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The ultra-thin white topping (UTW) is a cement concrete overlay of the thickness of 50–100 mm on bituminous concrete pavements with surface failures. This is a long-lasting solution without having short-term failures. This paper aims to design an ultra-thin cement concrete overlay using a developed critical stress model with sustainable concrete materials for low-volume roads.

In this research paper, a parametric study was conducted using the ultra-thin concrete overlay finite element model developed with ANSYS software, considering the significant parameters affecting the performance and development. The non-linear regression equation was formed using a damped least-squares method to predict critical stress due to the corner load of 51 kN.

The parametric study results indicate that with a greater elastic modulus of bituminous concrete, granular layer along with 100 mm thickness of concrete layer reduces the critical corner stress, interface shear stress in a significant way responsible for debonding of concrete overlay, elastic strains in the pavement further the concrete overlay can bear infinite load repetitions. From validation, it is understood that the non-linear regression equation developed is acceptable with similar research work done.

From the semi-scale experimental study, it is observed that the quaternary blended sustainable concrete overlay having a high modulus of rupture of 6.34 MPa is competent with conventional cement concrete overlay in terms of failure load. So, concrete overlay with sustainable materials of 100 mm thickness and higher elastic modulus of the layers can perform in a sustainable way meeting the environmental and long-term performance requirements.

The purpose of this study is to select a proper surface treatment to enhance wear resistance of engine camshafts. The camshaft is a relevant part of a diesel engine which works under torsion, fatigue and wear efforts. They are usually manufactured by casting, forging or machining from forged bar of low alloy steels, and in most cases, the machined surfaces are quenched and tempered by induction heating. After that, in many cases, to withstand the efforts imposed on the active surfaces and improve tribology and fatigue properties, the industry used for decades, thermochemical technologies such as salt bath or gaseous nitriding and nitrocarburizing processes.

This paper studied the effects of plasma nitriding and plasma nitrocarburizing, on the tribological behaviour of the steel SAE 1045HM3 proposed to produce camshafts. After the plasma treatments, the change in surface roughness was measured; the modified layers were studied by X-ray techniques and its thickness by optical microscopy. The diffusion zone was evaluated by Vickers microhardness determinations. Tribology tests were performed by pin-on-disc configuration using WC ball as a counterpart.

Results show that plasma nitrided samples present the best tribological behaviour compared with the nitrocarburized ones; also, the influence of the roughness produced by the thermochemical processes appears to be important.

Although both the plasma treatments have been applied for many years, and also reported separately in the scientific literature, there was no information comparing these two treatments for carbon steels, and also, there is not much about tribology in lubricated conditions of nitrided and nitrocarburized carbon steels. In fact, it is not proved that the porosity of the nitrocarburized layer is beneficial for wear resistance in lubricated conditions. In this paper, it was proved that at least in the tested conditions, it is not.

Gas or plasma nitrocarburizing is usually recommended for this kind of applications, although the modified layer is porous. This paper attempts to prove that nitriding could be better than nitrocarburizing, even with a thinner white layer.

Electrical discharge machining (EDM) of hard materials like NiTi 60 alloys is important as it finds application in different sectors of engineering such as automobile, aircraft, biomedical, oil industries, etc.

The first target of this investigation is to determine the effect of process parameters such as current, voltage, pulse on time and pulse off time on the material removal rate (MRR), surface roughness (SR) and white layer formation (WLT) for NiTi 60 smart material alloy. The secondary aim is to identify the presence of surface integrity parameters such as cracks, WLT, microvoids, globules and debris formation by using the scanning electron microscopy technique and with the use of ImageJ software for die sink EDM machining of NiTi 60 alloy.

The results reveal that current is significant for MRR, voltage and current influence SR, and for WLT, voltage is a significant factor. The experimentation study also shows the generation of oxide and carbide layers on the machined surface, which were evident with the use of the X-ray diffraction technique. The presence of these oxide and carbide layers causes to form WLT on the machined surface and thereby increases the hardness of the machined surface.

Hardness test was performed with Vickers hardness tester, which gives evidence for the increase in hardness of machined surface due to the generation of WLT.

The purpose of this paper is to analyze the surface integrity, including recast layer thickness, surface crack density, X-ray diffractions study and microhardness for Ni53.49Ti46.51 shape memory alloy (SMA) during wire-spark erosion machining.

