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Nowadays, there has been continuous development of metallic biomaterials to meet special needs in the manufacturing of biomedical implants, units and systems so as to function well in the required environment. Developed biomaterials which possess exceptional properties in terms of biocompatibility and biomechanical compatibility require precision processing and machining to obtain the desired dimensional tolerances. Electrical discharge machining (EDM) is the noncontact or nontraditional process of machining that suits the precision machining of biomaterials. In this work, an effort was made to optimize the EDM parameters during machining of titanium-based biomaterials Ti-6AL-4V, so that the multi-objective responses could be obtained. The response surface method was used in designing the experiment, while the grey relational method was used to analyze the effect of multiple objectives into a single unit. The electrical parameters that were considered in this study include peak current, gap voltage, pulse turn-on and duty cycle. These parameters were set within the acceptable limits of the equipment. Three responses were studied, which are tool wear rates (TWRs), material removal rate (MRR) and surface roughness (SR). Using the signal-to-noise ratio and ANOVA optimum tool/electrode wear rate (TWR) is obtained at [Formula: see text][Formula: see text]g/min with process parameters [Formula: see text] A, [Formula: see text][Formula: see text]V, [Formula: see text][Formula: see text][Formula: see text]s, [Formula: see text]%. Optimum values of material removal rate (MRR) are obtained as 0.01035[Formula: see text]g/min with process parameters [Formula: see text] A, [Formula: see text][Formula: see text]V, [Formula: see text][Formula: see text][Formula: see text]s, [Formula: see text]%. Optimum SR is observed as 2.258[Formula: see text][Formula: see text]m with EDM process parameters [Formula: see text] A, [Formula: see text][Formula: see text]V, [Formula: see text][Formula: see text][Formula: see text]s, [Formula: see text]%. Surface characteristics are verified with SEM micrographs. Whereas, grey relation analysis predicted the multi-objective optimum response characteristics. Based on the grey relation grade, experiment number 7 ([Formula: see text][Formula: see text]A, [Formula: see text][Formula: see text]V, [Formula: see text][Formula: see text][Formula: see text]s, [Formula: see text]%) secured the first rank among the experiments/trails.

The production of biodiesel as an alternative fuel and its use as a mixture and other additives are presented. In the present research work, additive blends with diesel biodiesel from algae oil are physically characterised and an analysis of pollutant emissions is carried out when used in an ignition engine by compression. The measurement of pollutant emissions is carried out through a combined emission analyzer adapted to a system of valves attached to the experimental facility. The properties of each mixture with the polluting emissions are compared with that of the reference diesel. It was found that each of the properties improves compared to that of diesel, reducing most emissions in the use of mixtures with biodiesel.

In FSW, tool pin profile has a significant contribution on mechanical and microstructural properties of metallic joints. In the present work, various pin profiles such as conical, pedal, cylindrical with thread, triangular, square and pentagonal pins are used to join the AA2024 plates. Mechanical and microstructural characterization is done for welded plates using different pin profile tools. The mechanical properties such as percentage elongation, ultimate tensile strength (UTS), microhardness and impact strength are significantly improved, when plates are joined using square pin profile. The obtained joint efficiency is 78% using square pin profile tool. The percentage elongation, UTS and impact energy of joint made by square pin tool are measured as 15%, 362 MPa and 5.7 Joule, respectively, which are higher than the values obtained using other pin profiles. EBSD analysis was performed to know the microstructural changes, which are a cause of mechanical properties alteration. Analysis reveals that stirred zone exhibits the recrystallized fine grains with equiaxed structure, which is a result of dynamic recrystallization and heating during plastic deformation of the zone. Large fraction of HAGB is also observed in stirred zone, which is a cause of improved mechanical properties of the joint.

