Investigation of the Contact Interface between Natural Fibre Metal Laminates under Tension Using Finite Element Analysis (FEA).

Fibre Metal Laminates (FMLs) consist of layers of metals combined with layers of fibre-reinforced composites bonded together to create a laminate. The behaviour of a Fibre Metal Laminate (FML) with natural fibre composites has been investigated in this study with a specific focus on the performance of the laminate under uniaxial tension. The integration of aluminium layers with natural fibre flax/pp layers at different fibre orientations has been numerically modelled and analysed, by investigating the contact interface between natural fibre metal laminates (NFML) using finite elements (FE) implemented in ABAQUS/Explicit. The finite element model was developed by the isotropic-hardening behaviour of metal layers, the built-in Hashin damage model and cohesive surface-based behaviour for the interface. The results of the simulation included stress-strain response, failure sequences, delamination effect and ultimate tensile strength. It was found that those results are significantly affected by the layup sequence, giving a significant advantage to the unidirectional laminate, when the uniaxial loading is taken into consideration. This advantage is measured as a 41.9% reduction of the ultimate tensile strength when the flax fibres are oriented at [0/90] configuration between the aluminium layers and a 30% reduction when the fibres are oriented at [±45] angles.

Three-Dimensional Finite Element Modeling of Drilling-Induced Damage in S2/FM94 Glass-Fiber-Reinforced Polymers (GFRPs).

Considering that the machining of composites particularly fiber-reinforced polymer composites (FRPCs) has remained a challenge associated with their heterogeneity and anisotropic nature, damage caused by drilling operations can be considerably mitigated by following optimum cutting parameters. In this work, we numerically evaluated the effects of cutting parameters, such as feed rate and spindle speed, on the thrust force and torque during the drilling of glass-fiber-reinforced polymers (GFRPs). A meso-scale, also known as unidirectional ply-level-based finite element modeling, was employed assuming an individual homogenized lamina with transversely isotropic material principal directions. To initiate the meso-scale damage in each lamina, 3D formulations of Hashin's failure theory were used for fiber damage and Puck's failure theory was implemented for matrix damage onset via user subroutine VUMAT in ABAQUS. The developed model accounted for the complex kinematics taking place at the drill-workpiece interface and accurately predicted the thrust force and torque profiles as compared with the experimental results. The thrust forces for various drilling parameters were predicted with a maximum of 10% error as compared with the experimental results. It was found that a combination of lower feed rates and higher spindle speeds reduced the thrust force, which in turn minimized the drilling-induced damage, thus providing useful guidelines for drilling operations with higher-quality products. Finally, the effect of coefficient of friction was also investigated. Accordingly, a higher coefficient of friction between the workpiece and drill-bit reduced the thrust force.

Experimental Investigations and Effect of Nano-Powder-Mixed EDM Variables on Performance Measures of Nitinol SMA.

In the present study, the effect of alumina (Al2O3) nano-powder was investigated for the electrical discharge machining (EDM) of a Nitinol shape memory alloy (SMA). In addition to the nano-powder concentration, other parameters of pulse-on-time (Ton), pulse-off-time (Toff), and current were selected for the performance measures of the material removal rate (MRR), surface roughness (SR), and tool wear rate (TWR) of Nitinol SMA. The significance of the design variables on all the output measures was analyzed through an analysis of variance (ANOVA). The regression model term has significantly impacted the developed model terms for all the selected measures. In the case of individual variables, Al2O3 powder concentration (PC), Toff, and Ton had significantly impacted MRR, TWR, and SR measures, respectively. The influence of EDM variables were studied through main effect plots. The teaching-learning-based optimization (TLBO) technique was implemented to find an optimal parametric setting for attaining the desired levels of all the performance measures. Pursuant to this, the optimal parametric settings of current at 24 A, PC at 4 g/L, Toff at 10 µs, and Ton of 4 µs have shown optimal input parameters of 43.57 mg/min for MRR, 6.478 mg/min for TWR, and 3.73 µm for SR. These results from the TLBO technique were validated by performing the experiments at the optimal parametric settings of the EDM process. By considering the different user and application requirements, 40 Pareto points with unique solutions were generated. Lastly, scanning electron microscopy (SEM) performed the machined surface analysis. The authors consider this to be very beneficial in the nano-powder-mixed EDM process for appropriate manufacturing operations.

