Intelligent Manufacturing and Energy Sustainability

This paper presents experimental results on the thermal performance of low volume concentration (0.002%, 0.004% and 0.007%) TiO2/ethylene glycol nanofluid. Investigations are conducted using a counterflow heat exchanger in the range of fluid temperatures from 30° to 70 °C with Reynolds number ranging from 200 to 700. It is concluded that the non-dimensional heat transfer coefficient Nu increases with Reynolds. Addition of nanoparticles to the base fluid by 0.007% increased the thermal conductivity by 2%. Experimental results show that there is reduction in heat transfer coefficient as a function of temperature that corresponds to the reduction in Prandtl number. Important results are presented in graphical and tabular forms.

Robot calibration is a process to enhance the accuracy of robot manipulator through modification of the robot control software. The repeatability motion causes wears and tears to the robot joints that deteriorate the robot accuracy and repeatability. These wears and tears affect the position and orientation of the end-effector at any point in the workspace relative to a fixed known coordinate frame which is a set of three orthogonal right-handed axes X, Y, and Z, called principal axes. To compensate and improve the absolute positioning accuracy of serial link manipulator, a cost-effective measurement system was applied to calibrate the robot using theodolite system. The calibration process was carried out at the point of interaction between the workpiece and the end-effector of the Fanuc 430iF series arm robot. The experimental method of the robot calibrations was explained, analyzed, and evaluated. The analysis of inaccuracies and the sources of errors in the calibration was discussed. The outcome of this calibration procedures has the potential to be used to correct the inaccuracies in specific components of the robot joints and then improve the performance of the robot.

Manual production of fish cracker is inherenly inefficient with low productivity. Mechanisation and automation of the drying process which constitutes a major process would contribute to increase production. In this study, a batch type convection dryer for fish cracker with a capacity of 2 kg was developed. The prototype with a dimension of 89-cm length, 72-cm width and 60-cm height consists of a drying chamber, moving tray, transmission system, heating element and control system. A moving tray concept was applied for the machine design. The maximum temperature that can be reached in the chamber without load is 40.0 °C. Two different air velocities of 1.5 m/s and 2.0 m/s were applied in both simulation and experimental study. The higher air velocity was observed to shorten the time taken to heat the overall drying chamber. It was observed that the air velocity is higher when the tray rotates close to the fan inlet at the angle of 135°. The simulation results are consistent with the experiment in terms of temperature profile and air velocity. As a result, the dryer has successfully improved the drying hygiene and maintain the quality of fish cracker produced.

Main focus of this research work is to analyze the impact of mechanical behaviour (hardness) and tribological behaviour (wear properties) of Graphene reinforced Magnesium alloy (AZ91D) consisting of metal matrix compound. During this analysis, 1% reinforcement found in Graphene molecules by weight to the Mg alloy (AZ91D) to generate a compound by applying the technique of bottom poured stir casting. Wear analysis technique (wear and frictional coefficient) has been incorporated on the DUCOM pin and on the setup of disc tribometer, with the utilization of metal matrix composite (MMC). For experimental designs, Taguchi’s optimization technique has been incorporated. To study the wear resistance phenomenon of the MMC, “Smaller the better” criteria have been taken into consideration as an objective model. The operating parameters like applied load (30 N, 40 N, 50 N), disc rotating time (4, 6, 8 min) and disc rotational speed (500, 650, 800 RPM) are optimized through analysis of variance (ANOVA) along with signal to noise ratio analysis. From the statistical study of ANOVA, finally, it is concluded from the observation that tribological behaviour is significantly affected by rotational time and the load applied on the disc.

Aluminium is a binary alloy has a larger importance to engineering industries with excellent wear resistance and stiffness that have been designed for lightweight and higher strength applications in the automobile sectors. To synthesis the hybrid metal matrix composite, silicon carbide is chosen as primary reinforcement varied at different weight fraction (1, 2, 3, 4 wt%) with a constant boron carbide of 3 wt% used in the present study was carried through liquid metallurgy technique. The composites were then subjected to mechanical and wear properties study. The effect of reinforcement particles by increasing various weight fractions have been investigated and characterized mechanical and wear properties. The 4 wt% of SiC/B4C reinforced composites tends to increases hardness and tensile strength to 29.7% and 20% as compared to the base alloy.