The RFID-based vehicle collection program is intended to better handle toll operations through technology that aims to streamline the flow of vehicles. The purpose of this work is to plan, introduce and promote the automated operation of the car selection system (VTS). The Vehicle Toll Collection Device in this paper automatically detects vehicles and gathers machine-readable details on tolls for automobiles driving in the toll road. This knowledge is instigated by the modification and installation of at least one vehicle with a moving vehicle detection device. The computerized control device located along the toll line will transmit the registration signal as the car is reaching the registration point and will determine the toll to be debited and transfer the toll electronically to the account of the individual vehicle. This device helps a car to proceed beyond the scan point with no halting, thereby providing commuters with optimum comfort, speeding up traffic movement and reducing the need for human capital on highways

To increase the productivity and quality of the machined components, wire electro-discharge machine parameters such as cutting speed, kerf width, and surface roughness are often optimized. The Wire-electro discharge machining process generates a much higher temperature at the wire-work piece interface which can potentially change the metallurgical characteristics of the machined surface. This paper studies the changes in the tribology of surface and sub-surface of the workpiece due to the initial and optimized wire-electro discharge machine parametric setting using grey relational analysis while machining sub-cooled AISI P20 tool steel. It is concluded that the optimum parametric setting to obtain a better cutting speed, kerf width, and surface roughness using grey relational analysis, which improves the productivity and quality of the component, also produces a thicker recast layer. The wear test revealed that the surface machined with an optimized parametric setting gives higher wear resistance. Detailed scanning electron microscopy explains the characteristics of the recast layer and micro-hardness explains the surface hardenability of tool steel, which is a result of martensitic transformation through rapid cooling, formed heat affected zone, and increase in oxygen content on the surface. The wear test proved that the recast layer helps in improving the wear resistivity of tool steel. The methodology of the hardening of the surface and the sub-surface layer can strengthen the application of components.

In this paper we determine the natural frequency of highest speed milling spindle for length 335.4 mm and 16000 rpm speed based on modal analysis. This manuscript taking the high speed milling spindle of bar that is derived and presented by using finite element model in ANSYS software. This method takes into account bearing support contact interface that is recognized by spring damper element COMBIN 14 for giving cushioning effect to spindle. Furthermore, the modal analysis has completed by means of ANSYS commercial software. After that this result is compared with experimental result provided by FFT analyzer. The results show that the natural resonance region speed is far greater than the designed milling spindle.

Present study discusses the processing and experimental investigation of hybridized nano-composites. The epoxy polymer reinforced by Al2O3 Polymer nanocomposites hybridized by Al2O3 of rod and spherical shape were prepared by in-situ polymerization technique. Spherical particle of 20–50 nm diameter and rod particles having 15–30 nm diameter & 50 nm length were used as nanofiller. The weight percent of nanofiller of 0.5 wt%, 1 wt% & 1.5 wt% were used for reinforcement of epoxy matrix. The tensile strength, elastic modulus was observed at different wt % nanofilled epoxy resin and the results were compared with the performance of neat epoxy samples. The reinforcement of nanofillers significantly affects the tensile strength and moderately affects the elastic modulus of polymer resin. The results reported that the tensile strength was improved from 58.7 MPa to 64.1 MPa. The microstructure of fractures specimen were observed by scanning electron microscope (SEM) to verify the strengthening mechanism.

Electro spinning is a technique of producing nanofibers from polymer solution under the influence of electrostatic forces. In this work, we investigated the formation of nanofibers by electro spinning technique using synthetic biodegradable poly (e-caprolactone) (PCL) polymer sample. It provides a relatively inexpensive method of creating a variety of nanofibers. Nano to micro structure recyclable Poly (e-caprolcatone) materials were prepared by electro-spinning of solutions PCL in the range of 10–15 % (W/V) at constant voltage of 18Kv. Electrospun fabrics Hus obtained using chloroform as a solvent. The impacts of different parameters, including stream rate, and solution parameters, for example, focus and dissolvable were likewise inspected. While expanding arrangement focus, the morphology changed from beaded filaments to the uniform fibers. The compatibility of the PCL nanofibers with physiological fluids was assessed through standard assay procedures using simulated body fluids. The morphology of the fibers was investigated by scanning electron microscopy, nanofibers crystallinity and function groups were examined by X-ray diffraction analysis and Fourier transformer infrared spectroscopy. From this study, it could suggest that the formation of nanofibers were obtained in the range of 100 nm−350 nm thickness. The obtained result concluded that the PCL nanofibers could be suitable for tissue engineering applications.

