Neeraj Sharma

The present research used the stir-casting method to develop an Al-based composite. The developed composite exhibited challenges while being processed on conventional machining. Thus, a non-traditional machining process was opted to process the composite. The machining variables selected for the current research were the pulse off time (Toff), pulse on time (Ton), servo voltage (SV), current (I), and tool electrode. Three tool electrodes (SS-304, copper, and brass) were used to process the developed composite (Al/SiC/Gr). The experimental plan was designed using response surface methodology (RSM). The output responses recorded for the analysis were the material removal rate (MRR) and tool wear rate (TWR). The obtained data was optimized using complex proportional assessment (COPRAS) and machine learning methods. The optimized settings predicted by the RSM–COPRAS method were Ton: 60 µs; Toff: 60 µs; SV: 7 V; I: 12 A; and tool: brass. The maximum MRR and TWR at the suggested settings were 1.11 g/s and 0.0114 g/s, respectively. A morphological investigation of the machined surface and tool surface was conducted with scanning electron microscopy. The morphological examination of the surface (machined) presented the presence of cracks, lumps, etc.

Wire electric discharge machine (WEDM) is a spark erosion non conventional machining method to cut hard and conductive material with the help of a wire electrode. High strength low alloy steel (HSLA) is a hard alloy with high hardness and wear resisting property. The purpose of this study is to investigate the effect of parameters on metal removal rate for WEDM using HSLA as work-piece and brass wire as electrode. HSLA used in cars, trucks, cranes, bridges, roller coasters and other structures that are designed to handle large amounts of stress. It is observed that metal removal rate and surface roughness increases with increase in pulse on time and peak current. Metal removal rate and surface roughness decreases with increase in pulse off time and servo voltage. Wire mechanical tension has no significant effect on metal removal rate and surface roughness. Response Surface methodology (RSM) is used to optimize the process parameter for metal removal rate and surface roughness. Response Surface Methodology is formulating a mathematical model which correlates the independent process parameters with the desired metal removal rate and surface roughness. The central composite rotatable design (CCRD) has been used to conduct the experiments.

NiTi is a shape memory alloy, mostly employed in cardiovascular stents, orthopedic implants, orthodontic wires, micro-electromechanical systems and so on. The effective and net shape machining of NiTi is very critical for excellent response of this material in medical and other applications. The present experimental work on wire electrical discharge machining process identifies the influence of process parameters that affect the cutting rate, dimensional shift and surface roughness while machining of porous nickel–titanium (Ni 40 Ti 60 ) alloy. Porous Ni 40 Ti 60 alloy was produced in-house using powder metallurgy technique. Response surface methodology–based central composite rotatable design has been used for the planning of experiments on wire electrical discharge machining. Empirical relations have been developed between the process parameters (pulse on-time, pulse off-time, servo voltage and peak current) and response variables. Desirability approach has been used for optimizing the three response variables simultaneously. Confirmation experiments were also performed at the optimized settings and reflect a close agreement between the predicted and experimental values (percentage error varies from −6.13% to +6.85%). Using wire electrical discharge machining, NiTi alloy can be machined easily and successfully in single-cutting operation, but after the first cut in wire electrical discharge machining, a surface projection appears on work surface which is the unmachined material on work surface.

Nitinol exists in equiatomic phase of nickel-titanium (Ni-Ti). Nitinol has various applications in biomedical, automotive actuators, micro-electromechanical systems (MEMSs) and aero-space industries due to its distinctive properties of pseudo-elasticity, bio-compatibility, corrosion resistance and shape memory effect. This paper presents the applications of nickel-titanium alloy in various field of engineering, medical and other area. The attractive properties of NiTi alloy has also been discussed that makes it most influential material for various applications.

Wire electric discharge machining (WEDM) is a thermo-electric spark erosion non-traditional type manufacturing process. The applications of WEDM have been found in aerospace and die manufacturing industries, where precise dimensions were the prime objective. This process is applied in case of processing difficult to machine material. Brass wire is used as an electrode and High strength low alloy (HSLA) steel as a work-piece during experimentation. The present research deals with the effect of process parameters on the overcut while machining the HSLA steel on WEDM. The mathematical model has been developed with the help of Response Surface Methodology (RSM). Further this model is processed with help of Genetic Algorithm (GA) to find out the optimum machining parameters. The percentage error between the predicted and experimental values lies in the range of ±10%, which indicates that the developed model can be utilized to predict the overcut values. The experimental plan was executed according to central composite design. The optimal setting of process parameters is pulse on-time-117 μs; pulse off-time-50 μs; spark gap voltage-49 V; peak current-180 A and wire tension-6 g; for minimum overcut, whereas at the optimal setting overcut is 9.9922 μm.

Nitinol (NiTi) is categorized as a smart material which is highly recognized material for medical and other engineering applications. The behaviour of NiTi can be modified by altering the composition, modifying the porosity and applying external thermal and mechanical treatment. Due to high composition sensitivity, there are several impediments in fabrication of NiTi with conventional techniques which impel the use of additive manufacturing methods. But due to very high cost of equipments, these processes have not been commercialized till now. This paper presents a review on applications, manufacturing NiTi alloy and its various production routes from conventional to rapid prototyping, porous NiTi, effect of additives on properties of the alloy and its challenges.

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.

Magnesium alloys are the potential candidate for metallic implants due to their excellent mechanical characteristics, biodegradable nature, and properties similar to human bone. However, a high degradation rate is primary obstacle in implementing these alloys as biodegradable orthopedic implants. Powder-mixed electric discharge machining (PMEDM) is an emerging method of surface modification of metallic alloys that can be implemented to improve the corrosion resistance of Mg alloys. Therefore, PMEDM using zirconium (Zr) and manganese (Mn) powder particles has been proposed to modify the surface characteristics of Mg-4Zn alloy. In the present work, Zr and Mn powders have been used in varying concentrations during PMEDM of Mg-4Zn alloy. Experiments were conducted as per mixed design L18 orthogonal array (OA). Taguchi and Grey Relational Analysis (GRA) have been used to optimize the process parameters. Analysis of response characteristics, namely material removal rate (MRR), surface roughness (SR), and thickness of the alloyed layer (TAL), has been carried out at different values of input variables (like powder additives (Pa), powder concentration (Cp), peak current (Ip), pulse on time (Ton) and duty cycle (DC)). The corrosion analysis was carried out by immersing the specimen (machined at an optimized setting) in simulated body fluid (SBF). It is observed from the analysis that Cp, Ip, and Ton play a pivotal role in evaluating response characteristics. The favorable setting suggested by the gray approach is Pa: Zr; Cp: 2 g/l; Ip: 4A; Ton: 50 μs; DC: 80%, while responses at this setting are confirmed by confirmation experiments with MRR: 32.14 mm3/min; SR: 5.578 μm and TAL: 8.28 μm. The immersion test signifies that the corrosion rate (CR) of PMEDMed sample (3.20 mm/year) is 40.74% lesser than the corrosion rate of polished sample (5.40 mm/year). Zr powder shows better performance in terms of higher MRR, lower SR and higher TAL as compared to Mn powder during the PMEDM process. The corroded surface of polished sample exhibited larger size micro pits and cracks than the machined sample, which concluded that surface modification of MZ-4Zn alloy via PMEDM is a powerful tool to enhance its corrosion resistance.

Electric discharge drill machine (EDDM) is a spark erosion process to produce micro-holes in conductive materials. This process is widely used in aerospace, medical, dental and automobile industries. As for the performance evaluation of the electric discharge drilling machine, it is very necessary to study the process parameters of machine tool. In this research paper, a brass rod 2 mm diameter was selected as a tool electrode. The experiments generate output responses such as tool wear rate (TWR). The best parameters such as pulse on-time, pulse off-time and water pressure were studied for best machining characteristics. This investigation presents the use of Taguchi approach for better TWR in drilling of Al-7075. A plan of experiments, based on L27 Taguchi design method, was selected for drilling of material. Analysis of variance (ANOVA) shows the percentage contribution of the control factor in the machining of Al-7075 in EDDM. The optimal combination levels and the significant drilling parameters on TWR were obtained. The optimization results showed that the combination of maximum pulse on-time and minimum pulse off-time gives maximum MRR.

Present work deals with the parametric study of dry sliding wear behaviour of TiB2-reinforced aluminium matrix composites (AMCs). Aluminium 6082-T6 alloy specimens reinforced with 0, 3, 6, 9 and 12 wt% of TiB2 particles were fabricated by the in situ reaction of K2TiF6 and KBF4 in heated liquid aluminium. Experiments were conducted to study the wear behaviour of AA6082–T6/TiB2 composites using pin-on-disc apparatus at room temperature. Weight percentage of reinforcement, sliding speed, load and sliding distance were the process parameters studied in the present investigation, with five different levels of each parameter. The parametric optimization was done employing response surface methodology. The results confirmed that an increase in the amount of reinforcement and sliding speed decreased the wear loss, and an increase in load and sliding distance increased the wear in TiB2-reinforced AMCs. However, the relative significance of these parameters on the sliding wear resistance of the AMCs was very much different. Analysis of variance showed that the sliding distance was the most dominating factor with 65.28% to influence the wear loss in the fabricated composites; it was preceded by the sliding speed with 14.78%, load (9.39%) and reinforcement percentage (3.86%), respectively. The present model was validated by conducting confirmation tests. Thus in this work an accurate wear model has been developed, and it can be used as a predictive tool for wear applications.