In the present work, the effect of uniaxial stress on ferroelectric properties, energy storage and harvesting is studied for the 0.4Ba(Zr0.2Ti0.8)O3-0.6(Ba0.7Ca0.3)TiO3 (0.4BZT-0.6BCT) ceramics. Therefore, hysteresis loops were measured at different uniaxial compressive stress and temperature. The ferroelectric parameters (maximum polarization, remanent polarization, hysteresis loss and coercive electric field) decrease with an increase in stress. This is because the uniaxial compressive stress depolarizes 0.4BZT-0.6BCT by switching dipole in the energetically favorable direction (generally away from the electric field or poled direction). The maximum recoverable energy storage was found as 73.7 kJ/m3 at 100 °C and 80 MPa. Results show that the uniaxial compressive stress increases the stored energy density by 22% and stored energy efficiency from ~20% to ~38% at 22 °C. The maximum energy harvesting was obtained as 100 kJ/m3 when the cycle was operated between 5–160 MPa and 0.75–2 kV/mm at 22 °C.

In this paper, we have studied various types of sensors like chemical sensors, electrochemical sensors, biosensors, optical sensors, and mass-sensitive sensors. These sensors measure the temperature, velocity liquid level, displacement, pressure, vibrations, force radiation, chemical species, and strain at the nanoscale. Then, we have also reviewed different subsequent parameters like accuracy, precision, linearity, resolution, and hysteresis which are using for their characterization. In this paper, we have also discussed the applications of nano-heterostructure in various fields like biomedical, optoelectronic, etc., which are made by using various nanomaterials like Si, Si-Ge, GaAs, AlGaAs, InP, InGaAs, AlGaN, CdS, AlInGaP, ZnS, ZnSe, CdSe, SiC, GaN, and HgCdTe.

People were able to convey intentions and feelings through non-verbal languages such as gestures and facial expressions. However, recognizing facial expressions is a very difficult task. Numerous factors such as light, posture, and distortion can cause complications. The proposed system is a good method for facial emotion detection problems. The system, which considers the elements of the face, will help to predict emotions from an image. Then histogram of oriented gradient (HOG) is used to encode these facial elements as features. A linear support vector machine is then used to identify facial expressions. The final results of this experiment show the accuracy of our prediction.

Polycaprolactone (PCL) is an auspicious material for bone repair and bone replacement due to similar naturally occurring inorganic components. In this work, the polycaprolactone (PCL) scaffolds are manufactured using pneumatic extrusion method and scanning electron microscopy (SEM) images of the manufactured scaffolds can be produced to display the interior of the scaffold struts and the profile of in vitro release can be done to reveal the biocompatibility of the scaffolds. In order to confirm the performance of the manufactured composite scaffolds for the required strength of bone loadbearing regions, the UTM tests are carried out, and after this, the Taguchi optimization technique was applied to the numerical data derived from the experiments with the concept of the L9 orthogonal array. From this, it was determined that 40% porosity scaffold, 30 and 90 filament angle, 0.5 mm nozzle diameter is a sophisticated design compatible with the structure and function of the natural bone trabecular part. Taken together these results show that PCL scaffolds can be manufactured easily using 3D printing technology and can be a possible solution as implantable material for bone tissue engineering application.

An indoor space resembling a 4-occupant office room was modeled to evaluate the airflow characteristics of the Mixing and Displacement Ventilation system under different air supply rates. The room was created with box-shaped occupants seated in front of the table. The occupants along with the PCs placed on the table served as the heat sources in the domain. The supply airflow rate considered for the study was 6, 9, and 12 ACH. Three-dimensional CFD simulations were performed using the Fluent Solver. The airflow pattern, air velocity distribution, and temperature distribution showcased that the obtained flow-field is a strong function of the ventilation strategy being implied in the room. For identical air supply rates, the displacement ventilation system showcased a cooler sensation to the occupant.

The design and analysis of airfoil of an UAV at a low Reynolds number has been discussed in this paper. The new airfoil designs are being hampered by the aerodynamic attributes at low Reynolds number flows. The first step is to identify the design of the wing and the requirements for the analysis and then to formulate all the related concepts. Based on literature survey, analysis is piloted with four main design parameters using design concepts. Selection of airfoil is done using 2-dimensional computational fluid dynamic (CFD) analyses. Later, the verification of Xfoil is conducted by comparing the in hand wind tunnel data with the results of the Xfoil. The demerit of Xfoil compels us to use a 3-dimensional CFD analysis tools along with fluent so as to overcome it. Considering the lift and stability and requirements of the airfoil at various stall patterns, GEMINI and NACA0012 are considered for the wing and tail airfoils, respectively.