Joining of Dissimilar Al and Mg Metal Alloys by Friction Stir Welding.

In engineering applications, such as automobile, marine, aerospace, and railway, lightweight alloys of aluminum (Al) and magnesium (Mg) ensure design fitness for fuel economy, better efficiency, and overall cost reduction. Friction stir welding (FSW) for joining dissimilar materials has been considered better than the conventional fusion welding process because of metallurgical concerns. In this study, dissimilar joints were made between the AA6061 (A), AZ31B (B), and AZ91D (C) combinations based on the varying advancing side (AS) and retreating side (RS). The dissimilar joints prepared by the FSW process were further characterized by tensile testing, impact testing, corrosion testing, fracture, and statistical and cost analysis. The results revealed a maximum tensile strength of 192.39 MPa in AZ91 and AZ31B, maximum yield strength of 134.38 MPa in a combination of AA6061 and AZ91, maximum hardness of 114 Hv in AA6061 and AZ31B, and lowest corrosion rate of 7.03 mV/A in AA6061 and AZ31B. The results of the properties were supported by photomicrographic fracture analysis by scanning electron microscopy (SEM) observations. Further, the performance of dissimilar joints was statistically analyzed and prioritized for preference by similarity to the ideal solution (TOPSIS) method.

Investigating the Microstructural and Mechanical Properties of Novel Ternary Reinforced AA7075 Hybrid Metal Matrix Composite.

This study investigates the comparison of the microstructural and mechanical properties of a novel ternary reinforced AA7075 hybrid metal matrix composite. Four samples, including AA7075 (base alloy), AA7075-5wt %SiC (MMC), AA7075-5wt %SiC-3wt %RHA (s-HMMC), and AA7075-5wt %SiC-3wt %RHA-1wt %CES (n-HMMC) were developed using the stir casting liquid metallurgy route, followed by the heat treatment. The experimental densities corresponded with the theoretical values, confirming the successful fabrication of the samples. A minimum density of 2714 kg/m3 was recorded for the n-HMMC. In addition, the highest porosity of 3.11% was found for n-HMMC. Furthermore, an increase of 24.4% in ultimate tensile strength and 32.8% in hardness of the n-HMMC was recorded compared to the base alloy. However, its ductility and impact strength was compromised with the lower values of 5.98% and 1.5 J, respectively. This was confirmed by microstructural analysis, which reveals that n-HMMC has mixing issues and forms agglomerates in the matrix, which served as the potential sites of stress concentration leading to low impact strength and ductility. Nevertheless, the hybrid composites showed superior mechanical properties over the MMC and its base alloy.

Parametric Optimization and Influence of Near-Dry WEDM Variables on Nitinol Shape Memory Alloy.