Breast cancer is the most common cancer in women, and the breast mass recognition model can effectively assist doctors in clinical diagnosis. However, the scarcity of medical image samples makes the recognition model prone to overfitting. A breast mass recognition model integrated with deep pathological information mining is proposed: constructing a sample selection strategy, screening high-quality samples across different mammography image datasets, and dealing with the scarcity of medical image samples from the perspective of data enhancement; mining the pathology contained in limited labeled models from shallow to deep information; and dealing with the shortage of medical image samples from the perspective of feature optimization. The multiview effective region gene optimization (MvERGS) algorithm is designed to refine the original image features, improve the feature discriminate and compress the feature dimension, better match the number of samples, and perform discriminate correlation analysis (DCA) on the advanced new features; in-depth cross-modal correlation between heterogeneous elements, that is, the deep pathological information, can be mined to describe the breast mass lesion area accurately. Based on deep pathological information and traditional classifiers, an efficient breast mass recognition model is trained to complete the classification of mammography images. Experiments show that the key technical indicators of the recognition model, including accuracy and AUC, are better than the mainstream baselines, and the overfitting problem caused by the scarcity of samples is alleviated.

With the continuous development of social networks, Weibo has become an essential platform for people to share their opinions and feelings in daily life. Analysis of users’ emotional tendencies can be effectively applied to public opinion control, public opinion surveys, and product recommendations. However, the traditional deep learning algorithm often needs a large amount of data to be retained to obtain a better accuracy when faced with new work tasks. Given this situation, a multiclassification method of microblog negative sentiment based on MAML (model-agnostic metalearning) and BiLSTM (bidirectional extended short-term memory network) is proposed to represent the microblog text word vectorization and the combination of MAML and BiLSTM is constructed. The model of BiLSTM realizes the classification of negative emotions on Weibo and updates the parameters through machine gradient descent; the metalearner in MAML calculates the sum of the losses of multiple pieces of training, performs a second gradient descent, and updates the metalearner parameters. The updated metalearner can quickly iterate when faced with a new Weibo negative sentiment classification task. The experimental results show that compared with the prepopular model, on the Weibo negative sentiment dataset, the precision rate, recall rate, and F1 value are increased by 1.68 percentage points, 2.86 percentage points, and 2.27 percentage points, respectively.

Recently, data integrity for multiagent-based big data environments has been challenging. This paper presents a blockchain-based Merkle DAG structure (M-DAG) for audit data integrity. M-DAG resolves the problem that arises due to the multicopy of a large data volume in a big data environment. It employed Boneh–Lynn–Shacham’s (BSL) signature to verify the integrity of identical multicopy on big data environments. The proposed M-DAG audit mechanism uses a consortium chain algorithm for decentralized traceability and audit to archive reliable data. The evaluation has been carried out for the efficiency of the data integrity audit.

The present study aims to evaluate the influence of latent heat effect during phase change in a three-dimensional finite element numerical simulation of arc welding. A mathematical model is developed to incorporate the effect of latent heat of phase transformation using enthalpy formulation. The accuracy of the developed model was initially validated using available results in the literature and found consistent prediction. The validated numerical model is used to predict the temperature distribution, weld width, depth of penetration, melting efficiency with and without incorporating the effect of latent heat of fusion, solidification vaporization. The results obtained from a developed model incorporating the latent heat effect are in good agreement with the experimentally measured values, whereas a considerable deviation is observed between the predicted values and experimental values without considering the effect of latent heat. It is found that without considering the latent heat effect in the model, the mean error is 14%, 24.6%, 22% and 29.6% for peak temperatures, weld width, depth of penetration and melting efficiency respectively. Therefore, it can be concluded that the effect of latent heat of fusion, solidification, and vaporization is significant for analysis involving phase change and must be accounted for during numerical simulations.

Among the emerging new welding technologies, friction stir welding (FSW) is used frequently for welding of high strength aluminium alloys, which are difficult to weld by conventional fusion welding...