South Asian countries are facing a problem of transport vehicle emission. Electric vehicle with low or even a zero-emission is seen as a potential solution for the tail pipe emission. The environmental impact of lithium-ion battery has been undertaken in this study. One battery pack used in three-wheel electric rickshaws chosen as a case. It has nominal capacity of 3.69 kWh which is considered which is able to be used up to 40,000 km of driving distance for 400 cycles for a period of 3 years. This study reveals the environmental footprint associated with the lithium-ion battery production, use and recycling phases. The result shows that the production phase generates higher impact compared with other phases. In this use phase, electricity losses due to battery charging also cause environmental impact. Valuable materials are recycled in the end-of-life waste management phase contributing benefits and earning environment credits.

The alarming increases in the utilization of fossil fuels in the energy sector had led to serious environmental threats in the last two decades. To meet the noticeable rise in energy demand, while maintaining the sustainability of the environment, power generation from renewable energy resources is the recent highly preferred technology. Among these, floating photovoltaic (FPV) systems are becoming increasingly competitive. Admittedly, high-efficient power production from underused surfaces of water sources is the reason for increased investment by global nations. Thus, it is necessary to analyze the structural components of FPV systems making them unaffected by external sources deterring uninterrupted power supply. This study provides insights into FPV technology in mitigating the evaporation rate on installed water bodies and discussing the key elements involved designing an FPV system with comparisons of real-time design examples.

The most efficient primary drivers are diesel engines. In order to safeguard the global environment and long-term security of energy, alternative fuels with equivalent qualities to petroleum-based fuels need to be developed. Contrary to the rest of the globe, India’s demand for diesel fuels is around 6 times that of petrol hence it is logical to look for alternatives to mineral diesel. Bio generated fuels present the developing nations with a viable answer to the double crises of depletion and degradation of fossil fuels in the environment. Due to the worldwide emphasis on the reduction of greenhouse gases (GHGs) and a clean development mechanism (CDM), bio-fuels are given additional emphasis. The usage of vegetable oil increases the usage of gasoline and Brake-specific fuel consumption (BSFC). It is injected in droplets to compensate for the insufficient mixing of fuel. CI engine is performed without substantial problems of long-term operation and durability. However, the transesterification step requiring chemical and process heat inputs adds significant processing costs. Vegetable oils can be crucial to decentralised power production for irrigation and electricity in rural and remote parts of developing nations where grid electricity is not accessible. Different types of vegetable oils in these remote places are cultivated/produced locally, however, owing to logistics challenges in rural locations they cannot be processed chemically. Hence, using heated or blended vegetable oils as petroleum fuel substitutes is an attractive proposition. Given this fact, Jatrophan oil on engines, typically used for agriculture and irrigation, and the decentralising generation of electricity, was used for a number of engine experiments in the current research. In order to minimise different operating issues, heating and mixing were utilised to reduce the viscosity of Jatropha oil.

An automatic grading system is necessary for fresh destemmed chilli fruits. In previous works, a CNN model has been built to identify the diseased damages that appeared on the fruit’s body, and a flipping mechanism has been designed to entirely recognition by rotating the fruits. This work focussed on evaluating and implementing the CNN model to classify the diseased damaged ones on the grading model. The training data set was updated to enhance the success rate of the recognition process. Tests were carried out on 1320 fruits, in which there were 920 non-damaged fruits and 400 damaged fruits. The total testing time is 6600, and the success grading rate was found out at an average of 92%. In addition, the limitation and the causes of errors were also clarified to determine the improvement for future works.

With every passing year, there is an exponential rise in human population. Due to this, the challenge of not having enough cultivable land is becoming a rising issue. It is also predicted that most of the world’s population that currently lives in rural areas will have shifted into urban cities. This will lead to an increase in urbanization and a further reduction in arable lands for agricultural purposes. As a solution to these issues, this paper proposes the idea of vertical farming and Hydroponics in specific. Hydroponics uses a fraction of the space required for traditional farming, uses 90% less water, and can reap practically organic produce all year round. This paper reviews the process of vertical farming, its benefits, and its different types. A detailed methodology that can be adopted to create a hydroponic system has been suggested. In this paper, Lettuce, Basil, and Kale have been used as primary examples.

In this project, the design of an automobile sheet metal component is done which is used as a bracket for an automobile handlebar. The main aim is to prevent burr at the edges, with optimum cutting clearance, straightness, and no bend marks, wrinkling formation, thinning at the bend region. To achieve this, the operations involved are blanking, notching, bending, and piercing operation where it has been done in a progressive way of tooling rather than eight stage tools. The number of parts per stroke is two numbers (LH + RH). For obtaining this sheet metal component, a progressive tool with eight stations is required, where the above operations are performed on the strip in a progressive way and feed has been from left side of the press. Analysis has been carried out on the punches of the press tool using Ansys 18.1. Software. The press tool has been designed using NX.10 Software. Finally, the deformation, stresses acting on the press tool has been calculated. Punches are made of D2 Steel material. As the result, lowest stress 13 MPa is in bending punch 1 and highest stress 538 MPa is in parting off punch is compared with ultimate tensile strength of D2 steel 600 MPa which is within acceptable limits.