Nitinol-shape memory alloys (SMAs) are widely preferred for applications of automobile, biomedical, aerospace, robotics, and other industrial area. Therefore, precise machining of Nitinol SMA plays a vital role in achieving better surface roughness, higher productivity and geometrical accuracy for the manufacturing of devices. Wire electric discharge machining (WEDM) has proven to be an appropriate technique for machining nitinol shape memory alloy (SMA). The present study investigated the influence of near-dry WEDM technique to reduce the environmental impact from wet WEDM. A parametric optimization was carried out with the consideration of design variables of current, pulse-on-time (Ton), and pulse-off-time (Toff) and their effect were studied on output characteristics of material removal rate (MRR), and surface roughness (SR) for near-dry WEDM of nitinol SMA. ANOVA was carried out for MRR, and SR using statistical analysis to investigate the impact of design variables on response measures. ANOVA results depicted the significance of the developed quadratic model for both MRR and SR. Current, and Ton were found to be major contributors on the response value of MRR, and SR, respectively. A teaching-learning-based optimization (TLBO) algorithm was employed to find the optimal combination of process parameters. Single-response optimization has yielded a maximum MRR of 1.114 mm3/s at Ton of 95 µs, Toff of 9 µs, current of 6 A. Least SR was obtained at Ton of 35 µs, Toff of 27 µs, current of 2 A with a predicted value of 2.81 µm. Near-dry WEDM process yielded an 8.94% reduction in MRR in comparison with wet-WEDM, while the performance of SR has been substantially improved by 41.56%. As per the obtained results from SEM micrographs, low viscosity, reduced thermal energy at IEG, and improved flushing of eroded material for air-mist mixture during NDWEDM has provided better surface morphology over the wet-WEDM process in terms of reduction in surface defects and better surface quality of nitinol SMA. Thus, for obtaining the better surface quality with reduced surface defects, near-dry WEDM process is largely suitable.

Evaluation of Mechanical and Tribological Aspect of Self-Lubricating Cu-6Gr Composites Reinforced with SiC-WC Hybrid Particles.

Because of their high thermal conductivity, good corrosion resistance, and great mechanical qualities, copper matrix composites are appealing materials utilized in a variety of industries. This study investigates the mechanical properties of copper-graphite (Cu-Gr) matrix composites reinforced with silicon carbide (SiC) and tungsten carbide (WC) particles by hot pressing using powder metallurgy method. The goal is to investigate the influence of the reinforcement ratio on the mechanical characteristics of copper composite materials generated (density, hardness, flexural strength, and wear resistance). SEM, EDS, and X-RD analysis were used to perform metallographic examinations. The highest relative density with a value of 98.558% was determined in the C3 sample. The findings revealed that when the reinforcement ratio was raised, the hardness rose. The highest hardness value was observed in the C6 sample with an increase of 12.52%. Sample C4 (with the lowest SiC and WC particles ratio) had the highest bending stress (233.18 MPa). Bending stress increased by 35.56% compared to the C1 sample. The lowest specific wear rates were found in the C4 sample, with a decrease of 82.57% compared to the C1 sample. The lowest wear rate (6.853 × 10-7 mm3/Nm) also occurred in the C4 sample. The microstructural analysis showed that the hybrid reinforcement particles exhibited a homogeneous distribution in the copper matrix. X-RD analysis showed that there was no intermediate reaction between the parent matrix and the hybrid reinforcements. A good interfacial bond was observed between the matrix structure and the hybrid reinforcements. The motivation of this research was to utilise the advantages of the unique features of SiC-WC hybrid particles to improve the performance of newly developed Cu-6Gr composites for wear-resistance applications.

Recent Advances in Bipedal Walking Robots: Review of Gait, Drive, Sensors and Control Systems.

Currently, there is an intensive development of bipedal walking robots. The most known solutions are based on the use of the principles of human gait created in nature during evolution. Modernbipedal robots are also based on the locomotion manners of birds. This review presents the current state of the art of bipedal walking robots based on natural bipedal movements (human and bird) as well as on innovative synthetic solutions. Firstly, an overview of the scientific analysis of human gait is provided as a basis for the design of bipedal robots. The full human gait cycle that consists of two main phases is analysed and the attention is paid to the problem of balance and stability, especially in the single support phase when the bipedal movement is unstable. The influences of passive or active gait on energy demand are also discussed. Most studies are explored based on the zero moment. Furthermore, a review of the knowledge on the specific locomotor characteristics of birds, whose kinematics are derived from dinosaurs and provide them with both walking and running abilities, is presented. Secondly, many types of bipedal robot solutions are reviewed, which include nature-inspired robots (human-like and birdlike robots) and innovative robots using new heuristic, synthetic ideas for locomotion. Totally 45 robotic solutions are gathered by thebibliographic search method. Atlas was mentioned as one of the most perfect human-like robots, while the birdlike robot cases were Cassie and Digit. Innovative robots are presented, such asslider robot without knees, robots with rotating feet (3 and 4 degrees of freedom), and the hybrid robot Leo, which can walk on surfaces and fly. In particular, the paper describes in detail the robots' propulsion systems (electric, hydraulic), the structure of the lower limb (serial, parallel, mixed mechanisms), the types and structures of control and sensor systems, and the energy efficiency of the robots. Terrain roughness recognition systems using different sensor systems based on light detection and ranging or multiple cameras are introduced. A comparison of performance, control and sensor systems, drive systems, and achievements of known human-like and birdlike robots is provided. Thirdly, for the first time, the review comments on the future of bipedal robots in relation to the concepts of conventional (natural bipedal) and synthetic unconventional gait. We critically assess and compare prospective directions for further research that involve the development of navigation systems, artificial intelligence, collaboration with humans, areas for the development of bipedal robot applications in everyday life, therapy, and industry.

