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This research aims to use energy harvested from conductive materials to power microelectronic components. The proposed method involves using vibration-based energy harvesting to increase the natural vibration frequency, reduce the need for battery replacement, and minimise chemical waste. Piezoelectric transduction, known for its high-power density and ease of application, has garnered significant attention. Additionally, graphene, a non-piezoelectric material, exhibits good piezoelectric properties. The research explores a novel method of printing graphene material using 3D printing, specifically Direct Ink Writing (DIW) and fused deposition modelling (FDM). Both simulation and experimental techniques were used to analyse energy harvesting. The experimental technique involved using the cantilever beam-based vibration energy harvesting method. The results showed that the DIW-derived 3D-printed prototype achieved a peak power output of 12.2 µW, surpassing the 6.4 µW output of the FDM-derived 3D-printed prototype. Furthermore, the simulation using COMSOL Multiphysics yielded a harvested output of 0.69 µV. [ABSTRACT FROM AUTHOR]

This paper proposes a convolutional neural network (CNN) model of the signal distribution control algorithm (SDCA) to maximize the dynamic vehicular traffic signal flow for each junction phase. The aim of the proposed algorithm is to determine the reward value and new state. It deconstructs the routing components of the current multi-directional queuing system (MDQS) architecture to identify optimal policies for every traffic scenario. Initially, the state value is divided into a function value and a parameter value. Combining these two scenarios updates the resulting optimized state value. Ultimately, an analogous criterion is developed for the current dataset. Next, the error or loss value for the present scenario is computed. Furthermore, utilizing the Deep Q-learning methodology with a quad agent enhances previous study discoveries. The recommended method outperforms all other traditional approaches in effectively optimizing traffic signal timing. [ABSTRACT FROM AUTHOR]

This article details the existing wearable assistive devices that could mimic a human's active range of motion and aid individuals in recovering from stroke. The survey has identified several risk factors associated with musculoskeletal pain, including physical factors such as engaging in high-intensity exercises, experiencing trauma, aging, dizziness, accidents, and damage from the regular wear and tear of daily activities. These physical risk factors impact vital body parts such as the cervical spine, spinal cord, ankle, elbow, and others, leading to dysfunction, a decrease in the range of motion, and diminished coordination ability, and also influencing the ability to perform the activities of daily living (ADL), such as speaking, breathing and other neurological responses. An individual with these musculoskeletal disorders requires therapies to regain and restore the natural movement. These therapies require an experienced physician to treat the patient, which makes the process expensive and unreliable because the physician might not repeat the same procedure accurately due to fatigue. These reasons motivated researchers to develop and control robotics-based wearable assistive devices for various musculoskeletal disorders, with economical and accessible solutions to aid, mimic, and reinstate the natural active range of motion. Recently, advancements in wearable sensor technologies have been explored in healthcare by integrating machine-learning (ML) and artificial intelligence (AI) techniques to analyze the data and predict the required setting for the user. This review provides a comprehensive discussion on the importance of personalized wearable devices in pre- and post-clinical settings and aids in the recovery process. [ABSTRACT FROM AUTHOR]

The materials used in engineering have seen a significant transformation in the contemporary world. Numerous composites are employed to overcome these problems because conventional materials are unable to meet the needs of current applications. For quite some time, professional engineers and researchers have been captivated by the problem of choosing the best machining parameters for new composite materials. Wire electrical discharge machining is a popular unconventional machining process that is often used for making complex shapes. Numerous process parameters influence the WEDM process. Thus, to achieve affordable and high-quality machining, the right set of process parameters must be provided. Finding the wire cut EDM optimized settings for the fabricated LM5/ZrO2/Gr composite is the main aim of this research. The chosen input parameters are the wire feed, pulse on and pulse off times, the gap voltage, and the reinforcing percentage. In this study, LM5/ZrO2/Gr composites were made from stir casting with 6-weight percent ZrO2 as the reinforcement and varying graphite percentages of 2, 3, and 4 wt%. Then they were machined in WEDM using L27 OA to seek the best parameters for machining by adjusting the input parameters. The findings were analysed by means of grey relation analysis (GRA) to achieve the supreme material removal rate (MRR), lowest surface roughness (SR), and a smaller kerf width (Kw) simultaneously. GRA determines the impact of the machining variables on the standard characteristics and tests the impact of the machining parameters. Confirmation experiments were performed finally to acquire the best findings. The experimental findings and GRA show that the ideal process conditions for achieving the highest grey relational grade (GRG) are 6% ZrO2 with 2% graphite reinforcement, a wire feed of 6 m/min, a pulse off time (Toff) of 40 µs, a pulse on time (Ton) of 110 µs, and a gap voltage (GV) of 20 V. The gap voltage (22.87%) has the greatest impact on the GRG according to analysis of variance (ANOVA), subsequent to the interaction between the pulse on time and the gap voltage (16.73%), pulse on time (15.28%), and pulse off time (14.42%). The predicted value of the GRG is 0.679; however, the experimental GRG value is 0.672. The values are well-aligned between the expected and the experimental results. The error is only 3.29%, which is really little. Finally, mathematical models were created for each response. [ABSTRACT FROM AUTHOR]