Ride comfort is the major concern to the roadway vehicle passengers, travelling in as it affects their health and efficiency to work. In the present study, a 9 DoF model of a three-wheel vehicle is developed with Lagrangian approach to investigate its ride behavior when subjected to random surface irregularities. The irregularities of the track are measured with a three-wheeled setup equipped with profilometer known as opto-coupler. The present model is validated in two ways, first by comparing the vertical-lateral PSD acceleration received from simulation and actual testing and second by comparing vertical seat to head transmissibility obtained from analysis (VSTH) with past reported studies. A 7 DoF bio-dynamic model of the seated human subject is formulated and integrated with the vehicle model, ride comfort of the vehicle and human body segments are assessed based on ISO specifications. Passenger Ride Comfort is optimized through non-linear optimization using Random Search Technique. The modified values of vehicle suspension parameters are presented to obtain optimum passenger comfort based on ISO-2631-1 criteria.

Purpose The purpose of this paper is to investigate the optimized setting of wire-cut electrical discharge machining (WEDM) parameters at which material removal rate (MRR) and mean roughness depth (Rz) set a compromise. The problem in the processing of Ti-6Al-4V by conventional processes is a high strength, high hardness, high tool wear. Due to which WEDM is adopted to machine Ti-6Al-4V biomedical alloy. Ti-6Al-4V alloy has a number of applications in the engineering and medical industries due to its high strength biocompatibility. Design/methodology/approach The effect of control factors (i.e. pulse on-time: Pon; pulse off-time: Poff; servo voltage: SV) on the MRR and Rz is investigated in the present research. The planning of experiments is done using a Taguchi-based L9 orthogonal array. The percentage influence of each factor on responses is also evaluated. The multi-objective optimization is done using the grey approach initially. After that, the results were also calculated using harmony search (HS). Therefore, a hybrid approach of grey and HS is used to find the optimized values of MRR and Rz. Findings The maximum value of grade calculated by grey-HS is 0.7879, while in the case of the experimental run the maximum value of grey grade is 0.7239. The optimized setting after improvisation at this grade value is Pon: 130 µ s; Poff: 45 µ s and SV: 70 V for MRR and Rz collectively. The validation of the suggested setting is completed by experimentation. The values of MRR and Rz are coming out to be 6.4 mm 3 /min and 13.84 µ m, which represents improvised results after the implementation of the HS algorithm. Originality/value The integration of the grey approach with the HS principle in the manufacturing domain is yet to be explored. Therefore, in the present research hybrid approach of grey-HS is implemented in the manufacturing domain having applications in medical industries.

Electric discharge drilling (EDD) is a variant of spark erosion machining and is successfully used for the drilling of quality microholes. In present research, an attempt was made to drill microholes on Al/SiC composite. The drilling on aluminum composite was made at different machining indicators to analyze its effect on drilling rate (DR), electrode wear ratio (EWR), hole overcut (HO) and circularity (C). The input parameters selected in this work are pulse on-time (Ton), peak current (Ip) and pulse off-time (Toff). The experiments were planned as per Taguchi's L9 orthogonal array (OA). It was found that with the increase in Ton value, HO and EWR increases. However, larger values of Ip and Toff decreases the HO and EWR. Due to the combination of different quality characteristics Grey theory along with desirability has been implemented for collective response of output parameters. The optimized setting for multiple performance characteristics is Ton: 40; Ip: 3; Toff: 50. An improvement of 0.0199 is observed in grade value during optimization as compared to the maximum calculated grade value. After the implementation of proposed optimization technique, an improvement of 42.88% in DR, a reduction of 33.59% in EWR, a reduction of 4.54% in HO and 0.68% in C is observed.

India is vast country with an approximate population of around 138 crores as of 2020 according to United Nations data. The increase in population leads to the high demand of petroleum oils and gases which results in the increase in the price as well. The combustion of fossil fuels produces harmful emissions, which are also responsible for secondary pollutants such as smog, acid rain, and other harmful air pollutants. To overcome these situations, there is need of alternative and clean fuel. Among the available alternatives, biodiesel derived from non-edible plants have been considered a better option than petroleum diesel. Government of India has proposed to use 5% biodiesel produced from waste cooking oils and non-edible oils such as jatropha, karanja by 2030. This study presents the current scenario of jatropha as a feedstock for biodiesel production and how the flexibility in the growth of jatropha makes it suitable for India. With the development done so far by many investigators to establish jatropha biodiesel as potential substitute of diesel has also been covered in this article.

Machining of difficult-to-machine materials has always been a prime area of investigation for researchers. With regard to that tool wear and surface roughness are some of the most important machinability indicators to evaluate the performance of machining processes. This paper reports a part of investigation conducted on dry turning of SS 304 using uncoated and multilayer coated carbide tools. In this work, the influence of machining parameters on tool wear and surface roughness is studied. The mechanisms of both crater wear and flank wear have been analyzed through scanned electron microscopy and energy dispersive spectroscopy. Moreover, surface roughness (mean roughness depth) profiles have been investigated. Carbide tools coated with TiAlN/TiN alternate layers outperformed uncoated tools with a significant reduction in tool flank wear and mean roughness depth (Rz). The percentage reductions in tool flank wear and Rz were investigated at different levels of input machining parameters. On average approximately 25% reduction in tool wear and 15% reduction in Rz was observed using coated tool than uncoated tool. Furthermore, the tool life has been improved by approximately 200% after using coated tools. Comparatively less irregular surface while machining with coated tools has been found than uncoated tools. The research is also complemented with a short chip morphology study. The present work recommends the use of multilayer TiAlN/TiN coating on carbide tools for machining of SS 304 under dry conditions.

In this research work the dry sliding wear behavior of a hybrid aluminum metal matrix composite is evaluated. Al 6061 is used as a matrix material while Si3N4 and nanographite powder (3–15 wt%) are used as reinforcements. These two reinforcements (50 wt% of each) were blended in a high-energy ball mill for homogeneous mixing to derive the sound aluminum matrix composite (AMC). The hybrid composite is made by the stir casting route and its wear rate was investigated against an EN32 steel disc surface, using a pin-on-disc tribometer. Integrated response surface methodology (RSM) and genetic algorithm (GA) are used to optimize the pin-on-disc process parameters. Analysis of variance (ANOVA) shows that sliding distance plays a major role on the dry sliding wear rate followed by load, sliding speed and reinforcements. Two-factor interactions and quadratic terms have also significant contributions. GA suggested a minimum wear rate value of 0.827 mg at optimized setting. Microstructural analysis by scanning electron microscopy (SEM) reveals that very fine grooves are obtained at optimized settings while at other settings severe ploughing is observed. Transition of wear mechanism takes place with the increase of speed (i.e., temperature between the two rubbing surfaces) from abrasive to adhesive.

Titanium alloys are widely used in various applications including biomedicine, aerospace, marine, energy, and chemical industries because of their superior characteristics such as high hot strength and hardness, low density, and superior fracture toughness and corrosion resistance. However, there are different challenges when machining titanium alloys because of the high heat generated during cutting processes which adversely affects the product quality and process performance in general. Thus, optimization of the machining conditions while machining such alloys is necessary. In this work, an experimental investigation into the influence of different cutting parameters (i.e., depth of cut, cutting length, feed rate, and cutting speed) on surface roughness (Rz), flank wear (VB), power consumption as well as the material removal rate (MRR) during high-speed turning of Ti-6Al-4V alloy is presented and discussed. In addition, a backpropagation neural network (BPNN) along with the technique for order of preference by similarity to ideal solution (TOPSIS)-fuzzy integrated approach was employed to model and optimize the overall cutting performance. It should be stated that the predicted values for all machining outputs demonstrated excellent agreement with the experimental values at the selected optimal solution. In addition, the selected optimal solution did not provide the best performance for each measured output, but it achieved a balance among all studied responses.

In the present research, a bio-composite material was initially designed and developed as per the requirement of prosthesis implants. Hydroxyapatite (HA) is considered as one of mostly used biomaterial due their unique characteristics of similarity in the composition of human bone and its bioactivity. Ti–6Al–4V is one of the foremost used materials in bio-implants due to their strength, wear resistance, corrosion resistance and bio-compatibility. The addition of HA in Ti alloy substantially improves its bioactivity and biocompatibility. However, at the same time, the wear rate of bio-composite increases. In the present work, Ti–6Al–4V/hydroxyapatite composite was developed by powder metallurgy method. To evaluate the real-time tribological characterization, the biocomposite was processed against the Al2O3 counter-surface in the presence of phosphate buffered saline (PBS) as a lubricant. In terms of characterization, the pin-on-disk tribometer was used for the evaluation of wear rate and friction coefficients in the range of 5 N–30 N of load. Scanning electron microscopy (SEM) micrographs revealed that plastic deformation and the abrasion are the main mechanisms of biocomposite/Al2O3 system. The pull-out material from the biocomposite plays a negative role on the friction coefficient and wear rate.