In this study, ARMCO iron sheets were subjected to severe plastic deformation through a potential sheet material processing technique called constrained groove pressing. This single phase polycrystalline material is imposed to effective strains of ~3.48 and ~4.64 after 3rd cycle and 4th cycle of constrained groove pressing process, respectively. Uniaxial tensile tests were carried out on all deformed ARMCO iron sheet samples at room temperature. During this tensile loading performed at a constant strain rate, an attempt was made to study the strain hardening behavior by identifying different stages of strain hardening using Kocks–Mecking (K–M) plots. It is shown that there is an increment in strain hardening rate in these deformed materials with increasing constrained groove pressing cycles. In both the deformed conditions, stage-III is prominently appeared. This stage is estimated to mark the development of dislocation cell structures, where dislocation activity explains strain hardening behavior during various cycles of severe plastic straining.

Welding the steels using aluminum have greater applications, and this combination will help to decrease the overall weight of assembled units. Two metals with dissimilar thickness will be aligned in lapped position wherein a spot weld, it is performed using non-consumable pin profiled tool. Welding is performed based on the friction generated by the rotating tool on the dissimilar metals. This heat generated during the friction helps the dissimilar metals AA6062 with the structural steel ST1020 to join which are taken with thickness of 0.3, 0.5 and 0.7 mm with a rotating tool made of ‘H13’ material and pin profile is taper at the end. Three parameters with three levels have been used to perform joining operation. Minitab software is used for design of experimentation, and ANOVA is utilized for the validation of larger the better.

The spur gear is an extensively used machine part where transmission of power is required between the shafts. The need for better spur gear is always there for the present market. Hence, there is a constant strive among the researchers to improve the design and productivity of the spur gear. In this regard, companies are looking forward to develop an advanced system for the design and development of the spur gear. A knowledge-based system can facilitate automating the design process with much more effectiveness. Hence, a knowledge-based system is required to address design and CAD modeling issues automatically. This paper presents an attempt to develop a preliminary approach for generating the spur gear automatically by CAD software based on the minimum design requirements inputs. Advanced modeling techniques like the parametric modeling technique is used to reach the target. Further, the proposed approach has proven itself as the better than the traditional approach where human is involved in CAD model generation.

This paper is on the design of an automatic robot for the welfare of the poultry. The poultry farming is a growing segment of the agriculture in India. The poultry farming creates significant air pollution. To reduce the environmental impacts of the poultry farming, a waste management is considered as the effective method. The implementation of a waste management in the poultry farm incurs the physical contacts between the birds and the personnel and leads to the spread of different diseases. To resolve these problems, an automatic robot is designed. The robot continuously maneuvers on the floor. The underneath tool scrubs the floor and makes the litter and bird waste upside down. Therefore, the odor and the time required to dry the waste reduce. In addition, the bird movement and the production rate are increased.

In the medical profession, ultrasound imaging for clinical recognition is far better suggested than any other imaging mode because of its adaptability, suitability, safety, and viability. The images that are taken and then preprocessed as part of the procedure are crucial in medical diagnosis. Different types of noise can be added to the images during the uploading process. The more deteriorated the image, the more difficult it is to better isolate the required components, recognize them, and examine edge clarity. In this study, a comparison is made between several filters such as Gaussian, Kuan, Lee, guided, and anisotropic filters, as well as the proposed filter, which is based on the cellular automata principle. Developing the proposed filter using the cellular automata approach yields superior results in terms of image parameters accessible for consideration.

The traditional CAD modeling approaches for IC engine pistons are tedious because of the complexity in geometry and design calculation. A little change in size or shape of IC engine assembly will cause an extensive chain reaction in calculating the associate modifications because of different interrelated plan issues. Therefore, the CAD model of the piston should be changed in order to match the modification(s) of the IC engine. The CAD modeling techniques, like parametric modeling, offer the answers for these issues. This paper presents a framework for generating the CAD model of an IC engine piston by using SolidWorks. A dedicated GUI was developed in the CAD software for helping the design engineers to feed the input data. The presented framework uses the reuse of the design information.