Titanium–silicon oxynitride sulfite (TiSiNOS) is a coating material that is deposited on H13 tool steel using the scalable pulsed power plasma (S3P) technique, where the coating deposition is a hybrid process consisting of a mix of sputtering and arc evaporation. The maximum hardness and coating thickness measured on TiSINOS-coated H13 tool steel are 38 GPa and 3.1 µm, respectively. After implementing the L9 orthogonal array, nine samples were coated with TiSiNOS, which consists of the same properties. The nine coated and uncoated samples were tested separately based on the L9 pattern to achieve accurate results. The experimental results indicate that the wear loss can be reduced by minimizing the load at 25 N even if the temperature rises to 250 °C. SEM analysis reveals that the uncoated sample has higher wear loss when compared with the coated samples, and material pullout is visible from the uncoated sample. Based on these results, it can be concluded that TiSINOS coating in H13 tool steel helps in improving the tool life during the drilling process. Taguchi was used in this research to evaluate the wear behavior. The data observed from the experiment were analyzed using the Minitab tool. The most crucial factor is to determine the effects of process parameters. A higher temperature influenced the wear behavior of the tool. [ABSTRACT FROM AUTHOR]

This study was designed to examine the effects of a trimethylolpropane trioleate (TMPTO)-based lubricant on thrust force and torque under the high-speed drilling of Al-6061 as an effective environmentally friendly cutting fluid. The tribological performance of three lubricant blends was evaluated based on ASTM standards. TMPTO base oil, notably enhances load-carrying capacity under extreme pressure conditions, with a seizer load of 7848 N. The best-performing oil was further optimized using a Taguchi-based design experiment to investigate the effect of different additive concentrations on thrust force and torque under actual contact conditions. Experiments were conducted using three critical machining parameters: additive concentration, spindle speed, and feed rate. The results of the ANOVA analysis reveal that spindle speed contributes most substantially (62.99%) to torque, with feed rate (23.72%) and additive concentration (7.74%) also showing significant impacts. On the other hand, thrust force is primarily influenced by feed rate (73.52%), followed by spindle speed (16.82%), and additive concentration (6.28%). Furthermore, a machine learning model was developed to predict and compare a few significant aspects of high-speed drilling machinability, including thrust force and torque. Three different error metrics were utilized in order to assess the performance of the predicted values, namely the coefficient of determination (R2), mean absolute percentage error (MAPE) and mean square error (MSE), which are all based on the coefficient of determination. Compared to other models, decision tree produces more accurate prediction values for cutting forces. The present study provides a novel approach for evaluating the most promising biodegradable lube oils and predicting cutting forces by formulating a perfect blend. [ABSTRACT FROM AUTHOR]

Fiber-reinforced additive manufacturing components have been used in various industrial applications in recent years, including in the production of aerospace, automobile, and biomedical components. Compared to conventional methods, additive manufacturing (AM) methods can be used to obtainin lighter parts with superior mechanical properties with lower setup costs and the ability to design more complex parts. Additionally, the fabrication of onyx composites using the conventional method can result in delamination, which is a significant issue during composite machining. To address these shortcomings, the fabrication of onyx composites via additive manufacturing with the Mark forged 3D-composite printer was considered. Machinability tests were conducted using abrasive water jet machining (AWJM) with various drilling diameters, traverse speeds, and abrasive mass flow rates. These parameters were optimized using Taguchi analysis and then validated using the Genetic algorithm (GA) and the Moth Flame Optimization algorithm (MFO). The surface morphology (Dmax) and the roughness of the drilled holes were determined using a vision measuring machine with 2D software (MITUTOYO v5.0) and a contact-type surface roughness tester. Confirmation testing demonstrated that the predicted values werenearly identical to the experimental standards. During the drilling of an onyx polymer composite, regression models, genetic algorithms and the Moth-Flame Optimization algorithm were used to estimate the response surface of delamination damage and surface roughness. [ABSTRACT FROM AUTHOR]