Formulation of a rail vehicle model using Lagrange’s method requires the system’s kinetic energy, potential energy, spring potential energy, Rayleigh’s dissipation energy and generalized forces to be determined. This article presents a detailed analysis of generalized forces developed at wheel–rail contact point for 27 degrees of freedom–coupled vertical–lateral model of a rail vehicle formulated using Lagrange’s method and subjected to random track irregularities. The vertical–lateral ride comfort of the vehicle and the ride index of the vehicle are evaluated based on ISO 2631-1 comfort specifications and stability is determined using eigenvalue analysis. The parameters that constitute the generalized forces and critically influence ride and stability have been identified and their influences on the same have been analysed in this work.

Graphene exhibits excellent distinct characteristics due to their lightweight and honeycomb structure. Due to these unique properties, graphene attracted number of researchers from diversified fields. Its applications are found in opto-electronics, electronics and biomedical sectors. These nanomaterials show some toxicity effects for biomedical applications, which are explained by the researchers working in this field in a limited manner. Due to which the toxic effect of these materials is still not well explained. Therefore, it became essential to analyze the characteristics of graphene and its potential application. The main aim of this review is to compile all the information (up-to-date) on its characteristics and applications, like energy, electronics, sensors and filed emission. Some challenges are discussed in conclusion section to provide the direction to the researchers for future research.

The development in technology developed new materials such as composites. These composites can be developed by different techniques. But the processing of these composites exhibits many challenges due to hard reinforcements. The recent work used the stir casting technique to develop the Al/SiC composite. After that, the machinability of the developed composite was checked with the electric discharge drilling. The microholes of diameter 1.5 mm were made on the developed composite. The experiments were designed using Response Surface Methodology based Box-Behnken design. According to the available drilling parameters (discharge current, pulse on-time, and pulse off-time) and their level, for each experiment overall, fifteen experiments were performed, and the tool wear rate (TWR) and material removal rate (MRR) were evaluated. After that, empirical models were developed for MRR and TWR, which were further solved by the Multi-objective Grasshopper Optimization Algorithm (MOGOA). It was observed that the predicted solutions suggested by MOGOA produce excellent results reproducibility. A small amount of burr formation was observed at the optimized setting. Energy dispersive spectroscopy (EDS) has been performed to determine the elements in the drilled composite.

In the present research, AISI P20 mold steel was processed using the milling process. The machining parameters considered in the present work were speed, depth of cut (DoC), and feed (F). The experiments were designed according to an L27 orthogonal array; therefore, a total of 27 experiments were conducted with different settings of machining parameters. The response parameters investigated in the present work were material removal rate (MRR), surface roughness (Ra, Rt, and Rz), power consumption (PC), and temperature (Temp). The machine learning (ML) approach was implemented for the prediction of response parameters, and the corresponding error percentage was investigated between experimental values and predicted values (using the ML approach). The technique for order of preference by similarity to ideal solution (TOPSIS) approach was used to normalize all response parameters and convert them into a single performance index (Pi). An analysis of variance (ANOVA) was conducted using the design of experiments, and the optimized setting of machining parameters was investigated. The optimized settings suggested by the integrated ML–TOPSIS approach were as follows: speed, 150 m/min; DoC, 1 mm; F, 0.06 mm/tooth. The confirmation results using these parameters suggested a close agreement and confirmed the suitability of the proposed approach in the parametric evaluation of a milling machine while processing P20 mold steel. It was found that the maximum percentage error between the predicted and experimental values using the proposed approach was 3.43%.

Wire electric discharge machine (WEDM) is a spark erosion machining process to cut very hard conductive material with the help of a wire electrode. High strength low alloy steel (HSLA) is a hard alloy with high hardness and wear resisting property. The purpose of this study is to investigate the effect of parameters on kerf width for WEDM using HSLA as workpiece. HSLA is used in cars, trucks, cranes, bridges, roller coasters and other structures that are designed to handle large amounts of stress. It is revealed that kerf width decreases with increase in pulse on time, pulse off time, spark gap voltage and peak current. Kerf width increases with increase in wire tension. In order to evaluate the effect of selected process parameters, the response surface methodology (RSM) is used to formulate a mathematical model which correlates the independent process parameters with the desired kerf width. The central composite rotatable design has been used to conduct the experiments. The analysis of results indicates that the spark gap voltage, pulse on time, peak current and pulse off time have a significant effect on kerf width.

Friction stir welding is a solid state welding in which two metal parts are joined without melting with the help of frictional heat generated between the work material and non-consumable tool. Because of the poor microstructure, cracks, porosity and residual stresses in fusion welding of aircraft aluminium alloys, friction stir welding is highly attractive for joints in aircraft structures. In the present work, using Taguchi’s design of experiment method, combined effect of process parameters namely tool rotation speed, welding speed (or traverse speed of tool), tool pin profile and tool shoulder diameter have been investigated for the ultimate tensile strength and percentage elongation of friction stir welded joints of AA6082 alloy. Two similar sets of experiments were performed to prepare the friction stir welded joints; first samples of AA 6082-T6 (solution heat treated and artificially aged) were friction stir welded and second cryogenic treated AA6082 alloy were friction stir welded . A comparison in the optimal conditions of two sets of experiments has also been presented. In tempered aluminium alloy, three process parameters namely tool rotation, weld speed and tool shoulder diameter are significantly affecting ultimate tensile strength, while all four parameters are significant for percentage elongation. The influence of cryogenic treatment has also been noticed on two response characteristics. An integrated approach of Taguchi method, grey relational analysis and entropy measurement method have been utilized to obtain an optimal single setting of process parameters for two response characteristics. For the friction stir welded joint of AA6082-T6 (without cryogenic treatment), a single optimal setting of process parameters was obtained corresponding to tool rotation: 1200 r/min, weld speed: 35 mm/min, tool pin profile, threaded cylindrical and tool shoulder diameter: 16 mm. Similarly, the single optimal setting for cryogenic treated aluminium alloy (AA6082) was obtained corresponding to tool rotation: 1200 r/.min, weld speed: 35 mm/min, tool pin profile, cylindrical and tool shoulder diameter: 14 mm.

This work is focused on the influence of different friction stir welding (FSW) parameters on AA6082 T-6 and AA5083-O alloys welding quality, by using Taguchi, Grey Relational and Weight Method.Four welding parameters were investigated, namely tool rotation speed (TRS), welding speed (WS), tool pin profile (TPP) and shoulder diameter (SD).The optimized setting of these input parameters was investigated so that weld parts quality could be optimized.Analysis of variance (ANOVA) was used to investigate the effects of these welding process parameters on response variables, viz.elongation (EL) and ultimate tensile strength (UTS).Single response optimization was carried using Taguchi Technique while grey relational analysis (GRA) was used for simultaneous optimization of two responses.Once the optimal settings of control factors were identified, confirmation experiments were performed for the validation of results.In the multi-response optimization, TRS was found to have the maximum effect (57.9%), followed by WS, SD and TPP.Weight method was applied for providing the priority to the response (i.e.EL and UTS).The response with higher priority presented a weight equal to 0.7, while the lower priority given corresponds to a weight of 0.3.

In cases where the natural frequencies of vibrations of a vehicle system are closed to the excitation frequencies from the road surface, dynamic vibration absorber provides the vibration isolation by shifting the resonant frequencies of the system. In the present work, the performance of a dynamic vibration absorber is evaluated with two degrees of freedom quarter car model of a road vehicle system when excited with deterministic inputs. The transmissibility of vibrations from the track to the sprung mass, the transfer function of sprung mass acceleration, the transfer function of suspension deflection and the transfer function of tire deflection is determined.

Aluminum-based hybrid composites are the lightweight materials used for many industrial applications. These applications include brake parts, automotive engine, high speed rotating shafts, high speed machinery and robots. The machining of aluminum was normally done by conventional machining processes. However, after the addition of ceramic particles, it became difficult to process the hybrid composite by conventional processes. Thus, non-conventional machining processes are used for the machining of aluminum-based hybrid composite. In the present work, the aluminum-based hybrid composite was developed using stir casting method, where Al6063 was used as matrix material and SiC along with Ti were used as reinforcement material. After the development of hybrid composite, the material is processed on wire electric discharge machining (WEDM). The varying control factors while machining was pulse on-time (Ton), pulse off-time (Toff), servo voltage (SV) and wire feed (WF). However, the response variable to measure the machining characteristics were cutting speed (CS) and kerf width (KW). The experiments were planned according to Response Surface Methodology (RSM) based Box Behnken Design (BBD). The response variables were converted into optimality function using Additive Ratio Assessment (ARAS) and then the developed empirical model was solved by Teaching Learning Based Optimization (TLBO). The optimized setting suggested by hybrid approach is Ton: 128 μs; Toff: 48 μs; SV: 48 V; WF: 7 m/min. After the optimization an improvement of 12% in optimality function, 18.24% in CS and 17.11% in KW was observed as compared to the best experimental run. The morphological investigation shows that at the optimized setting the presence of micro-cracks, sub-surface, globules and recast layer reduced significantly.