Evaluation of the Mechanical Properties and Drilling of Glass Bead/Fiber-Reinforced Polyamide 66 (PA66)-Based Hybrid Polymer Composites.

In this study, mechanical testing of glass bead (GB), glass fiber (GF), and hybrid (GB/GF) composites was carried out. Following that, drilling tests were undertaken on glass bead/fiber-reinforced hybrid Polyamide 66 (PA66) polymer composites. The purpose of this study is to determine the mechanical properties of the cutting elements and the effect of cutting parameters (spindle speed and feed rate) and reinforcement ratios on thrust force and surface roughness (Ra). The contribution of the cutting parameters to the investigated outcomes was determined using statistical analysis. Optical microscopy and scanning electron microscopy (SEM) was used to inspect the hole quality and damage mechanisms. The results revealed that the feed rate was the most contributing factor to thrust force (96.94%) and surface roughness (63.59%). Furthermore, in comparison to other hybrid composites, the lowest Ra value was obtained as 0.95 µm in samples containing 30% GB, while the Ra value was 1.04 µm in samples containing 10% GF + 20% GB. Polymer PA reinforced with 30% GF had the highest strength, modulus of elasticity, impact strength, and hardness.

Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloy.

Shape memory alloy (SMA), particularly those having a nickel-titanium combination, can memorize and regain original shape after heating. The superior properties of these alloys, such as better corrosion resistance, inherent shape memory effect, better wear resistance, and adequate superelasticity, as well as biocompatibility, make them a preferable alloy to be used in automotive, aerospace, actuators, robotics, medical, and many other engineering fields. Precise machining of such materials requires inputs of intellectual machining approaches, such as wire electrical discharge machining (WEDM). Machining capabilities of the process can further be enhanced by the addition of Al2O3 nanopowder in the dielectric fluid. Selected input machining process parameters include the following: pulse-on time (Ton), pulse-off time (Toff), and Al2O3 nanopowder concentration. Surface roughness (SR), material removal rate (MRR), and recast layer thickness (RLT) were identified as the response variables. In this study, Taguchi's three levels L9 approach was used to conduct experimental trials. The analysis of variance (ANOVA) technique was implemented to reaffirm the significance and adequacy of the regression model. Al2O3 nanopowder was found to have the highest contributing effect of 76.13% contribution, Ton was found to be the highest contributing factor for SR and RLT having 91.88% and 88.3% contribution, respectively. Single-objective optimization analysis generated the lowest MRR value of 0.3228 g/min (at Ton of 90 µs, Toff of 5 µs, and powder concentration of 2 g/L), the lowest SR value of 3.13 µm, and the lowest RLT value of 10.24 (both responses at Ton of 30 µs, Toff of 25 µs, and powder concentration of 2 g/L). A specific multi-objective Teaching-Learning-Based Optimization (TLBO) algorithm was implemented to generate optimal points which highlight the non-dominant feasible solutions. The least error between predicted and actual values suggests the effectiveness of both the regression model and the TLBO algorithms. Confirmatory trials have shown an extremely close relation which shows the suitability of both the regression model and the TLBO algorithm for the machining of the nanopowder-mixed WEDM process for Nitinol SMA. A considerable reduction in surface defects owing to the addition of Al2O3 powder was observed in surface morphology analysis.