Aluminum matrix composites (AMCs) are largely used in defense, maritime, and space applications for their excellent properties. LM5 is used where very high resistance to corrosion from seawater or marine atmospheres is required, for equipment used for the manufacture of foodstuffs, cooking utensils, and chemical plants. Zirconia is preferred over other reinforcements as it shows comparatively great refractory properties, high scratch resistance, and thermal shock resistance. Utilizing the stir casting technique, an attempt was made to produce AMCs of LM5 aluminum alloy strengthened with ZrO2. The weight percentage of ZrO2 was changed to 0%, 3%, 6%, and 9%. The specimens were prepared and tested as per ASTM standards to find the density, micro and macro hardness, impact, tensile, and compressive strength. The micrographs and SEM images confirm the uniform distribution of ZrO2 particles in the aluminum matrix. LM5/9%ZrO2 AMC has the highest density value of 2.83 g/cm3 and LM5/3%ZrO2 has the least porosity of 2.55%. LM5/9% ZrO2 has the highest hardness values of 78 VHN and 72 HRE. LM5/6% ZrO2 AMC has the highest tensile strength of 220 MPa, compressive strength of 296 MPa, and toughness of 12 J. LM5/6% ZrO2 AMCs may be used for many structural applications. [ABSTRACT FROM AUTHOR]

Heating of the electrode at the work–piece interface zone in spot welding, leading to degradation of the tip, becomes a significant concern in the high-volume production automotive industry. By recognizing the interrelationship between hardness, wear resistance, and thermal conductivity, the authors emphasize the importance of selecting electrode materials with suitable alloying elements desirable for achieving optimal performance in spot welding applications. This paper studies the wear behaviour of three types of spot-welding electrode materials under dry sliding contact conditions. A pin-on-disc tester was used to investigate Cu–Cd, Cu–Be and Cu–Cr–Zr alloys' wear behaviour under variable parametric load, temperature and time conditions. Taguchi L9 orthogonal array was used to investigate the significance of parameters and their effect on linear wear. The ranking of the parameters was performed using SN ratio analysis. The wear mechanism was also studied using SEM analysis. Abrasive wear was observed at lower loads, while adhesion, oxidation and plastic deformation were observed under high-load and -temperature conditions. This study suggests an alternative to the presently used electrolytic tough pitch (ETP) Cu electrode involving equally good wear-resistance material. However, a detailed investigation on the effect of plasma on the metallurgical characteristics of selected material is suggested. [ABSTRACT FROM AUTHOR]

Incremental sheet forming (ISF) is an emerging technology that has shown great potential in forming customized three-dimensional (3D) parts without the use of product-specific dies. The forming force is reduced in ISF due to the localized nature of deformation and successive forming. Forming force plays an important role in modeling the process accurately, so it needs to be evaluated accurately. Some attempts have been made earlier to calculate the forming force; however, they are mostly limited to empirical formulae for evaluating the average forming force and its different components. The current work presents a mathematical model for force prediction during ISF in a 3D polar coordinate system. The model can be used to predict forces for axis-symmetric cones of different wall angles and also for incremental hole flanging. Axial force component, resultant force in the r-θ plane, and total force have been calculated using the developed mathematical model appearing at different forming depths. The cone with the same geometrical parameters and experimental conditions was modeled and simulated on ABAQUS, and finally, experiments were carried out using a six-axis industrial robot. The mathematical model can be used to calculate forces for any wall angle, but for comparison purposes, a 45° wall angle cone has been used for analytical, numerical, and experimental validation. The total force calculated from the mathematical model had a very high level of accuracy with the force measured experimentally, and the maximum error was 4.25%. The result obtained from the FEA model also had a good level of accuracy for calculating total force, and the maximum error was 4.89%. [ABSTRACT FROM AUTHOR]

The hygroscopic properties of natural fibers tend to degrade the mechanical properties of composite materials. It is essential to investigate the influence of water absorption behavior on the mechanical properties of hybrid composite materials. In this study, hybrid laminate materials consisting of two different reinforcement materials, i.e., Kevlar fibers and jute fibers in the same layer, are considered. Hybrid laminates that have four different weaving patterns: plain weave, basket weave, twill weave, and the satin weave, are tested for their water absorption characteristics. The jute fiber is a naturally extracted fiber that is subjected to chemical treatment. A comparison of mechanical properties before and after treatment of the jute fibers is carried out. Mechanical properties such as tensile strength, compressive strength, flexural strength, impact strength, and hardness are tested. It is found that the mechanical properties improved after the treatment of the jute fibers. The twill weave pattern exhibited negligible defects compared to its counterparts. Chemical treatment of the jute fibers enabled less water being absorbed into the hybrid laminate materials. Mechanical properties improved after using chemically treated jute fibers as the reinforcement material in the hybrid laminate materials. It is concluded that the twill weave pattern and chemical treatment of the natural fibers improved the mechanical properties of the hybrid laminate materials. [ABSTRACT FROM AUTHOR]