This paper presents the surface modification of WC-Co alloy with the use of aluminum and silicon powder in wire electric discharge machining (WEDM) process. A separate attachment with the stirrer is used to mix the metal powder in the dielectric, which is further supplied by a pump at the workplace continuously. The effects of different process parameters like peak current, pulse on-time, pulse off-time and servo-voltage are investigated on the material transfer, crack formation and white-layer formation with the help of Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) analysis. It was observed that silicon powder enhances the surface quality (4 µm white layer) compared with aluminum (6 µm white layer) powder. The white-layer thickness without the use of metal powder was around 14 µm. The cracks density after the addition powders reduces significantly.

Nowadays, titanium alloys are achieving a significant interest in the field of aerospace, biomedical, automobile industries especially due to their extremely high strength to weight ratio, corrosive resistance, and ability to withstand higher temperatures. However, titanium alloys are well known for their higher chemical reactive and low thermal conductive nature which, in turn, makes it more difficult to machine especially at high cutting speeds. Hence, optimization of high-speed machining responses of Ti-6Al-4V has been investigated in the present study using a hybrid approach of multi-objective optimization based on ratio analysis (MOORA) integrated with regression and particle swarm approach (PSO). This optimization approach is employed to offer a balance between achieving better surface quality with maintaining an acceptable material removal rate level. The position of global best suggested by the hybrid optimization approach was: Cutting speed 194 m/min, depth of cut of 0.1 mm, feed rate of 0.15 mm/rev, and cutting length of 120 mm. It should be stated that this solution strikes a balance between achieving lower surface roughness in terms of Ra and Rq, with reaching the highest possible material removal rate. Finally, an investigation of the tool wear mechanisms for three studied cases (i.e., surface roughness based, productivity-based, optimized case) is presented to discuss the effectiveness of each scenario from the tool wear perspective.

AA6082 matrix hybrid composites reinforced with different weight percentages (wt. %) of (SiC + Gr) ceramic particulates by conventional stir casting process is manufactured. The weight percentage of ceramic powder is varied from 4 wt. % to 12 wt. % in a stage of 4 wt. %. The microstructures, physical properties such as density and porosity, as well as mechanical properties like hardness and tensile strength of the fabricated hybrid composites, are analysed. The optical micrographs reveal the uniform distribution of (SiC + Gr) ceramic particulates in the aluminium matrix. Density and porosity of hybrid composite increases from 2.69 to 2.75 g/cm3 and 0.37% to 1.23% with increase in weight percentage of (SiC + Gr) ceramic particulates in the aluminium matrix from 0 wt. % to 12 wt. % respectively. Both the hardness and ultimate tensile strength have enhanced from 52 to 84 VHN and 163 to 189 MPa, respectively, with a reduction in percentage elongation from 8.6 to 5.2 with rise in weight percentage of (SiC + Gr) ceramic particulates in the aluminium matrix from 0 wt. % to 12 wt. %, respectively.

The modelling and simulation of a passenger rail vehicle locomotive for its crashworthiness are carried out in this paper. It is carried out as an application of combined FEM and MBS analysis using MADYMO. In some parts, the locomotive is modelled as super elements, principal parts are modelled as finite elements and joints are taken as flexible elements considering all external forces along with boundary conditions. The crashworthiness has been determined by striking the locomotive on to a fixed barrier. The simulation results of MFBD model at 25 kmph is benchmarked to the EN 15227 for validation of this technique. Once the model is validated, it is used for the locomotive crash analysis of crashworthiness behaviour at a different impact speed of 100 kmph, 160 kmph, and 225 kmph. Local buckling is observed at multiple points that restrict locomotive continuous damage characteristics. The results predict an increase in the speed of impact, more plastic deformation for the locomotive frontal part. The peak deformation is nearly 8.23 m observed at 224 kmph velocity.

Railway wheel axle experiences the problem of hunting above a critical velocity, which is a kind of self-excited oscillation. This paper investigates the linear and non-linear stability analysis of wheel axle constrained within a fixed bogie frame. From the linear analysis the critical velocity of the system with the existing parameters is found to be 268 km/hr. The influence of different parameters on stability of the system is further investigated in present study. Nonlinear analysis provides additional information compared with linear systems. Nonlinear analysis provides several stable solutions with a single set of parameters and each stable solution is function of the initial conditions. Using domains for initial conditions i.e. domains for attraction, chances for existence for stable solutions is determined. Present nonlinear analysis indicates that for vehicle velocity range from the critical velocity 366 km/hr to 392 km/hr, two stable solutions coexist i.e. the trivial solution with limit cycle solution and for the range of velocities beyond 392 km/hr one stable solution exist.

Surface properties play a significant role in the biocompatibility and biodegradation of Mg-alloy implants which primarily depends on the manufacturing route followed. In the present work, the milling process has been optimized on ZM21 Mg-alloy to obtain the trade-off between the material removal rate (MRR), surface roughness (SR), and degradation rate (DR). Milling parameters vary the amount of force and pressure developed between the tool and work interface, thus, affecting the MRR and SR. The weight loss of machined samples was measured after seven days of immersion in simulated body fluid (SBF) to calculate the DR. L16 orthogonal array was used to study the effect of milling parameters such as tool rotation speed (TRS), feed rate (FR), and depth of cut (DoC). The result showed that the variation in the values of milling parameters significantly influences the surface integrity of Mg-alloy, thus affecting the DR. Chip morphology and surface cracks with scanning electron microscopy (SEM) were evaluated to correlate the influence of milling parameters on the machining performance of ZM21 Mg-alloy. The machined surface of Mg-alloy must be of very low SR and cracks-free to avoid fast corrosion. Therefore, grey relational analysis (GRA) has been employed for multi-optimization to get the best trade-off for higher MRR and lower SR and DR. The optimized setting suggested by GRA for milling of ZM21 Mg alloy is TRS: 2700 rpm, FR: 25 mm/min, and DoC: 1.25 mm.

In view of rising fuel prices and increasing pollution, the aerospace sector has been encouraged to make more efficient and light vehicles. The use of light weight alloy components for making vehicles reduces fuel consumption and gives them primitive mileage. Aluminium Based Matrix Composites (AMCs) are widely used in the aerospace industry due to their tribological properties and remarkable mechanical properties. This review is an outline aluminium-based hybrid composite used in aerospace designs due to its Mechanical features. There is a need to further increase the Mechanical properties of aluminium alloy to provide more strength in airspace. The literature has declared the strength of the composites must be forced to be more rigid to make them more primitive. In addition, the hybrid composite developed by mixing soft components with hard components, which increases the wear resistance and reduces the brittleness. The present review shows that AMCs have great potential to serve as an alternative to high-strength, light-weight monolithic aluminium alloys with good wear resistance.

Recommender systems are becoming an integral part of routine life, as they are extensively used in daily decision-making processes such as online shopping for products or services, job references, matchmaking for marriage purposes, and many others. However, these recommender systems are lacking in producing quality recommendations owing to sparsity issues. Keeping this in mind, the present study introduces a hybrid recommendation model for recommending music artists to users which is hierarchical Bayesian in nature, known as Relational Collaborative Topic Regression with Social Matrix Factorization (RCTR-SMF). This model makes use of a lot of auxiliary domain knowledge and provides seamless integration of Social Matrix Factorization and Link Probability Functions into Collaborative Topic Regression-based recommender systems to attain better prediction accuracy. Here, the main emphasis is on examining the effectiveness of unified information related to social networking and an item-relational network structure in addition to item content and user-item interactions to make predictions for user ratings. RCTR-SMF addresses the sparsity problem by utilizing additional domain knowledge, and it can address the cold-start problem in the case that there is hardly any rating information available. Furthermore, this article exhibits the proposed model performance on a large real-world social media dataset. The proposed model provides a recall of 57% and demonstrates its superiority over other state-of-the-art recommendation algorithms.

Abstract Nickel-based superalloys have numerous applications in automobile, aerospace, turbine blades, nuclear, oil refinery etc, due to their excellent properties like strength, wear resistance, corrosion resistance and higher creep strength. Because of these properties, modern manufacturing industries need help with the machining of nickel-based superalloys, i.e. hard-to-machine materials. In the present research, Ni-based X-750 alloy is machined with turning operation by a conventional lathe machine using a TiAlN PVD coated tungsten carbide tool at different rotational speed (TRS), depth of cut (DoC) and feed (F) values as input parameters whereas material removal rate (MRR) and tool wear (TW) are the responses of the study. The design of experiments (DoE) is prepared by response surface methodology-based Box-Behnken Design. Analysis of variance (ANOVA) was applied to investigate the percentage contribution of each machining parameter on responses. Non-dominated Sorting Genetic Algorithm-II (NSGA-II) simultaneously optimizes the developed empirical models of MRR and TW. The predicted solutions suggested by NSGA-II are the best solution, and confirmation experiments are conducted on randomly selected parametric settings from these solutions. The optimized set presented by NSGA-II is TRS: 900RPM; DoC: 0.06 mm; F: 0.1 mm rev −1 , and the maximum relative error in the case of MRR and TW is in the permissible limit. Scanning electron microscopy (SEM) and Energy dispersive spectroscopy (EDS) are used to investigate the morphology of tool insert before and after machining at optimized value TRS: 900 RPM; DoC: 0.1 mm; F: 0.06 mm rev −1 , and it shows the wear marks on the tool, and the Energy dispersive spectroscopy confirms the presence of coating and WC. SEM is used to investigate the morphology of chips formed at different optimized parametric settings.

