K. Soorya Prakash

Dry sliding wear characterization of Al 6061/rock dust composite

Abstract The influence of rock dust size (10–30 µm) and mass fraction (5%–15%) on density, hardness and dry sliding wear behavior of Al 6061/rock dust composite processed through stir casting was investigated. Wear behavior of the developed composite was characterized at different loads, sliding velocities and distances using pin-on-disc setup. The experiments were conducted based on Taguchis L27 orthogonal array and the influence of process parameters on wear rate was studied using ANOVA. The experimental results reveal that the applied load and reinforcement size are the major parameters influencing the specific wear rate for all samples, followed by mass fraction of reinforcement, sliding velocity and sliding distance at the level of 47.61%, 28.57%, 19.04%, 9.52% and 4.76%, respectively. The developed regression equation was tested for its accuracy and made evident that it can be used for predicting the wear rate with minimal error. With the help of SEM images, the worn surfaces of the novel composite were studied and the analysis proves that the wear resistance of aluminium alloys can be well improved with the addition of rock dust as reinforcement.

Investigations on the effect of friction stir processing on Cu-BN surface composites

ABSTRACT The main aim of this investigation focuses on fabrication of copper surface composites through friction stir processing (FSP) reinforced with boron nitride (BN) particles of varying volume fractions (5%, 10%, and 15%). Surface composites developed through single pass FSP were characterized for its microstructural, mechanical and tribological properties. Microstructural characterization indicated that developed surface composites were of good quality with reduced grain size and the SEM characterization confirmed good bonding between copper matrix and BN with uniform dispersion. Micro hardness survey of the developed surface composites showcased minimal deviation in the stir zone with increased trend in respect to the volume fraction of BN. The ultimate tensile strength, yield strength and percent elongation of FSPed composites was found to have reduced when compared with that of pure copper. BN dispersion in surface composite was effective in reducing the ductility and so maximum volume percent (15%) of BN dispersed composite prompt to have higher strength. The wear rate and friction coefficient of the developed surface composite was found decreasing with respect to increase in the dispersion of BN. Amongst the FSPed copper surface composite, specimen with 15 vol% of BN has shown the least wear rate with low coefficient of friction.

Investigation on the emission quality, performance and combustion characteristics of the compression ignition engine fueled with environmental friendly corn oil methyl ester - Diesel blends.

This paper deals with emission quality of diesel engine based on eco toxicological studies with different methods of environmental standard toxicity tests satisfy the Bharath and European emission norms. Based on the emission norms, Corn Oil Methyl Ester (COME) with diesel is tested in a compression ignition engine and the performance and combustion characteristics are discussed. The corn oil was esterified and the property of corn oil methyl ester was within the limits specified in ASTM D 6751-03. The COME was blended together with diesel in different proportion percentages along with B20, B40, B60, B80, and B100. The emission and performance tests for various blends of COME was carried out using single cylinder, four stroke diesel engine, and compared with the performance obtained with 100% diesel (D100). The results give clear information that COME has low exhaust emissions and increase in performance compared to D100 without any modifications. It gives better performance, which is nearer to the obtained results of D100. Specific Fuel Consumption (SFC) of B100 at the full load condition is found to be 4% lower than that of (D100). The maximum Brake Thermal Efficiency (BTE) of B100 is found to be 8.5% higher than that of the D100 at full load. Also, the maximum BTE of part load for different blends is varied from 5.9% to 7.45% which is higher than D100. The exhaust gas emissions like Carbon Monoxide (CO), Carbon Dioxide (CO2), Hydro Carbon (HC) and Nitrogen Oxide (NOx) are found to be 2.3 to 18.8% lower compared to D100 for part as well as full load. The heat release rate of biodiesel and it blends are found to 16% to 35% lower as compared to D100 for part load, where as for full load it is 21% lower than D100. The results showed that the test of emissions norms are well within the limits of Bharath VI and European VI and it leads to less pollution, less effect on green eco system and potential substitute to fossil fuels.

WEDM of Mg/CRT/BN composites: Effect of materials and machining parameters

ABSTRACT The current work presents a detailed exploration on real-time wire electric discharge machining (WEDM) experiments and grey relational analysis (GRA)–based multi-criteria optimization of material and machining characteristics for lowered surface roughness (Ra) and improvised material removal rate (MRR) of the newly developed magnesium/boron nitride/cathode ray tube (Mg/BN/CRT) hybrid metal matrix composites (MMCs). The composites were fabricated through powder metallurgy (PM) route by reinforcing silica-rich E-waste CRT panel glass powder crushed for different particle sizes (10, 30, and 50 µm) at various weight percentages (5%, 10%, and 15%) and with 2% boron nitride (BN). Taguchi-based orthogonal array procedure was utilized to formulate the experimental plan for WEDM considering reinforcement level and size, pulse on time (Pon), pulse off time (Poff), and wire feed (Wf) as the input process parameters. ANOVA results reveal that Pon and wt% of reinforcement has more effect on Ra and MRR than any other considered parameters. The developed mathematical model for Ra and MRR predicted values similar to that of experimental results. Multi-criteria optimization was done through GRA technique and the so recommended optimum parameter set furnishes higher MRR (22.34 mm3/min) and reduced Ra (2.87 µm).