Lightweight aluminum composite is a class of foam material that finds many applications. These properties make it suitable for many industries, such as the transportation, aerospace and sports industries. In the present work, closed-cell foams of an Al-Si12CuFe alloy and its composite are developed by a stir casting process. The optimization of the foaming temperature for the alloy and composite foams was conducted in terms of the ligament and node size of the alloy and also the volatility of the zircon with the melt, to provide strength to the cell walls. CaCO3 as a blowing agent was homogeneously distributed in the molten metal without adding any thickener to develop the metal foam. The decomposition rate of CaCO3 is temperature-dependent, which is attributed to the formation of gas bubbles in the molten alloy. Cell structure, such as cell size and cell wall thickness, is controlled by manufacturing process parameters, and both the physical and mechanical properties are dependent on the foam cell structure, with cell size being the major variable. The results show that the increase in cell wall thickness with higher temperature leads to a decrease in cell size. By adding the zircon to the melt, the cell size of the composite foam first increases, and then the thickening of the wall occurs as the temperature is increased. The uniform distribution of the blowing agent in molten metal helps in the formation of a uniform cell structure. In this work, a comparative structural study of alloy foam and composite foam is presented regarding cell size, cell shape and foam stability at different temperatures. [ABSTRACT FROM AUTHOR]

The design and development of a photovoltaic thermal (PVT) collector were developed in this study, and electrical and electrical thermal efficiency were assessed. To improve system performance, two types of coolants were employed, liquid and liquid-based MnO nanofluid. Flow rates ranging from 1 to 4 liters per minute (LPM) for the interval of 1.0 LPM were employed, together with a 0.1% concentration of manganese oxide (MnO) nanofluid. Various parametric investigations, including electrical power generation, glazing surface temperature, electrical efficiency, and electrical thermal efficiency, were carried out on testing days, which were clear and sunny. Outdoor studies for the aforementioned nanofluids and liquids were carried out at volume flow rates ranging from 1 to 4 LPM, which can be compared for reference to a freestanding PV system. The research of two efficiency levels, electrical and electrical thermal, revealed that MnO water nanofluid provides better photovoltaic energy conversion than water nanofluid and stand-alone PV systems. In this study, three different domains were examined: stand-alone PV, liquid-based PVT collector, and liquid-based MnO nanofluids. The stand-alone PV system achieved a lower performance, the liquid-based MnO performed better, and the liquid-based PVT achieved an intermediate level. [ABSTRACT FROM AUTHOR]

Incremental sheet forming (ISF) requires no or partial dies for sheet metal fabrication and is widely used for small batch production. In this process, necking is either suppressed or delayed due to the localized nature of tool–sheet contact; hence, more strains than conventional stamping and deep drawing are obtained. In the present study, two variations of ISF, namely cold ISF (CISF) and warm ISF (WISF), are compared. First, FEA modeling is carried out on ABAQUS to reach the forming forces involved in the process. It is found that WISF reduces the forming forces. The temperature for WISF is maintained at 180 °C. Following the simulation analysis, tests are carried out. The forming force in WISF is 55.77% less than that in CISF. The part fabricated by CISF is slightly more substantial than that by WISF; however, more forming depth can be achieved by WISF. There is a more uniform thickness distribution in the case of CISF than in WISF. However, the surface quality of the CISF product is inferior to that of WISF. It is observed that there is reduced forming force, increased formability, and better strain distribution in WISF compared to CISF. However, post-processing heat treatment and surface polishing of the formed parts is required to restore their mechanical properties. [ABSTRACT FROM AUTHOR]

Non-exhaust brake dust and pollution arising from metal, semi-metal, and ceramic brake pads have made recent research consider their replacement by potential natural fibers such as hemp, flax, sisal, etc. These natural fibers are lightweight, biodegradable, and cheap. This paper discusses the wear and friction analysis of hemp fiber reinforced polymer brake pad material. Three test specimens viz. HF4P20, HF5P20, and HF6P20 were prepared per ASTM G99 standards for the pin-on disc tribo-test. The test trials and validation were done using the Taguchi design of experiments and ANOVA. The optimum result showed a consistent coefficient of friction and lowered specific wear rate for HF6P20 brake pad material. Worn surface morphology was done using scanning electron microscopy. [ABSTRACT FROM AUTHOR]