Hand and Abrasive Flow Polished Tungsten Carbide Die: Optimization of Surface Roughness, Polishing Time and Comparative Analysis in Wire Drawing.

This research work highlights the benefits of abrasive flow polishing (AFP) applied to tungsten carbide dies compared with conventional hand polishing (HP). An indigenous experimental set-up for AFP was developed. The effect of prominent process parameters viz. extrusion pressure, number of cycles, and abrasive particle concentration on the final surface roughness, percentage improvement in surface roughness, and polishing time was investigated by Taguchi-designed experiments. The multi-objective optimization (MOO) was performed using the Taguchi-TOPSIS-Equal weight approach to find the respective optimized AFP parametric settings. A set of skilled operators performed the conventional HP of dies, and the best hand-polished (HPed) die was selected using the TOPSIS technique. The operational performance of the HPed dies and the abrasive flow polished (AFPed) dies were compared on the three-stage wire drawing operation. The results revealed that AFP's surface resulted in a better-quality surface than hand polishing with a 27.06% improvement in surface roughness. Furthermore, AFP can reduce the dependency on costly and tricky-to-locate skilled operators, with a reasonable amount of time saving (about 87.05%). Overall, the study's findings show that abrasive flow polishing of dies is fast and cost-effective.

Development of an Oxide Layer on Al 6061 Using Plasma Arc Electrolytic Oxidation in Silicate-Based Electrolyte.

The plasma electrolytic method is one of the techniques which can be used to form an oxide layer on the substrate material surface. This technique employs ion exchange by developing an electrolytic arc between the cathode and the anode. The strong bond at high temperatures promotes the formation of an oxide layer on the metal surface. The electrolyte composition has a strong influence on the metal surface characteristics. Hence, the addition of certain nanoparticles in an adequate amount can improve the surface properties like wear and corrosion resistance. In this study, a plasma electrolytic technique based on using a direct current and voltage approach is investigated. The plasma electrolytic technique is utilized to develop an oxide layer on the Al 6061 alloy substrate surface using a DC voltage input on a silicate-based electrolyte. The substrate surface is then investigated for the thickness of the oxide layer formed and the amount of carbon element absorbed, using the SEM and XRD analysis. The experimentation and the study of the results confirmed the presence of a substantial oxide layer on the surface. The influence of the process on the output parameters-direct voltage and electrode distance is studied with the significant changes obtained in the weight percentage of elements like C, Al, Si, and O as supported by SEM and EDAX analysis. Most changes occurred when using a 197 V and in the current range of 0.3 A to 1 A. This can be useful further to improve the mechanical properties of the metal alloy using the plasma arc oxidation method.

A Soft Computing-Based Analysis of Cutting Rate and Recast Layer Thickness for AZ31 Alloy on WEDM Using RSM-MOPSO.

In the present research, the AZ31 alloy is machined by wire-cut electric discharge machining (WEDM). The experiments were designed according to the Box-Behnken design (BBD) of response surface methodology (RSM). The input process variables, namely servo feed (SF), pulse on-time (Ton), servo voltage (SV), and pulse off-time (Toff), were planned by BBD, and experiments were performed to investigate the cutting rate (CR) and recast layer thickness (RCL). The analysis of variance (ANOVA) was performed to determine the influence of machining variables on response characteristics. The empirical models developed for CR and RCL were solved using Multi-Objective Particle Swarm Optimization (MOPSO). Pareto optimal front is used for the collective optimization of CR and RCL. The optimal solution suggested by the hybrid approach of RSM-MOPSO is further verified using a confirmation test on the random setting indicated by the hybrid algorithm. It is found that the minimum RCL (6.34 µm) is obtained at SF: 1700; SV: 51 V; Toff: 10.5 µs; and Ton: 0.5 µs. However, maximum CR (3.18 m/min) is predicted at SF: 1900; SV: 40 V; Toff: 7 µs; and Ton: 0.9 µs. The error percentage of ±5.3% between the experimental results and predicted solutions confirms the suitability of the proposed hybrid approach for WEDM of AZ31.