Internal combustion engines consume rich mixture during engine start-up to warm up the catalytic convertor, which is most efficient while operating at 600–800 °C temperature range. The overall life of the catalytic convertor is highly dependent on operating temperature, since noble metals are used for construction. Though modern vehicles are equipped with advanced technology to warm up the catalyst, it does not have a dedicated heat management system for the catalyst. With latest statutory pollution test requirements, the eventual lifespan of a vehicle equipped with factory-fitted catalytic convertor remains uncertain. Hence, a dedicated thermal management system is necessary for the catalytic convertor, which should be economical and compatible with existing vehicles for retro-fitment. This paper focuses on the quest of reducing automotive emissions through technological advancement. A potential solution for emission reduction is proposed by employing more stringent control on the catalyst’s operating temperature, also improving its life.

Life is a problem-solving workbook. In today’s technological world, new technology is being invented on a daily basis. Robotics is the most appropriate technology for surveillance purposes in order to identify the occurrence of related events. As we all know, robots are capable of performing surveillance tasks with a high level of integration while using a surveillance device. To develop long-range portable assistive-aided car system for user. This project presents a reconfigurable sensor network for structural monitoring of a user. In this project, we have built an all in one voice control car using custom mode PCB. This robotic car can perform as Bluetooth voice control robot, self-balancing robot, and obstacles avoidance robot. This robots batteries are powered using a solar panel. This robot can be useful for Industrial automated equipment carriers. This robot can be used for surveillance. All this things are done by Arduino UNO microcontroller.

The main objective of this research paper is to suggest the best alternative option for continuous power supply in the institute campus Nalanda College of Engineering, Chandi, Bihar in a cost-effective way. In this paper, four different hybrid combinations of solar photovoltaic, fuel cell generator, wind turbine generator, diesel generator, battery, and external grid have been studied. It has been observed that the solar PV-fuel cell battery hybrid system is the best alternative to replace the external grid system to supply continuous power in the campus. Among all four cases studied using hybrid power system optimization software, the levelized cost of ₹11.69 per unit is obtained providing a sustainable source of electricity for a greener future.

This research paper involves available solar energy conversion to useful electrical energy, which is utilized for battery charging to procure maximum power from SPV. The state variables of the solar photovoltaic panel such as voltage, current, and power are utilized for battery charging. Maximum power point tracking technique is utilized for harnessing maximum available solar energy. MPPT is used for the best utilization of the SPV panels to improve efficiency of solar module. At MPP, battery as a load is charged, and solar energy is stored in the it. Optimal operating point of the system used to perform tracking through DC-DC boost converter. The converter is used to control the switching action of IGBT by controlling duty ratio. Perturb and Observe (P&O) algorithm is used in this work. The battery performance in terms of state of charge (SoC), battery current, and voltage is verified for different irradiance in MATLAB/SIMULINK platform.

Jigs and fixtures are special production tools which are used to make the standard machine tool and more adaptable for different operations to be done. Jigs and fixtures are the economical ways to produce a component in mass production. The present work deals with the design of machining fixture for drilling operation for a drill bit of top hammer which is termed as drifter bit. Without jigs and fixtures, this component machining is carried out by manual indexing, setting the work piece for every single component, etc. Therefore, to meet the present production requirement, the time required has to be reduced by using a fixture that can hold the component on a 5-axis machine. A hydraulic fixture is designed for good manufacturability and assembly, and proper fixture elements and hydraulic elements are selected. Model is developed in Creo 4.0. Deflection and von miss stresses are predicted by using ANSYS 17.2 software. Total equivalent stress of the structure is 9.816 N/mm2. At the required cutting force, the maximum deflection obtained is 10 microns. The actual permissible limit is 15 microns. So, the obtained value is within the permissible limits for the required cutting force.

Robust techniques for pose estimation are crucial for robotic manipulators which enable efficient object grasping for industrial applications. The determination of the manipulator joint parameters is very complex and cumbersome. Simulation of these reduces the complication involved in understanding the analysis and implementation behind robotic kinematics. This paper discusses the kinematics of the PUMA 560 robot manipulator for appropriate actions using MATLAB/Simulink in its vision-enabled robotic workspace. The 2D image is processed to estimate the position and orientation vectors which activate the 6R manipulator for further actions. A graphical user interface (GUI) using MATLAB Robotics toolbox is integrated through which one can emulate robotic movements. The graphically represented results can be analysed easily as they are accurate, efficient and suitable for real-time application.

There is a tremendous rise in pollution in recent times due to the increased use of sophisticated equipment in many domestic and industrial applications. There is a considerable increase in dangerous emissions like chlorofluorocarbons (CFCs) due to the use of refrigerants. On the other hand, the increasing demand for refrigeration systems in transportation emphasizes portable refrigeration systems. The portable refrigeration works with electricity to provide the cooling effect. This system is free from emissions. In this work, a mobile refrigeration system is designed and developed on a bottle. The developed model is a bottle that is thermally insulated and has a Peltier module and batteries for the electric power supply. It has a digital temperature controller for displaying the temperature of the fluid. Various characteristics of the developed portable refrigeration model have been studied. It is observed that the optimum condition is obtained when the device is working with the power supply of 10.5 W.