The increasing population and the industrial revolution are the prime reasons for the accelerated consumption of fossil fuels. In addition, the combustion of fossil fuels is a major contributor to carbon dioxide emission (a greenhouse gas), which is one of the reasons for global warming. In view of the search for alternatives to fossil fuels, biofuels have become attractive candidate due to their vital advantages over fossil fuels and the availability of a variety of feedstocks for biofuel production. Biofuels can be produced from municipal trash, forest, agricultural, or fishery waste, as well as by-products and wastes from the food, beverage, and agro-industries. The objective of this article is to examine the vital benefits and limitations of biofuels, their production technologies, as well as the obstacles and constraints that must be overcome before they can be effectively commercialized to meet global energy needs. The impacts of adding nanoparticles on engine behavior are also discussed in this article.

Wire electric discharge machine (WEDM) is a thermo-electric spark erosion machining process to cut very hard conductive material with the help of a wire electrode. Cryogenic treated high carbon high chromium tool steel (D-2 tool steel) is used for the current investigation. Cryogenic treatment is a surface process in which the material is placed in nitrogen environment (below -190 C) to remove stress and enhance wear resistance. The purpose of this study is to investigate the effect of parameters on surface roughness for WEDM. D-2 tool steel is used in die and punch industries, where wear takes place due to frequent operation of die-punch. To increase the wear resistance the cryogenic treated work-piece is used for the research. The Mathematical modelling of the process is carried with the help of Response surface methodology (RSM). The central composite rotatable design (CCRD) has been used to planning the experiments. The input process parameters are pulse on time, pulse off time, servo voltage and peak current. Out of which Pulse on-time has maximum effect on surface roughness as compared to other process parameters. Genetic algorithm is used to predict the best individual parameters along with the predicted fitness values.

In the present research, Ti-6Al-4V alloy was processed on wire-cut electrical discharge machine (WEDM) and the machining responses were analysed. The effect of machining variables was investigated on cutting speed (CS) and surface roughness (SR). Taguchi technique-based L9 orthogonal array was considered for the planning of experiments. Grey relational theory is used for multi-characteristics optimisation. During the research, it was observed that the best optimal setting for the process parameters is A1 B2 C2. At the suggested optimal setting, the predicted value of CS was 0.2044 mm/min and SR was 2.162 μm. These values are predicted at 95% confidence level. Scanning electron microscopy (SEM) investigates the surface morphology after the WEDM process. The surface integrity reveals the white-layer, sub-surface cracks and micro-cracks on the machined surface. The crack intensity increases with the increase of discharge energy.

In the current scenario of medical research, NiTi based smart alloys gaining importance due to the pioneer quality of biocompatibility, wear and corrosion resistance. In the present research, copper particles were blended with the nickel and titanium powder for 8 hours in high energy ball mill for uniform mixing. Specimens were fabricated using powder metallurgy at different compaction pressures. During the sintering process, the binder gets evaporated which makes it porous and suitable for biomedical implants. The testing was carried out to improve the corrosion and wear resistance of NiTi alloy under load-bearing biomedical applications. The addition of copper increases the wear and corrosion resistance of NiTi alloy. The experiments were conducted on pin-on-disk tribometer in the presence of simulated body fluid (SBF) at the temperature of 37 ± 1 °C. The test conditions were maintained according to the simulated hip joint. It was observed that the wear resistance of NiTi alloy increases slightly with the addition of copper particles up to certain percentage. The behaviour of the material changes after copper addition in the presence of SBF. Furthermore, the copper particles were blended with other particles to investigate the consequences on the tribological and corrosion characteristics of the developed materials. The corrosion rate increases when the copper contents were more than 5% due to decrease in the Ecorrosion (−0.19), but after increase the copper content from 5% an increase in Ecorrosion (−0.17) was observed. The copper content should be less than 5% to avoid pitting in the material; otherwise, it decreases the anti-pitting ability of NiTi alloy. The size of wear debris also decreases with the addition of copper up to 5%. After that, an increase in the size of wear debris was observed which makes it unsuitable for biomedical implants.

Good software quality is a consequence of good design. Model refactoring counteracts erosion of the software design at an early stage in the software development project complying with the model-driven engineering paradigm. Traditional model refactoring approaches work at the surface level by using threshold values of model metrics as indicators of suboptimal design and carry out localized corrections. Through this paper, it is proposed that identifying design flaws at a higher level of granularity will save from the vicious cycle of small refactoring operations and their cascaded side-effects. The notion of functional decomposition, as an anomalous design tendency and a dominant cause of design, smells in object-oriented software, is introduced. It is suggested that refactoring operations targeted at signs of functional decomposition instead of atomic smells achieve substantial improvement in design within a concise quality assurance procedure. The idea is realized using a deep neural network that learns to recognize the presence of functional decomposition in UML models of object-oriented software. The presented approach uses data science methods to gain insight into multidimensional software design features and uses the experience gained to generalize subtle relationships among architectural components.

This chapter is deliberated on the fundamental understandings of effects of cooling and lubrication techniques on the tool–work interfaces in machining. Considering the widespread application of coolants, that work as lubricants too, the advanced application methodologies (i.e., minimum quantity lubrication, atomization-based cooling, high-pressure cooling, cryogenic cooling, compressed air cooling, solid lubrication, and nanofluids) have been presented in detail. Parameters of interest for such technologies are noted with state-of-the-art scientific advancement in the application areas of turning, milling, drilling, and grinding. Key performance indicators such as cutting temperature, surface quality tool wear, chip morphology, cutting force, energy, and frictional behavior are covered.

In the present work, an attempt has been made to study the influence of process parameters of the wire electric discharge machining (WEDM) process on the machining characteristics. The commercially pure titanium is machined by WEDM using brass wire as an electrode. The input parameters in this work were pulse on-time (Aon), pulse off-time (Aoff), servo voltage (SV) and wire tension (WT). On the other hand, dimensional accuracy (DA), average surface roughness (Ra) and maximum surface roughness (Rz) were chosen as the response parameters. The empirical relations developed for response characteristics were solved collectively using Evaluation Based on Distance from Average Solution (EDAS) and Particle Swarm Optimization (PSO). The optimized setting for minimizing the surface irregularities while machining titanium alloy on WEDM is predicted as Aon: 8 μs; Aoff: 13 μs; SV: 45 V; and WT: 8 N. Moreover, the predicted solution at the optimized parametric settings came out as DA: 95%; Ra: 3.163 μm; Rz: 22.99 μm; WL: 0.0182 g; and DR: 0.1277 mm. The validation experiments at the optimized setting showed the close agreement between predicted and experimental values. The morphological study by scanning electron microscopy (SEM) at the optimized setting revealed a significant reduction in surface defects such as micro cracks, micro cavities, globules and sub-surfaces, etc. In a nutshell, the study justified the effectiveness of EDAS-PSO in efficiently predicting the results for machining of pure titanium (Grade 2) using the WEDM process.

The present research deals with the investigation of morphological characteristics after mechanical alloying of Ni–50 at. %Ti in a high-energy planetary ball mill at various milling times (i.e., 4, 8, 30, 40, 50, and 60 h). Crystallite size was observed to be decreased with the increase of milling time, entire titanium fused in the nickel trellis, and results of intermetallic NiTi. The shape of particle also changed from lamella to globular. Steatite-ceramic and hardened balls were separately used for the ball milling. The observations of morphologies revealed that steatite balls are more durable and wear resistant as compared to steel ball. This research shows that ball milling with steatite-ceramic balls is a cost-effective, high purity, and productive step toward the formation of NiTi intermetallic compound with homogeneous composition and desired particle size.

Purpose Electric discharge drilling (EDD) is used to drill quality microholes on any conductive materials. EDD process parameters play a crucial role in the drilling. Depending upon the material characteristics, the cost of drilling also changes. Therefore, a suitable method is required to control the process parameters and drill quality microholes. Design/methodology/approach The input process parameters in the present work are peak current (Ip), pulse on-time (Ton) and pulse off-time (Toff). The trials were intended in accordance to central composite face-centered design of response surface methodology (RSM). The output responses, namely drilling rate (DR) and electrode wear ratio (EWR), were converted into a single response, that is, grade using Grey relational analysis (GRA). The grade value is further modeled by regression analysis. The empirical model was figured out using teaching–learning-based optimization (TLBO). The RSM-Grey-TLBO-based multicriteria decision-making (MCDM) is used to investigate the optimized process parameter setting. Findings The RSM-Grey-TLBO-based MCDM approach suggests that the optimized setting for DR and EWR is Ip: 3A; Ton: 40 µs; Toff: 42 µs. The percentage errors for the predicted and experimental results are 8.1 and 7.5% in DR and EWR, respectively. Originality/value The parametric optimization of EDD using RSM-Grey-TLBO-based MCDM approach while machining commercially pure titanium is still underway. Thus, this MCDM approach will give a path to the researchers working in this direction.