Study of a Multicriterion Decision-Making Approach to the MQL Turning of AISI 304 Steel Using Hybrid Nanocutting Fluid.

The enormous use of cutting fluid in machining leads to an increase in machining costs, along with different health hazards. Cutting fluid can be used efficiently using the MQL (minimum quantity lubrication) method, which aids in improving the machining performance. This paper contains multiple responses, namely, force, surface roughness, and temperature, so there arises a need for a multicriteria optimization technique. Therefore, in this paper, multiobjective optimization based on ratio analysis (MOORA), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and technique for order of preference by similarity to ideal solution (TOPSIS) are used to solve different multiobjective problems, and response surface methodology is also used for optimization and to validate the results obtained by multicriterion decision-making technique (MCDM) techniques. The design of the experiment is based on the Box-Behnken technique, which used four input parameters: feed rate, depth of cut, cutting speed, and nanofluid concentration, respectively. The experiments were performed on AISI 304 steel in turning with minimum quantity lubrication (MQL) and found that the use of hybrid nanofluid (Alumina-Graphene) reduces response parameters by approximately 13% in forces, 31% in surface roughness, and 14% in temperature, as compared to Alumina nanofluid. The response parameters are analyzed using analysis of variance (ANOVA), where the depth of cut and feed rate showed a major impact on response parameters. After using all three MCDM techniques, it was found that, at fixed weight factor with each MCDM technique, a similar process parameter was achieved (velocity of 90 m/min, feed of 0.08 mm/min, depth of cut of 0.6 mm, and nanoparticle concentration of 1.5%, respectively) for optimum response. The above stated multicriterion techniques employed in this work aid decision makers in selecting optimum parameters depending upon the desired targets. Thus, this work is a novel approach to studying the effectiveness of hybrid nanofluids in the machining of AISI 304 steel using MCDM techniques.

Integration of Fuzzy AHP and Fuzzy TOPSIS Methods for Wire Electric Discharge Machining of Titanium (Ti6Al4V) Alloy Using RSM.

Titanium and its alloys exhibit numerous uses in aerospace, automobile, biomedical and marine industries because of their enhanced mechanical properties. However, the machinability of titanium alloys can be cumbersome due to their lower density, high hardness, low thermal conductivity, and low elastic modulus. The wire electrical discharge machining (WEDM) process is an effective choice for machining titanium and its alloys due to its unique machining characteristics. The present work proposes multi-objective optimization of WEDM on Ti6Al4V alloy using a fuzzy integrated multi-criteria decision-making (MCDM) approach. The use of MCDM has become an active area of research due to its proven ability to solve complex problems. The novelty of the present work is to use integrated fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal situation (TOPSIS) to optimize the WEDM process. The experiments were systematically conducted adapting the face-centered central composite design approach of response surface methodology. Three independent factors-pulse-on time (Ton), pulse-off time (Toff), and current-were chosen, each having three levels to monitor the process response in terms of cutting speed (VC), material removal rate (MRR), and surface roughness (SR). To assess the relevance and significance of the models, an analysis of variance was carried out. The optimal process parameters after integrating fuzzy AHP coupled with fuzzy TOPSIS approach found were Ton = 40 µs, Toff = 15 µs, and current = 2A.

Analysis and Optimization of Dimensional Accuracy and Porosity of High Impact Polystyrene Material Printed by FDM Process: PSO, JAYA, Rao, and Bald Eagle Search Algorithms.