Since the first Industrial Revolution, the focus has shifted from mechanical production to smart manufacturing. The revolutionary term Industry 4.0 introduced in twenty-first century has still not been adopted worldwide due to various challenges in the manufacturing and production industries. There are concepts like lean and Six Sigma which have been introduced in the industry which helps to reduce waste and remove the unwanted processes. The Internet of things (IoT) with supply chain management (SCM) helps in building relations with suppliers as well as with other industries worldwide. Implementation of concepts like lean, Six Sigma, IoT in SCM, and Industry 4.0 will be helpful to industry to rely on technology rather than human work, production can be fast, and the ongoing processes can be upgraded. This paper gives a brief insight about the challenges and advantages of implementing these concepts in SCM and Industry 4.0.

Pervious concrete is a material developed from ancient history but was not in use because of strength issues. Pervious concrete is also determined as gap graded concrete, permeable concrete and no fines concrete. It is a type of concrete with greater porosity and is used for concrete flat work applications. This type of concrete allows the water to percolate in to the ground by reducing the storm water runoff and also recharges the ground water levels. Pervious concrete has found to be an authentic tool for storm water management. It is a compound made by blending concrete which is a coupling material with cement, coarse aggregates and water in required extents. Pervious concrete is generally low in strength but high in permeability. To increase compressive strength, several fibres are added.

Hands are the primary means of germ transmission, which results in the transmission of deadly diseases. Hand hygiene is thus an important measure to prevent the spread of harmful diseases. The World Health Organization (WHO) has recommended seven steps for proper handwashing hygiene. However, not everyone adheres to the WHO’s handwashing guidelines of seven steps. A proper hand wash is an important factor in protecting people’s health during the corona virus disease (COVID-19) pandemic, especially for healthcare workers who are exposed to bacteria, influenza, and other infectious diseases. There are technologies available like ultraviolet (UV) images to check a person’s hand hygiene. However, there is no real-time system to monitor how efficiently a person makes his or her hand wash. A real-time monitoring system is needed to check people’s hand wash hygiene in public places and hospitals, reducing the risk of spreading communicable diseases. In this paper, we have discussed predicting the accuracy of handwashing actions performed by humans using a deep learning model with transfer learning (VGG16).

Scheduling of jobs has a significant contribution to the improved performance of the job shop production system. This study is aimed at developing efficient priority dispatching rules (PDRs) for scheduling in a job shop to improve the tardiness and flow time performance measures. The selection of PDRs depends on the scheduling criteria and job shop conditions. LEKIN software can be used for a variety of well known job shop conditions and varying flexibility. Different schedules are derived using the LEKIN scheduling software for different PDRs such as earliest due date and shortest processing time. In this work, seven static dispatching rules have been taken from the literature study, and four new priority dispatching rules have been proposed and compared to schedule two formal job shop problems under four objective functions, whose aim is to improve the performance measures. The results show that the proposed PDRs are very effective in minimizing various performance measures.

The paper is based on the vibration measurement using a low-cost MEMS accelerometer kit. The MEMS accelerometer kit is developed using an open-source literature. The main components of the kit are ADXL 355 MEMS accelerometer, microcontroller, SD card and the batteries. The vibration measurement test on the electrical cooler is performed using the developed kit. It measures the acceleration in three axes x, y and z. The measured vibration response is validated with the phyphox application available for the smartphone with inbuilt accelerometer. The time domain responses acquired from both MEMS acceleration kit and the smartphone are analyzed using fast Fourier transform (FFT). The results are in good agreement. The developed kit can be used for measuring vibrations in the various applications. The cost of the kit is significantly lower than the conventional piezoelectric accelerometer.

In the present society, everyone is busy in their work-life and other activities without having time to consult doctors which they treat as simple issues during the initial stages but as time passes these may convert into life risk parameters. So for the early prediction and prevention of diseases, the proposed system maintains a public cloud that stores the information about different patients along with various symptoms and probable diseases as a matrix. For predicting the type of disease, symptoms are collected from the user and passed as input to the stacking algorithm. The patient’s records are collected from different hospitals, and this acquired huge amount of data cannot be handled using a local server so to provide a solution. A big data framework integrated with machine learning algorithms is deployed in the cloud. In the existing systems, big data tools like Hadoop, Apache Spark, and others are popular implementations at the same time the potential risk factors with these tools.