Conventional mechanical machining of composite is a challenging task, and thus, electric discharge machining (EDM) was used for the processing of the developed material. The processing of developed composite using different electrodes on EDM generates different surface characteristics. In the current work, the effect of tool material on the surface characteristics, along with other input parameters, is investigated as per the experimental design. The experimental design followed is an RSM-based Box–Behnken design, and the input parameters in the current research are tool material, current, voltage, pulse-off time, and pulse-on time. Three levels of each parameter are selected, and 46 experiments are conducted. The surface roughness (Ra) is investigated for each experimental setting. The machine learning approach is used for the prediction of surface integrity by different techniques, namely Xgboost, random forest, and decision tree. Out of all the techniques, the Xgboost technique shows maximum accuracy as compared to other techniques. The analysis of variance of the predicted solutions is investigated. The empirical model is developed using RSM and is further solved with the help of a teaching learning-based algorithm (TLBO). The SR value predicted after RSM and integrated approach of RSM-ML-TLBO are 2.51 and 2.47 µm corresponding to Ton: 45 µs; Toff: 73 µs; SV:8V; I: 10A; tool: brass and Ton: 47 µs; Toff: 76 µs; SV:8V; I: 10A; tool: brass, respectively. The surface integrity at the optimized setting reveals the presence of microcracks, globules, deposited lumps, and sub-surface formation due to different amounts of discharge energy.

Abstract Magnesium alloy of grade AZ91D is utilized for a variety of applications in aircraft design and frames, as well as vehicle engine radiators, bumpers, and suspension components to reduce the weight of automobiles. This research compared the mechanical, corrosion, wear, and erosion resistance of pure Mg to that of AZ91 alloy. The corrosion media was NaCl, NaOH, and MgSO4, and the weight loss method was utilised to evaluate corrosion. The pin-on-disc configuration was utilized to assess the dry sliding wear mechanism of the Pure Mg and AZ91D alloy. Pure monolithic Mg and AZ91D magnesium alloy have a low resistance to wear as a result of an increase in contact temperature brought about by a shift of operational conditions. Erosive wear is caused when solid particles in a liquid or air jet strike a surface. Significantly influencing the erosive wear are particle velocity, impact angle, and erodent particle size. In this work, the erosive wear of AZ91D was studied using an Air jet erosion tester. SiO 2 was used as the eroding material, and the flow rate of the eroding material and air was 5 gm min −1 . The erosive factor experiments are designed using Taguchi orthogonal array (L 16 ). The erosive factor response is erosion rate and primarily regulated by three factors as angle (30°, 45°, 60°, and 90°), time (5 and 10 min) and, contact pressure (1 and 2 bar). The results of the experiments showed that the rate of wear increased with increasing pressure, and that the angle of impact of the jet at 60° caused the most wear of any of the tested angles. Analysis of variance (ANOVA) shows that time is the most important factor in determining erosive rate for AZ91D. SEM is used to investigate the structure and morphology of worn-out materials, and its findings are then confirmed.

Abstract In this work, AA5082 alloy is used as base alloy to fabricate aluminum composites using fine reinforced particles of boron carbide (B 4 C). The conventional method of stir casting is employed for the production of composites. The particles are used with varying weight % of 5, 10, 15 and 20 for the composite fabrication. The microstructures of the composites are examined using the Scanning Electron Microscopy and x-ray Diffraction patterns. The hardness of the composites is tested and found to increase from 73 HV in base alloy to 93 HV in the AA5082 composite having B 4 C proportion of 15%. However, a slight decrease in hardness is also observed at higher wt% of B4C which could be due to agglomeration of particles. Evaluation of yield strength showed an escalation in the strong point with the addition of reinforced particles under the effect of orowan strengthening mechanism. Wear analysis conducted on Tribometer indicates that the escalation of load and sliding distance is proportional to the loss of material in composites whereas, wear declined with the rise of sliding speed. The micrograph examination of the wear tracks reveals the material removal mechanism from the composite as abrasive in nature. Pitting at certain places is also observed.

This study explores the use of hemp, pineapple, and palm in green composites that are ecological substitutes for synthetic fibers in ballistics and architecture. Multi-criteria decision-making (MCDM) methodologies are taken into consideration to select the optimal choice for the configuration or constituent under deliberation. Integrated MCDM approaches like the Attribute Hierarchy Model (AHM) and TOPSIS are used to rank developed composites. Thermogravimetric analysis (TGA) revealed the thermal stability of palm, pineapple, and hemp fibers, with steadiness temperatures of 276°C, 241°C, and 166°C, respectively. The investigation spans various fiber contents, evaluating thermal, mechanical, and water absorption properties. Hybrid epoxy composites with pineapple and palm fibers exhibit exceptional performance, showcasing heightened tensile strength, yield strength, and hardness. In contrast, the hybrid composite with hemp and pineapple had better water absorption (18%) and specific heat capacity (5.6%) compared to the pineapple-only composite. An in-depth AHM-TOPSIS unveiled that the hybrid epoxy composites (FC7; 0.8524) with palm, hemp, and pineapple exhibit the highest quality, and composite incorporating pineapple fiber (FC2; 0.1393) ranks lowest. Scanning electron microscopy (SEM) scrutinizes fiber morphology and interfacial boundaries in composite subjected to stress rupture.

In the footwear manufacturing system, the upper parts of the shoe and bottom parts of the shoes are attached with the help of adhesive or stitched with the help of thread. In the earlier time shoes were made from bark, twine and other natural man made materials. 5000 year ago leather has come as natural material to produce the footwear. Which is comes in the form of leather hide. Handmade shoes are very unique to wear because they conform to the anatomy of the foot. Firstly, we take the structure line of man's foot to measure the foot structure, according to which we make the shoe last, while the customer chooses the size, material and design of the shoe. After the measurement process shoe were made by hand. The manual operations for the upper parts led to a large variability in processing times, resulting in higher work-in-process inventory. Nowadays the efficient mechanized system is available, which is more powerful to produce the goods at given time period, the efficiently of the equipment and machinery is very high. In the mechanized cement lasting process the upper part of the shoes stuck with the outsole with the help of adhesive by machinery, in which construction the different types of shoe making machineries are involved. The purpose of this paper is to review the areas where the current footwear manufacturing system can significantly affect the way of footwear sector is practiced, and also we will discuss the implementation.

Nowadays, the COVID-19 pandemic spreads all over the world. Every community is helping in the pandemic situation. All communities, like material scientists, medical practitioners, engineers, and healthcare professionals, are collaborating with each other to fight against the pandemic situation. Therefore, manufacturing engineers also play a role in COVID-19. There are a number of medical devices or protection equipment that can be developed by additive manufacturing (AM) to fulfill the shortage of supply. In the present research, an attempt has been made to review the different medical components developed by AM processes. The government’s regulations for different components (development and testing) are also discussed. The challenges associated with the products developed by AM processes are explained. The safety of the developed products is the prime responsibility of manufacturing engineers. This will definitely give the engineers direction to fight against the pandemic situation.

Three-wheeled vehicles may be a better choice as compared with four-wheeler cars provided they are properly designed to improve the rollover stabilities and ride comfort. The design modifications need improvement in geometry and suspension. This article presents the dynamic behavior of three-wheeled vehicle equipped with an inerter-based dynamic absorber and compares the same with the conventional suspension system. The performance parameters analyzed are vertical-lateral acceleration, front & rear suspension deflection, and front & rear dynamic tyre loads. The analytical rigid body model is formulated by assigning 9 degrees of freedom to the system for the evaluation of performance parameters to compare the inerter-based absorber suspension with the conventional passive suspension system.

The usage of additive manufacturing (AM) as a production technology for end-use products has increased due to advancements in the field. It permits the production of more complex parts with least waste material at a relatively low cost. Recent advancement in the domain is additive manufacturing of fibre reinforced polymer (FRP) materials having high strength to weight ratio. However, the mechanical properties of additively manufactured components depend upon the process parameters. This paper presents the correlation study of Fused Deposition Modelling (FDM) process parameters with mechanical properties of additively manufactured Nylon-Carbon fibre composite material. Infill density, layer thickness and infill orientation were the process parameters considered based on their influence on the strength of the component. Tensile strength, compressive strength and impact strength were considered as the response parameters. Tensile specimens were fabricated as per ASTM D638- Type I standard, while compressive and impact test specimen were fabricated as per ASTM D695 and ASTM D256 standards respectively. A fractional factorial Taguchi orthogonal array- L9 (3 parameters, 3 levels) was developed, and the influence of the process parameters was evaluated using Taguchi analysis. Based on the parametric study, the result showed that the infill density prominently influenced the strength of the component. Inverse proportionality was observed between the layer thickness and tensile & compressive strength, whereas impact strength exhibited direct proportionality with the layer thickness. Furthermore, tensile and compressive strength increased when the infill orientation was aligned with the loading direction, while impact strength increased with cross-oriented infill.

The characterization and mechanical behavior study of Al-7075 Metal Matrix Composites (MMCs) are the main topics of this illustration. It offers a thorough grasp of the material's potential by concentrating on crucial elements such microstructure, processing methods, reinforcing qualities, fatigue, thermal behavior, and modeling. For improved mechanical qualities, the review underlines the significance of developing a balanced microstructure and solid interfaces between the reinforcement and the matrix. It is also critical to investigate how reward size and substance affect mechanical behavior. The investigation also emphasizes the need for efficient processing techniques and the possibility of cutting-edge computational modeling to forecast and optimize the performance of the material. This debate clarifies key elements necessary for moving Al-7075 MMCs toward a variety of applications.