Four persuasive process parameters, that is, spark on time (SON), spark off time (SOFF), wire feed (WF) and spark gap voltage (SV), have been chosen for the current investigation. Efforts have been done to explore the effects of above said parameters on the machined surface of Ni-Ti SMA by embracing box Behnken design of response surface methodology (RSM). Cutting speed and ten-point mean roughness (Rz) has been taken into account as response variables. Analysis of variance test was also performed for both response parameters with the coefficient of determination (R²) 0.9610 for cutting speed and 0.9252 for ten-point mean Rz.

The recast layer thickness from 7.83 to 12.13 µm was developed near the machined surface at different parametric settings. The least surface crack density was found at the lowest value of ten-point mean Rz, while most surface crack density was identified at the highest value of cutting speed. The microhardness near the machined surface was increased by approximately 1.8 times bulk-hardness of Ni53.49Ti46.51 SMA.

Some researchers have done a study on average surface roughness, but very few investigators concentrated on ten-point mean Rz. Surface crack density is an essential aspect of machined parts; other researchers have seldom reported it. The novelty of this research work is that the influence of SON, SV, WF and SOFF on cutting speed, Rz, recast layer thickness, micro-hardness and surface crack density proximate the machined surface while machining workpiece material.

The purpose of this paper is to investigate prediction and optimization of multiple performance characteristics in the wire electrical discharge machining (wire-EDM) process of SKD 61 (AISI H13) tool steel.

The experimental studies were conducted under varying wire-EDM process parameters, which were arc on time, on time, open voltage, off time and servo voltage. The optimized responses were recast layer thickness (RLT), surface roughness (SR) and surface crack density (SCD). Arc on time was set at two different levels, whereas the other four parameters were set at three different levels. Based on Taguchi method, an L18 mixed-orthogonal array was selected for the experiments. Further, three methods, namely grey relational analysis (GRA), backpropagation neural network (BPNN) and genetic algorithm (GA), were applied separately. GRA was performed to obtain a rough estimation of optimum drilling parameters. The influences of drilling parameters on multiple performance characteristics were determined by using percentage contributions. BPNN architecture was determined to predict the multiple performance characteristics. GA method was then applied to determine the optimum wire-EDM parameters.

The minimum RLT, SR and SCD could be obtained by setting arc on time, on time, open voltage, off time and servo voltage at 2 ms, 3 ms, 90 volt, 10 ms and 38 volt, respectively. The experimental confirmation results showed that BPNN-based GA optimization method could accurately predict and significantly improve all of the responses.

There were no publications regarding multi-response optimization using a combination of GRA and BPNN-based GA methods during wire-EDM process available.

Inconel 718 (IN718) is a high-performance nickel-based superalloy with high oxidation-corrosion-temperature resistance, high strength (tensile, fatigue, creep and rupture), durability, toughness, hardness and dimensional stability, which is difficult to machine with traditional fabrication methods. To overcome these difficulties, wire electrical discharge machining (WEDM), one of the modern manufacturing methods, is used.

Main performance criteria in WEDM; material removal rate (MRR), cutting speed, surface roughness, cutting width (kerf) and wire wear rate. In this study, the effect of processing parameters on kerf and MRR because of processing IN718 in WEDM was investigated. Machining parameters, voltage, wire feed rate and dielectric fluid pressure were determined. Deionized water was used as a dielectric fluid and 0.3 mm brass wire was used as wire in the experiments. Gray Relational Analysis (GRA), which is one of the multi-criteria decision-making methods, has been applied for the optimization of the machining parameters in the cutting process with the WEDM. Analysis of variance (ANOVA) was used to determine the effect percentages of the cut-off parameters.

The parameter with the highest effect was determined as tension with a rate of 76.95% for kerf and 91.21% for MRR.

The novel approach uses Taguchi-based GRA optimization as a result of cutting IN718 with WEDM, reducing cost and time consumption.

Electrical discharge machining (EDM) is well-known for its credibility in the processing of advanced materials, which are electrically conductive. The strenuous effort associated with machining of Ti6Al4V (Ti64) using conventional methods, and its low tribological behavior, present an immediate need to develop solutions to monitor and improve the compatible techniques such as EDM.