This paper audits the ongoing developments in the field of thermal energy storage based on PCM and comparison of their different properties. Solar energy is bounteously accessible and can be stored utilizing PCMs to counter the increasing demand of this era. There are different types of PCMs available for the same. Main disadvantage with the organic PCM is their poor conductivity. By using nanofluids it is found that the conductivity for paraffin wax may be improved as discussed in this article. Discharge using nanofluid is not so beneficiary because it reduces the time of discharging which is generally not required therefore it is advised to use nanofluid for charging purpose and simple water for discharging purpose to obtain maximum efficiency of the system.

As we are moving towards future, our natural energy resources are exploited day by day so we have to limit our usage for future generation but simultaneously our need is also increasing drastically so we cannot limit our self by using them, but we can modify/alter the design of object so that we can increase the fuel efficiency. As wings are made of Airfoil section, so we can increase the lift force corresponding to drag force generated by the flow of air over airfoil section. The main motive of this study is to compare coefficient of lift and coefficient of drag at different angle of attack for constant air velocity at different airfoil sections provided by The National Advisory Committee for Aeronautics (NACA). We selected NACA 2412, NACA 2414 and NACA 2415 using Computational Fluid Dynamics. To obtain the solution we have to solve steady state governing equations, momentum equations with standard k-epsilon viscous model. The geometry is first imported in design modular of ANSYS, and then import the file into Ansys15 software using Fluent as a solver and CFD – Post as post processor.

For many years titanium-based biomedical devices are gaining a promising place in modern society. Titanium is one of the best suitable materials for manufacturing bio implants and its application areas are orthopedics, dentistry etc. There are many features possess by titanium which make it appropriate are its biocompatibility, resistance to corrosion, wearing, osteoporosis etc. The Cp- Titanium and titanium-based alloys are categorized in three ways depending upon its microstructure such as (α + β), α- type, β-type and comparative analysis are done its behavior, stability through SEM. This review paper discussed the conventional and modern methods of fabricating the bio-implants and also summarizes the various additive manufacturing techniques.

Powder bed fusion process is one of the basic technique associated with additive manufacturing. It follows the basic principle of manufacturing the product layer by layer and their fusion. A heat source focuses its heat over a powder base material and heats the selected cross section area. Sources like laser beam, electron beam and infrared beam are used as heating tool. The process of heating allows the powder to take the shape of the intended object. Powder bed fusion process is compatible to every engineering material such as metals, ceramics polymers, composites etc. this technique is widely used in many industrial sectors such as aerospace, energy sector, transportation etc. A comprehensive overview on powder bed fusion process is presented in this review paper. Other popular techniques like selective laser melting (SLM), selective laser sintering (SLS), and electron beam melting (EBM) are also reviewed.

The present study is solely based upon the comparison of electric discharge machining (EDM) characteristics of AA2024 alloy and synthesised Aluminium metal matrix composite, fabricated with two different weight percentages of Silicon di-oxide (SiO2) as reinforcement. The experiment is performed using optimized critical parameters of EDM which affects the machining characteristics such as material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR) considerably. In this study it is observed that after the reinforcement of SiO2 nano powder (30 nm) in aluminium metal matrix (AA2024), the material removal rate of developed metal matrix nanocomposite (MMNC) decreases whereas TWR and SR increase as compared to the base metal AA2024.

Metal matrix nano composites (MMNCs) have vital role in the field of industrial applications due to its light weight with improved mechanical properties in terms of hardness, tensile strength and having good wear resistance. Aluminium, magnesium and copper have been mostly used to develop nanocomposites injecting the common reinforcing agents such as ceramics particles, carbide, oxide and nitride forms of metals or non-metals. In present work, AA2024-T351 as base metal matrix reinforced with silicon di-oxide (SiO2) nanoparticles having particles size of 30 nm with varying weight percentage. Stir casting method is adapted to get homogeneity in the mixture during synthesis of metal matrix nanocomposite (MMNC). The improved mechanical properties of fabricated metal matrix nano-composites are examined and compared with the base metal.

In this experimental study, we demonstrated the consequence on the charging and discharging time of energy of PCM used with nanofluid Aluminum oxide. During the experimentation the working fluid are water and then the nanofluid Aluminum oxide is used. PCM used during the experimentation is paraffin wax. It has been found that by using nanofluid with paraffin wax in energy storage system, the charging time is enhanced by 25% and the discharging time is reduced by 20%.