Performance and emission characteristics of various biodiesel blends prepared in a ratio by volume from a mixture of sunflower and soybean biodiesels are studied. It was found that the engine’s performance characteristics like indicated power, indicated mean effective pressure, and the volumetric efficiency of the blend D70X15Y15 are higher than the other blends (16.75, 1.3, and 0.77%). It was also found that the blend D40X40Y20 has a significant effect on the break thermal and mechanical efficiencies than the other blends (23.32 and 17.83%). The air/fuel ratio is decreased with the increased load of all blends. The percentage of decrease in A/F is about 0.24–4.3%. And for all other blends, there is an increase in the A/F ratio. The emission characteristics of all blends are presented for the load. A significant decrease in CO and CO2 emissions for the biodiesels D50X25Y25, D70X15Y15, D40X30Y30 up to 7.96–15.74% and 1.26–12.94% than that of diesel, respectively. The nitrogen oxides are decreased up to 4.8–18.2% with blends D70X25Y5, D40X30Y30, and X100 Y100. The smoke opacity for all blends X100 and Y100 are decreased up to 11.7–20.6%.

Biodiesel is the most promising alternative source to petroleum fuel which reduces emissions as well as the dependence on fossil fuels. Nanoparticles are used as combustion catalysts to improve performance characteristics and to reduce emissions. In this experiment, copper oxide (CuO) nanoparticle are added to the Jatropha biodiesel B10 and B20 blends for this study. Jatropha biodiesel is used in the blend of B10 and B20. Copper oxide is added in 50 and 100 ppm to the Jatropha biodiesel blend. The experimental results show that the performance and emission characteristics have been improved by adding copper oxide to the Jatropha biodiesel blends. BSFC reduces by 9.2%, brake thermal efficiency increases by 10.2%, and NOx, CO, HC, and smoke emissions are reduced by 17%, 25%, 20%, and 11.5%, respectively for B20 with 100 ppm of CuO nanoparticles.

The social media applications like Facebook, Twitter, and others have gained a lot of name and fame and are represented as “Online Social Networks” (OSN). These networks are similar in their usage and can access with ease. With this popularity, people are sharing their personal sensitive information without checking any privacy policies, which made cyber-attacks easier nowadays. Most teenagers and women are getting affected by these cyber-attacks. Hackers take away the profile information of existing users in a profile cloning attack to create duplicate profiles, which are then used to compromise the identity of the original profile owners. This process is known as “Profile Cloning,” this cloning can be created on the same site or another site. Nowadays, hackers are creating fake profiles in cross-site, i.e., other social networks which are rare from the popular OSN walls. So, the users do not have any clue about their accounts on other platforms. Moreover, to simplify the registration process, the OSNs are not asking for authorization details which became an advantage for hackers to create millions of fake accounts. The proposed KNN algorithm is compared with the probability algorithm naïve Bayesian.

Nowadays, rapid growth in vehicles on the road causes traffic congestion, a considerable problem. Accidents, noise, long lines at intersections, health damage, and other facets of the transportation sector of modern society are all impacted by this problem. A reliable traffic management system (TMS) is needed in the contemporary world to resolve traffic-related issues and improve the transportation systems’ safety and overall efficiency. TMS collects data from various sources and analyses it using various techniques like artificial intelligence, optimization, data analysis etc., to identify hazards and then provides services to mitigate them. In light of this, this article reviews the recent developments, challenges, and potential prospects of implementing a traffic management system.

The proposed research paper is to illustrate the execution of the round seam welding machine based on the programmable logic controller (PLC) automation. This machine aspires to increase the production rate of the product that requires welding on the circumference. It is an innovation from manual welding to automatic welding for any rounded border welding industrial part. For a worker, it is very difficult to rotate and weld the product simultaneously. This modernization shifts the arduous task to surveillance work for the labor. Panel designing and wiring of PLC with the welding machine was simulated in “SolidWorks Electrical.” “DELTA” PLC was used to move the pneumatic cylinder that holds the welding torch, and it also helps to rotate the plate using the AC motor where a product is placed. The PLC was encrypted with ladder logic programming using the “ISP Soft” software.