The present work includes following: monitoring the ED process parameters, namely, current (I) and pulse on time (T_on), in controlling the material removal rate and surface roughness (R_a and S_a) for development of tribo-adaptive surfaces; and investigation on the role of oxides pertinent to the tribo-behavior of Ti64 (bare and EDMed) surfaces.

The tribological behavior of Ti6Al4V surfaces got remarkably improved through ED machining, which points to the credibility of the process to establish itself as a surface alloying technique. The recast layer (RL, alloyed matrix) acted as a protective coating; stable enough to assist the developed tribo-oxides such as TiO and Ti₈O₁₅ in rendering improved sliding performance at load = 50 N and speed = 0.838 ms⁻¹.

The surface modification through ED machining was experimentally proven to improve the wear behavior of Ti6Al4V surfaces.

To meet the requirements of high-dimensional accuracy and surface finish of various advanced engineering materials for generating intricate part geometries, non-traditional machining (NTM) processes have now become quite popular in manufacturing industries. To explore the fullest machining capability of these NTM processes, it is often required to operate them while setting their different controllable parameters at optimal levels. This paper aims to present a novel approach for selection of the optimal parametric mixes for different NTM processes in order to assist the concerned process engineers.

In this paper, design of experiments (DoE) and technique for order preference by similarity to ideal solution (TOPSIS) are combined to develop the corresponding meta-models for identifying the optimal parametric combinations of two NTM processes, i.e. electrical discharge machining (EDM) and wire electrical discharge machining (WEDM) processes with respect to the computed TOPSIS scores.

For EDM operation on Inconel 718 alloy, lower settings of open circuit voltage and pulse-on time and higher settings of peak current, duty factor and flushing pressure will simultaneously optimize all the six responses. On the other hand, for the WEDM process, the best machining performance can be expected to occur at a parametric combination of zinc-coated wire, lower settings of pulse-on time, wire feed rate and sensitivity and intermediate setting of pulse-off time.

As the development of these meta-models is based on the analysis of the experimental data, they are expected to be more practical, being immune to the introduction of additional parameters in the analysis. It is also observed that the derived optimal parametric settings would provide better values of the considered responses as compared to those already determined by past researchers.

This DoE–TOPSIS method-based approach can be applied to varieties of NTM as well as conventional machining processes to determine the optimal parametric combinations for having their improved machining performance.

In the current exploration, the machinability of three different nickel-based super-alloy materials (Inconel 625, Inconel 718 and Nimonic 90) was experimentally investigated by using a die-sinking electrical discharge machining (EDM). The effect of changing important input process parameters such as pulse on time (T_on), off time (T_off), peak current (Ip) and tool rotation (TR) was investigated to get optimum machining characteristics such as material removal rate, roughness, electrode wear rate and overcut.

Experimentation has been performed by using Taguchi L9 orthogonal design. An integrated route of fuzzy and grey relational analysis approach with Taguchi’s philosophy has been intended for the simultaneous optimization of machining output parameters.

The most approbatory factors for machining setting have been attained as: (T_on = 100 µs, T_off = 25 µs, Ip = 14 A, TR = 725 rpm) for machining of Inconel 625 and Inconel 718; and (T_on = 100 µs, T_off = 75 µs, Ip = 14 A, TR = 925 rpm) for machining of the Nimonic 90 material. Peak current has been observed as an overall influencing factor to achieve better machining process. Microstructural study through SEM has also been carried out to figure out the surface morphology for the EDMed Ni-based super alloys.

The proposed machining variables and methodology has never been presented for Nimonic 90 alloy on die-sinking EDM.

In this study, powder mixed electro discharge machining (PMEDM) has been performed for the machining of AISI 304 stainless steel by using the tungsten carbide electrode when silicon carbide (SiC) powder is mixed with kerosene. The purpose of this study is to find the optimal value and ascertain the effect of significant machining parameters on surface crack density (SCD) of a machined surface of AISI 304.

A face-centered central composite design-based response surface methodology has been adopted for designing this experiment.

An increase in peak current and powder concentration decreases SCD, which is the main goal of this investigation.

From this investigation, an optimal value has been achieved to minimize the SCD and prevent fatigue and corrosion resistance of the workpiece.