Motion detection is one of the key techniques for automatic video analysis to extract crucial information from scenes in video surveillance systems. This paper presents a new algorithm for MOtion DEtection (MODE) which is independent of illumination variations, bootstrapping, dynamic variations and noise problems. MODE is pixel based non-parametric method which requires only one frame to construct the model. The foreground/background detection starts from second frame onwards. It employs new object tracking method which detects and remove ghost objects rapidly while preserving abandon objects from decomposing into background. The algorithm is tested on public available video datasets consisting of challenging scenarios by using only one set of parameters and proved to outperform other state-of-art motion detection techniques.

The sugar mill roller shaft is one of the critical parts of the sugar industry. It requires careful manufacturing and testing in order to meet the stringent specification when it is used for applications under continuous fatigue and wear environments. For heavy industry, the manufacturing of such heavy parts (>600 mm diameter) is a challenge, owing to ease of occurrence of surface/subsurface cracks and inclusions that lead to the rejection of the final product. Therefore, the identification and continuous reduction of defects are inevitable tasks. If the defect activity is controlled, this offers the possibility to extend the component (sugar mill roller) life cycle and resistance to failure. The current study aims to explore the benefits of using ultrasonic testing (UT) to avoid the rejection of the shaft in heavy industry. This study performed a rigorous evaluation of defects through destructive and nondestructive quality checks in order to detect the causes and effects of rejection. The results gathered in this study depict macro-surface cracks and sub-surface microcracks. The results also found alumina and oxide type non-metallic inclusions, which led to surface/subsurface cracks and ultimately the rejection of the mill roller shaft. A root cause analysis (RCA) approach highlighted the refractory lining, the hot-top of the furnace and the ladle as significant causes of inclusions. The low-quality flux and refractory lining material of the furnace and the hot-top, which were possible causes of rejection, were replaced by standard materials with better quality, applied by their standardized procedure, to prevent this problem in future production. The feedback statistics, evaluated over more than one year, indicated that the rejection rate was reduced for defective production by up to 7.6%.

This paper presents the mechanical and tribological characteristics of the NiTi shape memory alloy (SMA) fabricated by powder metallurgy. This material has prominent applications in micro-electromechanical systems, medical implants, actuator, space and aerospace industries, etc. In every field, wear characteristics plays a dominating role. In present work dry-abrasion wear behavior is determined for NiTi alloy by varying binder percentage. With increasing binder percentage from 2.5 to 15 %, density decreases from 6.5 to 5.3 g/cm3 while porosity increases from 19 % to 51 %. Increasing rotational speed and binder percentage at a constant load the wear rate increases in the NiTi alloy. Due to the presence of hard particles, NiTi exhibits a very small wear rate. The coefficient of friction is also computed for the alloys in present research work. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray diffraction were used for the investigation of surface morphology and phases in the NiTi alloy.

This work presents the Influence of T4 and T6 heat treatment on the wear behavior of coarse and fine WC reinforced LM28 cast Composites. Production of the composites was achieved by stir casting method in the presence of inert gas. Fine (0.1–20 µm) and coarse (60–80 µm) particulates of WC were used from 0 to 12 wt.% in a step of 3%. Composites were given T4 and T6 heat treatment in the conventional manner. For T4 heat treatment, composites were heat treated at 450 °C for 2–3 h followed by quenching in oil and then naturally aged for 6–40 days at normal room temperature whereas for T6 heat treatment, similar cycle was employed with the addition of artificial aging at 180–220 °C for 3–7 h followed by normal cooling. T6 heat treated composites showed optimum hardness in comparison to T4 heat treated and non-heat treated composites. Pin on disk tests revealed the optimal wear resistance and coefficient of friction in T6 heat treated composites at varying sliding distance and load. Scanning-electron microscopy examination showed that the surface damage under the influence of load and sliding distance was higher in T4 heat treated and non-heat treated composites as compared to T6 heat treated composites. Abrasive wear mechanism was observed in the initial phase of material removal but gradually as the sliding distance increases, the wear mechanism transformed into adhesive. T6 composites showed superior wear resistance and hardness and therefore can ideally be employed in applications where high resistance to wear is critical.

In the present work, analysis of intake swirl is carried out on a single cylinder, direct injection diesel engine to determine the effect of swirl ratio on engine performance. A two dimensional CAD model was built to predict the pressure, temperature and velocity variation of air entering the cylinder during the suction and compression strokes of a cycle and the swirl ratio was calculated. Later, a three-dimensional model of the cylinder and a valve was made to carry out simulations at different valve lifts to identify and obtain the optimized swirl. Here, the maximum swirl ratio was obtained at 1 mm of valve lift whereas minimum at 6 mm of valve lift. The simulated results are validated with experimental data and good agreement was found between them. In addition to this, guide vanes were introduced in the intake manifold increasing the overall swirl ratio and hence leading to better engine performance.

The present research work investigates and analyses the effect of compaction pressure, sintering temperature and time on mechanical characteristics, namely compressive strength and Young's modulus of Ni50−xTi50Cux (x = 0, 5 and 10) alloys fabricated using powder metallurgy technology. The effect of process parameters on mechanical characteristics was evaluated using the Taguchi method and analysis of variance. Using the Taguchi approach, optimised values of process parameters were found for higher compressive strength and lower Young's modulus in each set of Ni50Ti50, Ni45Ti50Cu5 and Ni40Ti50Cu10 alloys. With the addition of copper in NiTi alloy, a little improvement in mechanical characteristics was observed, but bioactivity was decreased at 10%of Cu. Therefore, above 5% of Cu in NiTi alloy was not proved successful for biomedical applications.

The present research work is focused on optimisation of WEDM process parameters for machining of Nimonic-90. It is a nickel-based alloy possessing creep resistance and high rupture strength at high temperature (up to 950°C). Genetic algorithm (GA) and response surface methodology (RSM) incorporated with each other to optimise the process parameters. Four input process parameters viz. discharge current (Ip), pulse-off time (Toff), pulse-on time (Ton), and servo voltage (SV) have been investigated and modelled for surface roughness (SR) utilising RSM. In present experimentation, quadratic model has been suggested for surface roughness. Pulse-on time is most significant effect on surface roughness as compared to other parameters. Finally, genetic algorithm, a popular evolutionary approach is used to optimise the process parameters. Using SEM micrographs and micro-hardness profile, effect of discharge energy on surface morphology has been examined.

A problem of reflection at a free surface of micropolar orthotropic piezothermoelastic medium is discussed in the present paper.It is found that there exist five type plane waves in micropolar orthotropic piezothermoelastic medium, namely quasi longitudinal displacement wave (quasi LD wave), quasi thermal wave (quasi T wave), quasi CD-I, quasi CD-II wave and electric potential wave (PE wave).The amplitude ratios corresponding to reflected waves are obtained numerically.The effect of angle of incidence and thermopiezoelectric interactions on the reflected waves are studied for a specific model.Some particular cases of interest are also discussed.

It has always been argued that the two practices (distribution + agile) are actually incompatible. Introduction of agile methodologies in distributed field raises new challenges for development infrastructures to support collaboration and knowledge sharing in software development. Agile in a distributed setting does not mean step–by–step implementation of a particular agile methodology. It means collaboration among distributed teams to collate processes that follow agile principles and put together a methodology that works for them. This paper finds out different parameters for applicability of agile in distributed environment. Consequent upon the extensive literature review, a set of 43 factors were finalised. Factor analysis is used to factorising the minimising factors. After analysing eight broad factors are identified. The empirical analysis validates some long–held beliefs, it also provides some surprises. The findings agree with many of the 12 principles of agile practices laid down in the agile manifesto. The other three auxiliary factors identified also support several manifesto practices. On the other hand, the study findings fail to support several common assumptions about agile success factors.

The application of NiTi shape memory alloys are growing day by day in biomedical industry. These materials present inherent problems when undergoing conventional machining processes during manufacture of bioimplants. Conventional machining processes require high consumption of energy and resources, and assistance of post processing operations to make high quality implants of shape memory alloys. Unlike conventional methods, nonconventional methods are capable to eliminate the need for post processing amongst other advantages and thus prove to be the most economic means of producing biomedical implants. Wire spark erosion machining (also known as Wire Electro Discharge machining i.e. Wire-EDM) is one such nonconventional machining process that has been explored for the machining of biomedical implants by Ni rich NiTi. The present study aims to analyze and optimize the machinability of Ni55.8Ti shape memory alloy during wire electric discharge machining for biomedical applications. The L16 Orthogonal array using Taguchi design of experiments has been employed for this experimental study. The variable input parameters are namely pulse on time, pulse off time, servo voltage and wire feed rate. Machining at optimum parameters produced good surface finish, high material removal rate and excellent surface integrity. In this paper, specifically, the effect of the aforementioned Wire-EDM parameters on cutting rate, process optimization for the highest cutting rate, and surface roughness obtained at optimum parameters are reported. The outcomes encourage exploring wire spark erosion machining of other shape memory alloys for different scientific and industrial applications.