This paper presents that the efficiency of thermal energy storage system is increased by reducing the charging time of Phase Change Material (PCM) by using the mixture of hybrid nanofluid (Zinc Cobalt Iron Oxide) and water as Heat Transfer Fluid (HTF). By using nanofluids it is found that the charging time for paraffin wax is reduced to about 25% and discharging time is also reduced to about 20%. Discharge using nanofluid is not so beneficiary because it reduces the time of discharging which is generally not required therefore it is advised to use nanofluid for charging purpose and simple water for discharging purpose to obtain maximum efficiency of the system.

The performance of a grinding wheel is greatly determined by its structure which in turn is influenced by the characteristics of the bonding material. Vitrified bonds were used in 50% of the wheels, which are mixtures of clay, feldspar and fusible materials. Vitrified wheels were fired at temperatures >1270°C. The main aim of this work is to focus on the feasibility of a low melting bonding material that would render the wheels a better or comparatively closer performance level than that of the conventional wheels, thereby attempting to reduce fuel and time consumption. Suitable low melting bonds were chosen based on the results of fusibility tests and chemical analysis, and their properties such as density, sound index (SI) and Young's modulus (YM) were evaluated. Performance characteristics were investigated through a cylindrical grinding test and compared along with the standard wheel. Attempts have been made to reduce the size of bonds to improve their properties, and the results obtained were promising.

Present market focuses on “Know your customer” and relies on advertisement and user’s navigation habits. The data collected from Internet and various Web sites is known as Web-based data, i.e., collection of Web pages. The Web pages available on Internet are in form of different levels and make multilevel taxonomy. Generalized multilevel association rule mining considers the items or predicates mined are at different levels of taxonomy. The generalized association rule mining can help to decide the plans for enhancing the business as well as it will also help to target the promotional offers and advertisement for customers with personal care. In this paper, it has been shown how generalized multilevel association rule mining is integrated to the knowledge discovery process, its potential applications, and techniques. Furthermore, an integrated approach has been presented showing how multilevel association rule mining can contribute to e-business via its great potential. Finally, generalized association rule mining algorithms have been presented for discussing the process of enhancing the e-business.

In order to enhance organizational sustainability, SCM is known as the strategic business policy of the twenty-first century. Supply chain management (SCM) is a methodology which has developed from automation. SCM can be described as an integration of key business processes between end users and original providers who supply goods, services and information. Supply chain management information system (SCMIS) has been increasingly essential in order to operate a supply chain safely and effectively and even to achieve comparative advantages. A successful supply chain without IT cannot be done, nonetheless. Since vendors are distributed across the globe, the operations both inside and outside the company will be coordinated. This document explains the main features of SCIS, its relationship with one another and its relation to performance and teamwork. This document defines the SCIS. In view of the interest of IT in SCM, an effort was made to define the major problems relevant to the usage in SCM.

Present research paper suggests combined Bayesian framework for attribute-based simultaneous localization and map building (SLAM) in common instance of indefinite feature count and relation of data. Through modeling the evaluations and map of feature as RFSs-random-finite-sets, the formulation is on SLAM attribute-based issue will be shown which combined predicts the count and features location and also trajectory of vehicle. More precisely, joint posterior dissemination of group-valued map and vehicle path will be propagated toward timely arrival of measurements, hence including both the management of feature and association of data into one recursion. And the objective of the thesis is applying and experimentally evaluating the RFSs manifold SLAM vehicle in the 3D. And both real-life and simulated datasets are verified for offering the accurate analysis and entire execution of suggested implementation. Moreover, to solve the consistent connection topic of transferring the objects, covariance region connection belief assignment will be implemented for evaluation of motion state and corresponding evidences like vision features, and kinematics are synergized jointly to improve the efficiency of association through the verification fusion model. And concept proof with simulations is fruitfully analyzed and demonstrated.

Inconel 718 is one of the widely used material for combustion chamber of jet engine, Purpose of the study is to obtain an optimal setting of process parameters for single and multi-optimisation resulting in an optimal value of the material removal rate and tool wear rate by varying input parameter current, pulse on time pulse off time and gap voltage while EDM for Inconel 718 using copper cadmium as electrode Taguchi L9 array has been used to design the experiments, the results are further analyzed using MINITAB for single optimisation and MCDM technique named Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE) to investigate the multi-optimization of response characteristics for Inconel 718.