The current scenario of society is to produce fuel from renewable energy resources. The purpose of this research work is to develop an integrated approach for glycerol valorization and biodiesel production. Employing a range of methodologies widely used in the industry, technical analysis and assessments of the process's applicability in real-world situations are also made. The integrated process plant is simulated using Aspen Plus®. Several different sensitivity analyses are carried out to describe the process that improves efficiency and are designed to maximize hydrogen recovery from the reforming section. The integrated process results are compared with several existing standalone biodiesel production processes. Additionally, the results are verified with the theoretical studies on glycerol valorization. The outcomes of the process plant simulation reveal coherent results with the current industrial standards for the two processes. The results show that the amount of glycerol produced (stream 7) is 60.72 kmol/h in mass flow rate, this translates to 7272.74 kg/h. The hydrogen produced is 488.76 kmol/h and, in mass flow rate, this translates to 985.3 kg/h. The total yield of hydrogen produced is around 13%. The biodiesel yield is at 92.5%. It shows a realistic recovery that would be attained if the process is implemented, contrary to theoretical studies. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) has started to unfold diverse fields of applications by providing unique solutions to manufacturing. Laser cladding is one of the prominent AM technologies that can be used to fulfill the needs of custom implants. In this study, the wear resistance of the laser cladded titanium alloy, Ti-17Nb-6Ta, has been evaluated under varied loads in Ringer's solution. Microstructural evaluation of the alloy was performed by SEM and EDX, followed by phase analysis through XRD. The wear testing and analysis have been carried out with a tribometer under varied loads of 10, 15, and 20 N while keeping other parameters constant. Abrasion was observed to be the predominant mechanism majorly responsible for the wearing of the alloy at the interface. The average wear rate and coefficient of friction values were 0.016 mm3/Nm and 0.22, respectively. The observed values indicated that the developed alloy exhibited excellent wear resistance, which is deemed an essential property for developing biomedical materials for human body implants such as artificial hip and knee joints. [ABSTRACT FROM AUTHOR]

Coronavirus (COVID-19) disease has not only become a pandemic but also an overwhelming strain on the healthcare industry. The conventional diagnostic methods include Antigen Rapid Kits and Reverse Transcription–Polymerase Chain Reaction (RT-PCR) tests. However, they entail several drawbacks such as low precision in diagnosis, increased time in obtaining test results, increased human–patient interaction, and high inaccuracy in the diagnosis of asymptomatic individuals, thus posing a significant challenge in today's medical practice in curbing an extremely infectious disease such as COVID-19. To overcome these shortcomings, a machine learning (ML) approach was proposed to aid clinicians in more accurate and precise infection diagnoses. A Convolutional Neural Network was built using a sample size of 1920 chest X-rays (CXR) of healthy individuals and COVID-19-infected patients. The developed CNN's performance was further cross-checked using the clinical results of the validation dataset comprising 300 CXRs. By converting the final output to binary, an intuitive classification of whether a specific CXR is of a healthy or a COVID-infected patient was accomplished. The statistical analysis of the CNN was: Accuracy: 95%; Precision: 96%; Specificity: 95%; Recall: 95%, and F1 score: 95%, thus, proving it to be a promising diagnostic tool in comparison to the other existing ML-based models. The datasets were obtained from Kaggle, GitHub, and European Institute for Biomedical Imaging Research repositories. The prospects of the proposed CNN lie in its flexibility to be altered and extrapolated in diagnosing other lung infections, such as pneumonia and bacterial infections, with relevant training algorithms and inputs. Additionally, the usage of other bio-imaging modalities as input datasets such as CT scans, Lung Ultrasounds and Heat Maps gives the CNN immense potential to assess for better insights on the severity of infection in both infected and asymptomatic patients as well as other related medical diagnoses. [ABSTRACT FROM AUTHOR]