Educational dataSharma, Neeraj miningJain, Vaibhav facilitates educational institutions to discover useful patterns and apply them to improve the overall quality of education. Analysing student feedback may help institutions to enhance student's learning capabilities in the classroom. We propose a student feedback analysis system that helps in identifying sentiments from student reviews, and it further helps in generating the summary of feedback. It is implemented using sentiment analysis and text summarization techniques. Based on our evaluation, the lexicon-based approach did better than traditional machine learning-based techniques. Finally, we were able to generate a precise summary of student feedback.

The present research work deals with the fabrication of porous NiTi and NiTiCu shape memory alloy (SMA) by powder metallurgy process. These SMAs have number of applications in medical and space industries. The transformation temperature of both SMAs is measured by differential scanning calorimetry (DSC). Corrosion behavior is measured by potentiodynamic polarization curve in the presence of artificial saliva (pH value 7.4). Result shows that transformation temperature decreases by 8 °C to 10 °C after copper addition. Also, the corrosion current density decreases for NiTiCu, which exhibit more corrosion resistant than equi-atomic NiTi alloy. The corrosion current density of NiTiCu is less than NiTi by a factor of 31.

The current objective is to develop hybrid green AMCs that not only possess strength but are also eco-friendly and cost-effective by utilising reinforcements that are readily available at negligible or minimal cost and can be extracted from waste material. Chicken eggshell (ES) is one such example of waste material because it is an industrial and aviculture byproduct whose disposal causes a severe environmental hazard. Chicken eggshell can be utilised in consumer goods to create new low-cost, low-density materials. With these factors in mind, the objective of this work is to fabricate AA2024/SiC/carbonized eggshell hybrid green MMCs by the stir casting method. In this study, hybrid reinforcement particles (SiC and carbonised eggshell) are allowed to uniformly mix in the AA2024 matrix by the stir casting technique. The composition of reinforcements in this study varies from 0 to 12 wt% of SiC and ES particles together in a step of 3 i.e., (0, 3, 6, 9, 12) as per earlier researchers. The term "green" is being added to signify waste reduction from the environment by employing ES as a waste reinforcement and to make our environment sustainable and eco-friendly.

AISI 1045 can be machined well in all machining operations, namely drilling, milling, turning, broaching and grinding. It has many applications, such as crankshafts, rollers, spindles, shafts, and gears. Wiper geometry has a great influence on cutting forces (Fr, Ff, Fc and R), temperature, material removal rate (MRR) and surface roughness (Ra). Wiper inserts are used to achieve good surface quality and avoid the need to buy a grinding machine. In this paper, an optimization-based investigation into previously reported results for Taguchi’s based L27 orthogonal array experimentations was conducted to further examine effect of the edge geometry on the turning performance of AISI 1045 steel in dry conditions. Three input parameters used in current research include the cutting speed (Vc), feed (f) and depth of cut (ap), while performance measures in this research were Ra, Fr, Ff, Fc, R, temperature (temp) and MRR. The Vise Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method was used to normalize and convert all the performance measures to a single response known as the VIKOR-based performance index (Vi). The machine learning (ML) approach was used for the prediction and optimization of the input variables. A correlation plot is developed between the input variable and Vi using the ML approach. The optimized setting suggested by Vi-ML is Vc: 160 m/min; ap: 1 mm and f: 0.135 mm/rev, and the corresponding value of Vi was 0.2883, while the predicted values of Ra, Fr, Ff, Fc, R, temp and MRR were 2.111 µm, 43.85 N, 159.33 N, 288.13 N, 332,16 N, 554.4 °C and 21,600 mm3/min, respectively.

The field of knowledge and experience management has witnessed rapid changes mainly as a result of the dramatic progress in the domain of information technology and partly because of the Internet revolution. Accumulation and sharing of experiences is facilitated with efficiency as internet-enabled technologies allow movement of information at unimaginable speed. It has also made the storage of experiences in varied forms like Experience Bases possible. Moreover, learning has accrued over time in the area of social and structural mechanisms, such as through mentoring and retreats that enable effective experience sharing. This in turn has enabled the development of KM/EM applications that best leverage these improved mechanisms by deploying sophisticated technologies. Therefore, it will not be an exaggeration to state that technology has provided a major impetus for enabling the implementation of KM/ EM processes in organizational settings. The present paper discusses the role and the relevance of latest technology in the field of knowledge and experience management and uncovers the state of technology-mediated KM/ EM in Indian IT sector through a survey.

The advent of Model Driven Engineering has promoted software quality assurance activities to a higher level of abstraction than code, i.e. architectural models. Early quality assessment facilitates better design, reduces maintenance costs, manages requirement volatility and leads to faster software development. Less than optimal design decisions made during development and subsequent evolution introduce smells in the software. Model Refactoring uncovers smells at architectural level and transforms graphical representations of software to enhance design without affecting its observable behaviour. Focusing on object-oriented software systems, this paper presents a catalogue of smells and refactoring operations for UML class diagrams. The paper concludes by highlighting challenges in model refactoring and the potential of learning-based approach in automating the process.

LASERLaser claddingCladding technology has a strong applicability in the surface coating sector, mainly in metallic surfaces, although, it has been arousing, more and more, the interest in the components repair and rapid prototypingRapid prototyping sector. The reason for its creation was to improve the quality of component surfaces, overcoming the already known disadvantages in traditional processes as TIG—Tungsten Inert Gas weldingWelding also known as GTAW—Gas Tungsten Arc Welding, plasma spray or HVOF—High Velocity Oxy Fuel, being these disadvantages the high dilution of the substrate material into the coating/cladding, the large increase of temperature imposed by the process resulting in distortions in the parts, the low precision in material deposition, porosities, micro-cracks, bond defects and problems in the adherence to the substrate. The application of LASER technology for material addition/deposition processes come, for example, to improve the precision of the material deposition, to reduce the dilution of the substrate and the temperature increase of the component to be coated and also, the utilization of a LASER beam, does not cause unfavourable alterations in the mechanical properties of the melt pool. LASER claddingCladding technology can be considered interdisciplinary, in so far as it includes various technological areas, namely the LASERLaser technology, drawing area and computer assisted production, the robotic and control area and also the area of powder metallurgy. The majority of the scientific publications about LASER cladded coatings refer mainly its use in materials from aerospace, medical and automotive industries. Therefore, this chapter will attempt to focus on the LASER CladdingCladding growing applications of this recent technology and advantages and limitations of this process. This chapter will begin with a historic description of the LASERLaser Cladding technology, followed by the principles of the process operation, the applicability of the process, the state of art of materials utilized in the Cladding process, and the advantages and limitations of the process. At the end of the chapter will be present the recent developments in LASER CladdingCladding process.

Tungsten Inert Gas welding is a fusion welding process having very wide industrial applicability. In the present study, an attempt has been made to optimize the input process variables (electrode diameter, shielding gas, gas flow rate, welding current, and groove angle) that affect the output responses, i.e., hardness and tensile strength at weld center of the weld metal SS202. The hardness is measured using Vicker hardness method; however, tensile strength is evaluated by performing tensile test on welded specimens. Taguchi based design of experiments was used for experimental planning, and the results were studied using analysis of variance. The results show that, for tensile strength of the welded specimens, welding current and electrode diameter are the two most significant factors with P values of 0.002 and 0.030 for mean analysis, whereas higher tensile strength was observed when the electrode diameter used was 1.5 mm, shielding gas used was helium, gas flow rate was 15 L/min, welding current was 240A, and a groove angle of 60o was used. Welding current was found to be the most significant factor with a P value of 0.009 leading to a change in hardness at weld region. The hardness at weld region tends to decrease significantly with the increase in welding current from 160-240A. The different shielding gases and groove angle do not show any significant effect on tensile strength and hardness at weld center. These response variables were evaluated at 95% confidence interval, and the confirmation test was performed on suggested optimal process variable. The obtained results were compared with estimated mean value, which were lying within ±5%.

Model refactoring enhances the platform-independent design models of software aiming at smoother impact of requirement changes, thereby improving the design quality and assisting in their evolution and maintenance. This study reports a systematic literature review of refactoring techniques particularly in the domain of models of object-oriented software systems. The study used the standard systematic literature review method based on a comprehensive set of 58 articles from a total of 1200 articles published in leading journals, premier conferences, workshops and books. The primary studies were thoroughly analyzed on various aspects of model refactoring process. Identification of methodologies and classification on the basis of model transformation systems, refactoring operations and their application, model behavior specification and preservation, model quality expression, model consistency management and automation of process is reported. This study shows that inadequate model-based approaches for behavior preservation, synchronized model enhancement and empirical evaluation of the proposed refactoring techniques are major obstacles in fully automated model refactoring process.

In the present work, Aluminium composites were fabricated through conventional stir casting process. The composites were fabricated at 800°C inside the electric furnace in the presence of inert gas. AA5083 and B4C particulates with varying weight % of 5, 10, 15 and 20 were used as the starting materials. The microstructure of the composites was examined using scanning electron microscopy (SEM). The physical and mechanical properties of the composites were investigated and the results show that the increase in B4C content in the aluminium matrix increases the tensile strength and hardness of the composites to a significant level. The decrease in density accompanied by increase in porosity was also observed with the increase in B4C.