High impact polystyrene (HIPS) material is widely used for low-strength structural applications. To ensure proper function, dimensional accuracy and porosity are at the forefront of industrial relevance. The dimensional accuracy cylindricity error (CE) and porosity of printed parts are influenced mainly by the control variables (layer thickness, shell thickness, infill density, print speed of the fused deposition modeling (FDM) process). In this study, a central composite design (CCD) matrix was used to perform experiments and analyze the complete insight information of the process (control variables influence on CE and porosity of FDM parts). Shell thickness for CE and infill density for porosity were identified as the most significant factors. Layer thickness interaction with shell thickness, infill density (except for CE), and print speed were found to be significant for both outputs. The interaction factors, i.e., shell thickness and infill density, were insignificant (negligible effect) for both outputs. The models developed produced a better fit for regression with an R2 equal to 94.56% for CE, and 99.10% for porosity, respectively. Four algorithms (bald eagle search optimization (BES), particle swarm optimization (PSO), RAO-3, and JAYA) were applied to determine optimal FDM conditions while examining six case studies (sets of weights assigned for porosity and CE) focused on minimizing both CE and porosity. BES and RAO-3 algorithms determined optimal conditions (layer thickness: 0.22 mm; shell thickness: 2 mm; infill density: 100%; print speed: 30 mm/s) at a reduced computation time equal to 0.007 s, differing from JAYA and PSO, which resulted in an experimental CE of 0.1215 mm and 2.5% of porosity in printed parts. Consequently, BES and RAO-3 algorithms are efficient tools for the optimization of FDM parts.

Optimization and Modeling of Material Removal Rate in Wire-EDM of Silicon Particle Reinforced Al6061 Composite.

The mechanical, physical and interfacial properties of aluminum alloys are improved by reinforcing the silicon carbide particles (SiCp). Machinability of such alloys by traditional methods is challenging due to higher tool wear and surface roughness. The objective of research is to investigate the machinability of SiCp reinforced Al6061 composite by Wire-Electrical Discharge Machining (wire-EDM). The effect of wire-EDM parameters namely current (I), pulse-on time (Ton), wire-speed (Ws), voltage (Iv) and pulse-off time (Toff) on material removal rate (MRR) is investigated and their settings are optimized for achieving the high MRR. The experiments are designed by using Taguchi L16 orthogonal arrays. The MRR obtained at different experiments are analyzed using statistical tools. It is observed that all the chosen process parameters showed significant influence of on the MRR with contribution of 27.39%, 22.08%, 21.32%, 15.76% and 12.94% by I, Iv, Toff, Ton and Ws, respectively. At optimum settings, the Wire-EDM resulted in MRR of 65.21 mg/min and 62.41 mg/min for samples with 4% and 8% SiCp. The results also indicated reinforcing SiCp upto 8% showed marginally low influence on MRR. Microstructural investigation of the cut surface revealed the presence of craters with wave pattern on its surface. The top surface of the crater is featured by the recast layers connecting adjacent craters. Further, the statistical model is developed using linear regression to predict the MRR (?2-73.65%) and its predicting accuracy is verified by the confirmation trials. The statistical model is useful for predicting the MRR for different settings of the process parameters. The optimized settings can be used to improve the machining productivity by increasing the MRR while machining of Al6061-SiCp (upto 8 wt. %) alloy by wire-EDM industries.

Corrosion Resistance and Surface Bioactivity of Ti6Al4V Alloy after Finish Turning under Ecological Cutting Conditions.