To meet the global requirements of the industry, there is a need for innovative light weight, low cost, eco-friendly, high quality engineering materials with superior performance at a wide range of temperatures. Aluminum Matrix Composites (AMCs) are lightweight materials with isotropic properties, a suitable choice for modern industry. Low-cost aluminum alloys reinforced with minerals have found a special place in the automotive industry for the manufacture of automobile parts. Rutile particles improve the mechanical properties of the aluminum matrix, making it attractive for structural applications as well as providing greater wear resistance to the composite during sliding. In the present studies, a rutile mineral reinforced LM27 aluminum alloy composite was developed through a stir casting route with 6, 9 and 12 wt.% reinforcements. To study the effect of particle size on the mechanical and tribological properties of composite samples reinforced with fine-sized (50–75 μm) and coarse-sized (106–125 μm) rutile particles were prepared From the results of the experiment, it was found that the hardness, compressive strength and wear resistance increase with increasing rutile wt.% addition. The worn surface and re-groove of the new surface are restored during sliding with the help of oxide films. The analysis of the fractured surface clearly indicates with the help of energy dispersive X-ray spectroscopy (EDS) that with the increase in the volume fraction of the reinforced particles, the porosity increases, which could be the main reason for the compression failure of the composite material. [ABSTRACT FROM AUTHOR]

The present research investigates the wear properties of a continuous carbon fiber-reinforced additively manufactured polymer composite under dry sliding conditions. The effect of load and fiber orientation is examined on polymer composite specimens. The wear test of the additively manufactured polymer composite specimens is conducted on pin-on-disk test equipment. The result shows that the applied load and fiber orientation significantly affect the composite specimen's wear properties. The wear and coefficient of friction (COF) increase with load. The minimum effect on wear and COF is observed for 0° fiber orientation, and the maximum effect is observed for 90° fiber orientation. Finally, morphological analysis is conducted using an optical micrograph of the worn-out surfaces to understand the failure type for different fiber orientations. [ABSTRACT FROM AUTHOR]

This work addresses an evolutionary algorithmic approach to reduce the surplus pieces in selective assembly to increase success rates. A novel equal area amidst unequal bin numbers (EAUB) method is proposed for classifying the parts of the ball bearing assembly by considering the various tolerance ranges of parts. The L16 orthogonal array is used for identifying the effectiveness of the proposed EAUB method through varying the number of bins of the parts of an assembly. Because of qualities such as minimal setting parameters, ease of understanding and implementation, and rapid convergence, the moth–flame optimization (MFO) algorithm is put forward in this work for identifying the optimal combination of bins of the parts of an assembly toward maximizing the percentage of the success rate of making assemblies. Computational results showed a 5.78% improvement in the success rate through the proposed approach compared with the past literature. The usage of the MFO algorithm is justified by comparing the computational results with the harmony search algorithm. [ABSTRACT FROM AUTHOR]

Hybrid composites recently developed as highly effective, high-strength structural materials that are increasingly used. Aluminum matrix hybrid composites strengthened with ceramic particulates are commonly used in marine, aerospace, and defense applications because of their exceptional properties. Zirconia-reinforced composites are favored because these composites display high refractory properties, excellent abrasion resistance, and chemical resistance compared to composites of other reinforcements.For applications where lightweight and superior performance is paramount, such as parts for spacecraft, fighter aircraft, and racecars, graphite compositesare the material of choice. In this research work, an effort was made to combine the properties of zirconia and graphite by producing a unique metal matrix composite of LM5 aluminum alloy reinforced with 6% zirconium dioxide (zirconia), using the stir casting process by changing the percentage of the weight of graphite to 2%, 3%, and 4%. The test specimens were prepared and evaluated in compliance with ASTM standards to study micro- and macrohardness, and impact, tensile, and compressive strength. Microstructural studies of composites performed through optical microscopy and SEM expose the unvarying dispersal of particulates of ZrO2/graphite in the aluminum matrix. The hardness, impact, and compressive strength are enhanced due to the addition of reinforcement. [ABSTRACT FROM AUTHOR]

Nanoparticles dispersed in lubricants are being studied for their ability to reduce friction and wear. This paper examines SAE 5W-30 oil enhanced with dispersed graphene nanoplates for tribological and rheological properties. Graphene nanoplate (GNs) concentration effects on the rheological and tribological properties of 5W-30 base oil (0.03, 0.06, 0.09, 0.12, and 0.15 wt percent) were tested. Under various loads, a four-ball testing model was used to conduct a tribological analysis (200, 400, 600, and 800 N). Kinematic viscosity is calculated, and base oil and nanofluid-added 5W30 lubricant are compared for thermal conductivity and flashpoint. Wear scar and coefficient of friction improved by 15% and 33% with nano-additives. When related to the base oil, the flashpoint, thermal conductivity, kinematic viscosity, and pour point all increased, by 25.4%, 77.4%, 29.9%, and 35.4%, respectively. The addition of GNs improved the properties of 5W30 engine oil. [ABSTRACT FROM AUTHOR]

