the proposed hybrid ensemble model. The proposed hybrid ensemble model is the integration of random forest, gradient boosting, and a deep multi-layered neural network. In order to evaluate the performance of the proposed model, comparative analyses have been made in terms of mean square error, mean average error, and $R^2$ score. The result shows that the proposed hybrid model gives minimum error for surface roughness.

Machining of difficult-to-cut materials has always been a focus of research. In terms of surface roughness, it is one of the most important machinability indicators used to evaluate the performance of machining processes. This research aims to investigate the effect of biocompatible TiAlN-coated and uncoated carbide inserts, as well as the effect of cutting parameters such as feed, rotational speed, and depth of cut on surface roughness in the hard turning of M2 tool steel at 64 HRC. The central composite design is used to create the experimental layout. Surface roughness values are measured using separate experiments for coated and uncoated inserts. A quadratic model is selected, and an analysis of variance (ANOVA) is performed to test the adequacy of the developed model. From the ANOVA, it is found that feed and rotational speed are the most significant parameter while hard turning with TiAlN-coated and uncoated inserts, respectively. Cutting parameters are ranked according to their importance using the Pareto chart. The composite desirability function is employed to determine the optimal setting of cutting parameters to minimize the surface roughness and a confirmation experiment is conducted to validate the optimization results. Confirmation results are very close to the predicted value and the error between experimental and predicted results are 7.93% and 9.36% with TiAlN-coated and uncoated carbide inserts, respectively. TiAlN-coated carbide insert gives better surface roughness compared to an uncoated carbide insert.

Magnesium and its alloys have become a great sparking topic of research due to their excellent biocompatible and biodegradable behavior. Magnesium and several biocompatible alloying elements were developed long back. The trends are to develop a surface composite of as-cast Mg alloys to control the degradation behavior. In this work, the surface composites of AZ31–TiO2 were developed by friction stir processing (FSP). The influence of spindle speed or tool rotation speed and number of processing passes on mechanical and microstructural performance were analyzed. The tool rotation speeds 720, 1050, 1550 and 2260RPM with pass 1, pass 2 and pass 3 were considered. The FSP workpiece was analyzed by microstructure and universal testing machine and the significant improvement in grain refinement and hardness was observed.

Nowadays, there has been continuous development of metallic biomaterials to meet special needs in the manufacturing of biomedical implants, units and systems so as to function well in the required environment. Developed biomaterials which possess exceptional properties in terms of biocompatibility and biomechanical compatibility require precision processing and machining to obtain the desired dimensional tolerances. Electrical discharge machining (EDM) is the noncontact or nontraditional process of machining that suits the precision machining of biomaterials. In this work, an effort was made to optimize the EDM parameters during machining of titanium-based biomaterials Ti-6AL-4V, so that the multi-objective responses could be obtained. The response surface method was used in designing the experiment, while the grey relational method was used to analyze the effect of multiple objectives into a single unit. The electrical parameters that were considered in this study include peak current, gap voltage, pulse turn-on and duty cycle. These parameters were set within the acceptable limits of the equipment. Three responses were studied, which are tool wear rates (TWRs), material removal rate (MRR) and surface roughness (SR). Using the signal-to-noise ratio and ANOVA optimum tool/electrode wear rate (TWR) is obtained at $5\times 10^{-5}$ g/min with process parameters $\mathrm{\text{Ip}}=6$ A, $\mathrm{\text{Vg}}=30$ V, $\mathrm{\text{Ton}}=200$  $\mu$s, $D=65$%. Optimum values of material removal rate (MRR) are obtained as 0.01035g/min with process parameters $\mathrm{\text{Ip}}=6$ A, $\mathrm{\text{Vg}}=60$ V, $\mathrm{\text{Ton}}=140$  $\mu$s, $D=50$%. Optimum SR is observed as 2.258 $\mu$m with EDM process parameters $\mathrm{\text{Ip}}=6$ A, $\mathrm{\text{Vg}}=90$ V, $\mathrm{\text{Ton}}=200$  $\mu$s, $D=65$%. Surface characteristics are verified with SEM micrographs. Whereas, grey relation analysis predicted the multi-objective optimum response characteristics. Based on the grey relation grade, experiment number 7 ($\mathrm{\text{Ip}}=6$ A, $\mathrm{\text{Vg}}=90$ V, $\mathrm{\text{Ton}}=200$  $\mu$s, $D=65$%) secured the first rank among the experiments/trails.