Present synergistic review is an attempt to evaluate compatibility of application of solar energy based systems for water purification. It provides an eagle’s perspective on progressive and contemporary, experimental and theoretical studies of water purification and production. Review focuses on conventional as well as modern techniques of desalination and waste water treatment. Systems modification with application of advanced materials and mimicking nature’s ways of conversion of waste water into potable water in vapor form has been new areas of research. Twenty-first century being marked with consistent and focused effort to conserve natural resources. It can be addressed by putting enhanced emphasis on use of non-conventional energy resources. Hybrid materials, like core shells, blended nanofluids can be used for selective absorptance of ultraviolet and infra-red radiation. This may be utilized in disinfection of certain type of harmful bacteria, and to enhance rate of diffusion through thin membrane. These are an innovative and promising techniques being used in recent years. There has been policy initiative taken by governments and research institutions to use solar energy in devices which are designed for water purification and production. With use of advanced materials for filter design, design modification of solar energy collecting devices, employing suitable photocatalytic conversion processes, area specific need based purification systems can be developed.

A numerical and experimental investigation of gas tungsten arc welding (GTAW) of AISI 304L was carried out to obtain the thermal field, depth of penetration with varying input process parameters. A three-dimensional finite element model is developed to simulate the GTAW welding process considering double ellipsoidal heat source with Gaussian heat flux distribution. A novel iso-volume approach is used to estimate the melting efficiency of the process and calculated maximum melting efficiency of the process is found 44 %. Calculated results in terms of thermal histories and depth of penetration have compared with measured results and are in good agreement.

The present work aims to review the welding behavior of welded AISI duplex stainless steel 2205(DSS). DSS has duel phase structure i.e. austenite and ferrite phases and therefore, combines the properties of both the phases. DSS is commonly used as high corrosion and pitting resistant material in aggressive environments. Welding process involves electrical, thermal, chemical, fluid and mechanical phenomenon. It also involves the melting of the faying surfaces of the DSS and subsequent solidification. These melting involves heating of base metal near to fusion zone which is coined as heat affected zone (HAZ). These region depends on the heat input, thermal field, melting of filler, the rate of cooling, process variables and technique used. The effect of different parameter of welding involved in various welding processes used for DSS welding such as gas tungsten arc welding (GTAW), gas metal arc welding (GMAW), submerged arc welding (SAW), plasma arc welding (PAW), Friction stir welding (FSW), laser and electron beam welding (LBW/EBW) are reviewed. Additionally, a compressive study is done on the effect of welding on corrosion, mechanical properties and subsequently on the microstructure of DSS.

In this paper, a case of demand forecasting for engine oil for automotive and industrial lubricant manufacturing company has been presented. It has been observed that the demand for engine oil mainly depends on three factors i.e. quality, cost, and delivery time. These factors are studied and compared with other competitors dealing in similar nature of products. The quality is associated with three sub-parameters viz. poor, same, and better. Similarly, the cost is mapped with three sub-parameters viz. more, equal & less. Delivery time is linked with two sub-parameters viz. long and short. An artificial neural network model is built on the basis of these causal factors. First, the raw data of demand for a period of past 36 months is collected from supply chain managers of the automotive company. The data for a period of 24 months is utilized to train, validate, and test the model. The next twelve month data is predicted by the trained neural network model. After that, the root mean square error is calculated by comparing the predicted data with the rest 12-month available data. The root mean square error is checked for many cases by manipulation of a number of layers and number of neurons at different locations of the network. The result shows predictions made by the neural network model are in tune with the actual demand given by supply chain managers of automotive and industrial lubricant manufacturing company. Thus, the built neural network model can be utilized for accurate & precise future demand predictions for engine oils.