Titanium (Ti) and its alloys are predominant choices for use as biomaterials in human implants. Research has shown the adverse effects of using commercial Ti alloy Ti-6Al-4V in the human body, and this presents a need for viable alternatives. In this study, Ti alloy Ti-17Nb-6Ta was manufactured by laser cladding—a prominent additive manufacturing (AM) technology. Laser cladded specimens were evaluated for their in vitro and electrochemical behavior. A human osteosarcoma cell line (MG-63 cells) was used for in vitro investigations. Cell proliferation was good in the physiological medium, and cells were alive when in contact with the laser cladded alloy, even after two to three weeks, indicating good cell viability and compatibility with this alloy. Electrochemical characterization was carried out in Ringer's solution, and noticeably lower corrosion current density and corrosion rate values were observed. The lower amounts of these parameters indicated the passivation behavior due to multi-layer Ti, Nb, and Ta alloy oxide films. These oxide films also enhanced osseointegration. Thus, the Ti-17Nb-6Ta alloy can be an ideal biocompatible alternative to Ti-6Al-4V. [ABSTRACT FROM AUTHOR]

Exposure of the engine valve to high temperatures led to the degradation of the valve material due to microstructural instability and deteriorating mechanical properties. Performance enhancement and alteration in microstructures can be attained through the powder metallurgy route which is a viable method to produce near net shape components. In this current study, the development of austenitic stainless steel (21-4N) through the powder metallurgy route as an alternate material for engine valves was investigated. Mechanical alloying was carried out for the pre-alloyed mixtures and consolidated using vacuum hot pressing. Sintering parameters were fixed at 1200 °C, 50 MPa and at a vacuum level of 10-3 Torr. A scanning electron microscope was used to analyze the morphology of the milled powders. Densities for the hot pressed powders were compared with theoretical densities and found to be around 98–99%. Observations regarding grain size, the presence of austenitic grain, heterogeneous distribution of metal carbides and analysis of chemical composition along the metal matrix were determined using both optical and electron microscopes. X-ray diffraction was carried out for both the consolidated and powder samples. The hot pressed samples exhibited a hardness value of 410 ± 10 Hv. An isothermal compression test for the sintered samples was carried out at a temperature of 650 °C and strain rate of 0.001 s−1. It is showed that the compressive strength of 1380 MPa. An analysis between the room temperature yield strength obtained from hardness measurement and the strengthening mechanism based on the microstructure was conducted. Grain size, dislocation and solid solution are the major strengthening mechanisms which strengthen the material. Overall, the development of valve steel material through the powder metallurgy route exhibited improved metallurgical and mechanical properties in comparison to the corresponding cast product. [ABSTRACT FROM AUTHOR]

Electrochemical machining (ECM) is a preferred advanced machining process for machining Monel 400 alloys. During the machining, the toxic nickel hydroxides in the sludge are formed. Therefore, it becomes necessary to determine the optimum ECM process parameters that minimize the nickel presence (NP) emission in the sludge while maximizing the material removal rate (MRR). In this investigation, the predominant ECM process parameters, such as the applied voltage, flow rate, and electrolyte concentration, were controlled to study their effect on the performance measures (i.e., MRR and NP). A meta-heuristic algorithm, the grey wolf optimizer (GWO), was used for the multi-objective optimization of the process parameters for ECM, and its results were compared with the moth-flame optimization (MFO) and particle swarm optimization (PSO) algorithms. It was observed from the surface, main, and interaction plots of this experimentation that all the process variables influenced the objectives significantly. The TOPSIS algorithm was employed to convert multiple objectives into a single objective used in meta-heuristic algorithms. In the convergence plot for the MRR model, the PSO algorithm converged very quickly in 10 iterations, while GWO and MFO took 14 and 64 iterations, respectively. In the case of the NP model, the PSO tool took only 6 iterations to converge, whereas MFO and GWO took 48 and 88 iterations, respectively. However, both MFO and GWO obtained the same solutions of EC = 132.014 g/L, V = 2406 V, and FR = 2.8455 L/min with the best conflicting performances (i.e., MRR = 0.242 g/min and NP = 57.7202 PPM). Hence, it is confirmed that these metaheuristic algorithms of MFO and GWO are more suitable for finding the optimum process parameters for machining Monel 400 alloys with ECM. This work explores a greater scope for the ECM process with better machining performance. [ABSTRACT FROM AUTHOR]