The influence of cooling conditions and surface topography after finish turning of Ti6Al4V titanium alloy on corrosion resistance and surface bioactivity was analyzed. The samples were machined under dry and minimum quantity lubrication (MQL) conditions to obtain different surface roughness. The surface topographies of the processed samples were assessed and measured using an optical profilometer. The produced samples were subjected to electrochemical impedance spectroscopy (EIS) and corrosion potential tests (Ecorr) in the presence of simulated body fluid (SBF). The surface bioactivity of the samples was assessed on the basis of images from scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) analysis. The inspection of the surfaces of samples after turning under dry and MQL conditions revealed unevenly distributed precipitation of hydroxyapatite compounds (Ca/P) with a molar ratio in the range of 1.73-1.97. Regardless of the cutting conditions and surface roughness, the highest values of Ecorr ~0 mV were recorded on day 7 of immersion in the SBF solution. The impedance characteristics showed that, compared to the MQL conditions, surfaces machined under dry conditions were characterized by greater resistance and the presence of a passive layer on the processed surface. The main novelty of the paper is the study of the effect of ecological machining conditions, namely, dry and MQL cutting on the corrosion resistance and surface bioactivity of Ti6Al4V titanium alloy after finish turning. The obtained research results have practical significance. They can be used by engineers during the development of technological processes for medical devices made of Ti6Al4V alloy to obtain favorable functional properties of these devices.

Elucidating the Effect of Step Cooling Heat Treatment on the Properties of 2.25 Cr-1.0 Mo Steel Welded with a Combination of GMAW Techniques Incorporating Metal-Cored Wires.

The prospect of using metal-cored wires instead of solid wires during gas metal arc welding (GMAW) of 2.25 Cr-1.0 Mo steels embraces several challenges. The in-service requirements for the equipment made up of these steels are stringent. The major challenge faced by the manufacturers is temper embrittlement. In the current study, the temper embrittlement susceptibility of the welded joint was ascertained by subjecting it to step cooling heat treatment. A 25 mm thick 2.25 Cr-1.0 Mo weld joint was prepared using a combination of the regulated metal deposition (RMD) and GMAW processes incorporating metal-cored wires. After welding the plates were exposed to post-weld heat treatment followed by a rigorous step cooling heat treatment prescribed by API standards. The temper embrittlement susceptibility of the weld joint was ascertained by Bruscato X-factor as well as by formulating ductile-to-brittle transition temperature (DBTT) curves by carrying out the impact toughness testing at various temperatures. Detailed microscopy and hardness studies were also carried out. It was established from the study that the X-factor value for the welded joint was 15.4. The DBTT for the weld joint was found to occur at -37 °C which was well below 10 °C. Optical microscopy and scanning electron microscopy indicated the presence of carbides and the energy dispersive X-ray spectrometry studies indicated the presence of chromium and manganese-rich carbides along with the presence of sulfur near the grain boundaries. This study establishes a base for the usage of metal-cored wires particularly in high temperature and pressure application of Cr-Mo steels.

Towards Analysis and Optimization for Contact Zone Temperature Changes and Specific Wear Rate of Metal Matrix Composite Materials Produced from Recycled Waste.

Tribological properties are important to evaluate the in-service conditions of machine elements, especially those which work as tandem parts. Considering their wide range of application areas, metal matrix composites (MMCs) serve as one of the most significant materials equipped with desired mechanical properties such as strength, density, and lightness according to the place of use. Therefore, it is crucial to determine the wear performance of these materials to obtain a longer life and to overcome the possible structural problems which emerge during the production process. In this paper, extensive discussion and evaluation of the tribological performance of newly produced spheroidal graphite cast iron-reinforced (GGG-40) tin bronze (CuSn10) MMCs, including optimization, statistical, graphical, and microstructural analysis for contact zone temperature and specific wear rate, are presented. For this purpose, two levels of production temperature (400 and 450 °C), three levels of pressure (480, 640, and 820 MPa), and seven different samples reinforced by several ingredients (from 0 to 40 wt% GGG-40, pure CuSn10, and GGG-40) were investigated. According to the obtained statistical results, the reinforcement ratio is remarkably more effective on contact zone temperature and specific wear rate than temperature and pressure. A pure CuSn10 sample is the most suitable option for contact zone temperature, while pure GGG-40 seems the most suitable material for specific wear rates according to the optimization results. These results reveal the importance of reinforcement for better mechanical properties and tribological performance in measuring the capability of MMCs.