Aluminium metal foams offer low density (∼10–15% of bulk material) possessing cellular structure that ensures unique features with high stiffens, better energy absorption, thermal and acoustic properties. Selection of different foaming agents for preparing AA6061 foam samples are indeed an industrial relevance for better control over porosity and its dimensions, strengths (tensile, flexural and compression) useful for distinguished applications. Three foaming agents such as wax powder, magnesium hydroxide, and titanium hydride are selected with varying 3–9 weight percentage to prepare metal foams viz. powder metallurgy technique. For the prepared foam samples the percentage porosity, pore dimensions (maximum pore size, and equivalent diameter) and strengths were examined. Wax powder foaming agent resulted with a maximum strength in foam samples compared to magnesium hydroxide and titanium hydride. Scanning electron microscope with energy dispersive spectroscopy analysis revealed that there is no evidence of foreign elements and confirm uniform distribution of porosity in the foam samples.

The term Pi can be defined as the share of the boundary of any circle to the diameter of that circle. Despite the circle’s dimension, this ratio is the same for all circles. Sometimes it is approximated as 22/7. In decimal form, the value of Pi is approximately 3.14. These approximations result in an error during precise calculations because actually, it is an irrational number. Its decimal representation is non-repeating & non-terminating. In this paper, an effort has been made to estimate the value of Pi using Monte Carlo Simulations.

In the current scenario, it is a very difficult task to predict the demand for a particular product in the market. It is very challenging work for the industries to manufacture the product without being acquainted with the actual sale. To meet the demand of customers and to make the supply chain process optimize various strategies are being adopted at each node of the supply chain. Manufacturing the product by the market consumption significantly affects the revenue generation of small and medium scale enterprises especially of the FMCG industry. In this paper, a case study of a medium-scale industry named “Gopal Ji Food Products.” Kosi Kalan (U.P.) has been performed, Highlights of this case study have been kept to know the demand for the number of boxes of biscuits which are to be distributed in the market. The primary work is done by collecting historical data of the requirement of boxes for the last 104 weeks (April 2017 to March 2018). With the help of this data, the demand pattern is known. After knowing the demand pattern, an attempt has been made to develop a prediction model using time series forecasting to acquaint with the number of boxes to be manufactured in advance. The result shows that the data obtained through Non-linear Autoregressive time series forecasting can be used for better planning and fulfilling market demand on time and making the whole supply chain more optimize, effective, and cost-efficient.

Nowadays the higher fuel efficiency is a major concern in every developing field of technology and it is also a cause for the development of lightweight materials. There are many applications in which it is required to join two dissimilar lightweight materials. Friction stir welding (FSW) is the most crucial development for such types of applications. This technique helps in overcoming the challenges raised during the joining of two dissimilar materials due to their incompatibility with conventional welding techniques. The lightweight materials developed with the help of friction stir welding (FSW) have applications in various industrial sectors like automotive, electronics, shipbuilding, railways, marine, and many others. It is inevitable in joining the different grades of materials like magnesium alloys, aluminum alloys, and low carbon steels without any weld defect. The thermal properties like heat generation and peak temperature also have a significant effect on the quality and strength of the weld joint. The thermal properties change the microstructure of the weld material and influence the mechanical properties of the welded material. This provides Temperature controlling methods so as to reduce the surface temperature and hence reduce the defects in the welded material. This present review article is based upon the summary of the work carried out by different researchers in the field of thermal modeling of the friction stir welding (FSW).

The soil stabilization wealth modification of the soil assets by the addition of further material to meet the particular engineering necessities. Techniques for the stabilization would compaction and utilization of admixtures. Utilization of ragged rubber tires in geotechnical engineering for upgrading the soil properties has gained excessive consideration in the present times. The goal of the study might have been to utilize the dissipate material for stabilization of soil to decrease the natural effect. A few reinforcement methods are nearby for stabilizing soils. In the current examination, the ragged rubber from dissipate tires is picked as the strengthening substance and cement of 2% and 4%as binding agent. The binding agent that might have been haphazardly incorporated into the soil at 3 diverse ratios of shredded rubber satisfied, i.e., 5%, 10%, and 15% by influence of soil the examination is concentrated on the performance of soil reinforced by haphazardly incorporated ragged rubber. The examples are subjected to California attitude ratio (soaked and unsoaked) and released density tests. The tests have unmistakably indicated a critical development in the shear power and behavior ability limitation of the soil.