In this research work, the machinability of turning Hastelloy X with a PVD Ti-Al-N coated insert tool in dry, wet, and cryogenic machining environments is investigated. The machinability indices namely cutting force (CF), surface roughness (SR), and cutting temperature (CT) are studied for the different set of input process parameters such as cutting speed, feed rate, and machining environment, through the experiments conducted as per L27 orthogonal array. Minitab 17 is used to create quadratic Multiple Linear Regression Models (MLRM) based on the association between turning parameters and machineability indices. The Moth-Flame Optimization (MFO) algorithm is proposed in this work to identify the optimal set of turning parameters through the MLRM models, in view of minimizing the machinability indices. Three case studies by considering individual machinability indices, a combination of dual indices, and a combination of all three indices, are performed. The suggested MFO algorithm's effectiveness is evaluated in comparison to the findings of Genetic, Grass-Hooper, Grey-Wolf, and Particle Swarm Optimization algorithms. From the results, it is identified that the MFO algorithm outperformed the others. In addition, a confirmation experiment is conducted to verify the results of the MFO algorithm's optimal combination of turning parameters. [ABSTRACT FROM AUTHOR]

The proposed work aims to acquire the maximum number of non-linear assemblies with closer assembly tolerance specifications by mating the different bins' components. Before that, the components are classified based on the range of tolerance values and grouped into different bins. Further, the manufacturing process of the components is selected from the given and known alternative processes. It is incredibly tedious to obtain the best combinations of bins and the best process together. Hence, a novel approach using the combination of the univariate search method and the harmony search algorithm is proposed in this work. Overrunning clutch assembly is taken as an example. The components of overrunning clutch assembly are manufactured with a wide tolerance value using the best process selected from the given alternatives by the univariate search method. Further, the manufactured components are grouped into three to nine bins. A combination of the best bins is obtained for the various assembly specifications by implementing the harmony search algorithm. The efficacy of the proposed method is demonstrated by showing 24.9% of cost-savings while making overrunning clutch assembly compared with the existing method. The efficacy of the proposed method is demonstrated by showing 24.9% of cost-savings while making overrunning clutch assembly compared with the existing method. The results show that the contribution of the proposed novel methodology is legitimate in solving selective assembly problems. [ABSTRACT FROM AUTHOR]

Tolerance cost and machining time play crucial roles while performing tolerance allocation in complex assemblies. The aim of the proposed work is to minimize the above-said manufacturing objectives for allocating optimum tolerance to the components of complex assemblies, by considering the proper process and machine selections from the given alternatives. A novel methodology that provides a two-step solution is developed for this work. First, a heuristic approach is applied to determine the best machine for each process, and then a combined whale optimization algorithm with a univariate search method is used to allocate optimum tolerances with the best process selection for each sub-stage/operation. The efficiency of the proposed novel methodology is validated by solving two typical tolerance allocation problems of complex assemblies: a wheel mounting assembly and a knuckle joint assembly. Compared with previous approaches, the proposed methodology showed a considerable reduction in tolerance cost and machining time in relatively less computation time. [ABSTRACT FROM AUTHOR]

Electric, hybrid, and fuel cell vehicles are the future of the automobile industry, and power source design is one of the most crucial steps in designing these vehicles. This paper aims to design and structurally simulate a custom accumulator—which powers an electric vehicle, for a lightweight, single-seater formula-style racecar. The work is dependent on the model-based design and CAD model approach. Mathematical modeling on SCILAB is used to model equations to get the characteristics of the accumulator, such as the energy, capacity, current, voltage, state of charge, and discharge rates. The output of this model gives the configuration of the battery pack as several cells in series and parallel to adequately power the tractive system. An accumulator container is designed to safeguard the cells from external impacts and vibrational loads, which otherwise can lead to safety hazards. Following this, the Finite Element Analysis (FEA) performed on the accumulator resulted in maximum peak deformation of 0.56 mm, ensuring the safety check against various external loads. Further, the finer stability of the battery pack was virtually validated after performing the vibrational analysis, resulting in a deformation of 3.5493 mm at a 1760.8 Hz frequency. [ABSTRACT FROM AUTHOR]

Non-exhaust brake dust and pollution arising from metal, semi-metal, and ceramic brake pads have made recent research consider their replacement by potential natural fibers such as hemp, flax, sisal, etc. These natural fibers are lightweight, biodegradable, and cheap. This paper discusses the wear and friction analysis of hemp fiber reinforced polymer brake pad material. Three test specimens viz. HF4P20, HF5P20, and HF6P20 were prepared per ASTM G99 standards for the pin-on disc tribo-test. The test trials and validation were done using the Taguchi design of experiments and ANOVA. The optimum result showed a consistent coefficient of friction and lowered specific wear rate for HF6P20 brake pad material. Worn surface morphology was done using scanning electron microscopy.