Parametric optimization of dry sliding wear loss of copper–MWCNT composites

Abstract The wear behavior of multi-walled carbon nano-tubes (MWCNTs) reinforced copper metal matrix composites (MMCs) processed through powder metallurgy (PM) route was focused on and further investigated for varying MWCNT quantity via experimental, statistical and artificial neural network (ANN) techniques. Microhardness increases with increment in MWCNT quantity. Wear loss against varying load and sliding distance was analyzed as per L16 orthogonal array using a pin-on-disc tribometer. Process parameter optimization by Taguchis method revealed that wear loss was affected to a greater extent by the introduction of MWCNT; this wear resistant property of newer composite was further analyzed and confirmed through analysis of variance (ANOVA). MWCNT content (76.48%) is the most influencing factor on wear loss followed by applied load (12.18%) and sliding distance (9.91%). ANN model simulations for varying hidden nodes were tried out and the model yielding lower MAE value with 3-7-1 network topology is identified to be reliable. ANN model predictions with R value of 99.5% which highly correlated with the outcomes of ANOVA were successfully employed to investigate individual parameters effect on wear loss of Cu–MWCNT MMCs.

Position control of industrial robotic manipulator using variable structure control system with single term Haar wavelet series method

Controlling an industrial robot is mainly a problem of dynamics. It includes nonlinearities, uncertainties and external perturbations, which should be considered in the design of control laws. In this paper, a variable structure control method with a mathematical tool is proposed and applied to nonlinear systems to solve the trajectory tracking problem for rigid robot manipulators. The aim is to implement a methodology to control errors in a controller that is robust to uncertainties in the model of the system. Variable structure theory provides the technique for the design of such a controller. The design steps are presented, first from a theoretical perspective and then applied to the control of a two degree-of-freedom manipulator. Simulation results that backed the implementation are presented followed by the experiments conducted, and then the results are presented. The conclusion is that the proposed mathematical tool with variable structure control is readily applicable to industrial robots for the robust control of positions.

WEDM process parameter optimization of FSPed copper-BN composites

ABSTRACT A systematic view on evaluating the machining characteristics of Wire Cut Electrical Discharge Machining (WEDM) employing Taguchi Method and Grey Relational Analysis based multiobjective optimization is provided in this research article. The outcome of various WEDM processing parameters including pulse discharge on time (PulseON), pulse discharge off time (PulseOFF), wire feed rate (WireFR) along with the material characteristics of varying Boron Nitride (BN) volume fractions while machining a friction stir processed (FSPed) copper-BN surface composite was investigated. The output responses considered in this research include Material Removal Rate (MRR) and Surface roughness (Ra) that was obtained from the L27 orthogonal array based on the above said input factors. ANOVA was performed, and PulseON and BN volume fraction were found most significant for MRR, while PulseON and PulseOFF influence the most in attaining minimal Ra values. Based on the obtained experimental values for MRR and Ra, a mathematical model was developed based on the control factors and was proved to be precise in predicting the output response. An optimal combination of input control factors was finalized through grey relational analysis, and the same proved to achieve the utmost MRR (20.19 mm3/min) and nominal Ra(3.01 µs) values.

Doping Effect of SiC over Graphene on Dry Sliding Wear Behaviour of Mg/SiC@r-GO MMCs and its Surface Characterization

In this research, solvent based powder metallurgy is used to develop Silicon Carbide (SiC) doped reduced Graphene Oxide(r-GO) reinforced magnesium composite. SiC was doped with r-GO with varying wt.% (10 & 20) by adopting hydrothermal method. Influence of SiC doping over r-GO in wear resistance of developed composite was investigated by pin on disc method. Taguchi based Artificial neural network (ANN) was used to attain optimal wear parameter and to study the influence of wear parameter by developing a mathematical model. From ANOVA results it has been observed that wt.% of reinforcement play an important role in governing the wear loss of fabricated MMC. The developed ANN model exhibits accuracy of about 99.9% when subjected to predict the wear loss. Formation of tribolayer and plastic deformation were notified from worn surface morphology, thus evidencing for the occurrence of delamination and oxidation wear.

Wire Electric Discharge Machining of Silica Rich E-waste CRT and BN Reinforced Hybrid Magnesium MMC

The current work presents an experimental investigation and multi objective optimization of material and WEDM machining features for better surface finish (Ra) and material removal rate (MRR) for a newly made-up Mg/BN/CRT Hybrid MMC. Powder metallurgy route is followed for composite fabrication by reinforcing silica rich E-waste CRT panel glass powder of different particle sizes (10, 30 & 50 μm) at different weight percentages (5, 10 & 15%) and a fixed quantity of 2% Boron Nitride. Reinforcement weight percentage and size, pulse ON time, pulse OFF time and wire feed are considered as process parameters to design the WEDM experiments through Taguchi based orthogonal array technique. Based on the ANOVA results it is revealed that pulse ON time and reinforcement wt. % has higher influence over Ra and MRR when compared to any other parameters considered. The predicting ability of the developed mathematical models for MRR and Ra is found superior and it predicts similar values as that of experimental results. Multi objective optimization carried over through TOPSIS selects the optimal parameter for multi response and the TOPSIS recommended optimum parameter set delivers higher MRR (22.34 mm3/min) and reduced Ra (2.87 μm).

Effect of friction stir processing and hybrid reinforcements on copper

ABSTRACT In this research, a copper based surface composite was fabricated through dispersing hybrid composite particles onto its surface through friction stir processing (FSP) technique. Optical micrographs and scanning electron microscopy images indicates finer refinement of grains and particles dispersion into matrix along with its bonding and particle separation. As per the outcomes of microhardness analysis, hardness of the developed surface composite shows increment with increase in dispersion of volume fraction of hybrid particles. Strength of the developed copper surface composite exhibited a positive trend with introduction of hybrid reinforcement particle onto the surface of the composite but yet again ductility reduced. Wear resistance of the composite increased with reinforcement addition and the same was supported through worn out surface morphology. Fluctuations in friction coefficient value reduced with increase in particles, as for the presence in BN particles while the average frictional coefficient value was observed increasing. A reduction in corrosion rate was observed with increase in reinforcement particle dispersion onto copper matrix through FSP.