Nowadays, analyzing the road surface conditions is one of the most important aspects of road infrastructure which in turn leads to the better driving conditions and minimizes the risk of road accident. Traditional road condition monitoring systems falls short of collecting real-time update about the road conditions. In earlier models, road surface condition monitoring is done for the fixed roads and static speed of the vehicles. Various systems have proposed approaches of utilizing the sensors mounted in the vehicles. But this approach will not help in predicting the exact location of the potholes, speed breakers and staggered roads. Therefore, smartphone-based road condition assessment as well as the use of the navigation has gained a great existence. We propose to analyze different machine learning approaches to effectively classify the road conditions using accelerometer, gyroscope and GPS data collected from smartphones. In order to avoid noise in the data, we also captured the videos of the roads. This dual technique to data collection will help in providing a more accurate location of potholes, speed breakers and staggered roads. This way of data collection using machine learning algorithms will help in the classifications of roads conditions into various features such as smooth roads, potholes, speed breakers and staggered roads. This information will be provided to the user through the map by classifying the various road conditions. Accelerometers and Gyroscope sensors will investigate various features from all the three axis of the sensors in order to provide a more accurate location of classified roads. Investigate the performance using SVM, random forest, neural network and deep neural network to classify the road conditions. Hence, our results will show that the models trained with the help of the dual technique of data collection will provide the more accurate results. By using neural networks will provide significantly more accurate data classification. The approaches discussed here can be implemented on a larger scale to monitor road for defects that present a safety risk to commuters as well as provide maintenance information to relevant authorities.

A Go-Kart is a four-wheeled vehicle having low ground clearance and does not involve a differential and suspension. The present study focuses on the analysis of an electric Go-Kart chassis frame based on proper material selection and optimized chassis thickness. To find the optimum material and thickness, a comparative analysis was conducted with three different materials, namely AISI 1018, AISI 1020 and AISI 4130, which were selected based on their yield tensile strength values. Similarly, the effect of stress on thickness variation of the chassis is analysed by varying the thickness values between 1.4 and 2 mm in a step of 0.2 mm. From the numerical studies, the results show that the AISI 1018 is the suitable material based on the factor of safety, weldability and machinability. Optimizing the thickness of the chassis helps chassis weight and cost reduction.

Meeting our daily scheduled events in time has always been a challenging task to be accomplished. The recent advancements in the NLP area developed many general-purpose personal assistants like Google Assistant, Alexa, Siri, etc., that can perform a vibrant range of tasks and remind the user about various tasks. The existing schedulers have not taken the real-world factors like traffic, the current location of the user into consideration while managing the user schedule and reminding the user about an event. Thus, the development of an efficient task scheduler is still a challenging problem. This paper proposes a personal task scheduler to assist the user by considering both event time and current user location. We used technologies like Dialogflow and Google Maps APIs for developing a web application prototype for our reminder system that reminds the user dynamically without having a preset time.

When you think about the global situation, there is a sea of opportunity for skilled people all over the globe, and for a given opportunity, the workers shift from one company to other that leads to a high attrition rate within the company. Nowadays, employee attrition is treated as a severe problem by all the companies due to the negative impact on productivity at work and on completing company goals and vision in time. To deal with this problem, companies are now relying on machine learning methods to predict employee attrition rate. These methods work on products based on employee data analysis and the degree of prediction by the models. With accurate results, all the companies may take necessary actions in a timely manner for retaining or dismissing the staff. The system currently in use is the human resource’s data system which does not work well in predicting how efficient the worker will be to the institution in future. These models that are used by the companies are now outdated and do not help them in successfully making decisions; in this paper, we have used modern machine learning algorithm models for predicting employee attrition that is employee’s plan to either leave or continue working within the organization based on available huge data set to give more close results.

In this work, it is aimed to find and analyse natural frequencies and optimise resonance conditions of roll cage of an All-Terrain Vehicle. The analysis is done to predict failure modes of the frame of the vehicle under harmonic analysis. Further investigations are made to minimise the resonance and effect of engine vibrations on roll cage by using dampers such as ethylene propylene diene monomer (EPDM) rubber engine mount. ANSYS workbench is used for simulations and modelling.

Agricultural automation is an important subject for high production yield of crops and minimizing work time on farms, and multipurpose vehicles can be utilized for agricultural work to address financial issues. Purchasing of three different vehicles for farming activities is not affordable for small-scale farmers in Asian and African countries. To overcome this problem, a new multi-specialty vehicle combining the three fundamental farming activities of tilling, plowing, and reaping was designed. The multi-tool light agricultural vehicle (MTLAV) is advantageous for small to medium farms and hill areas. The whole design was carried out in CATIA, and analysis was done using Ansys. Structural analysis was performed for the plow and tiller. This work aims to provide a cost-effective solution for agricultural problems that plague farmers in Asia.

Effective identification of Alzheimer’s disease (AD) becomes primary importance in biomedical research. Recently, deep models have reported with high accuracy for AD detection compared to general machine learning (ML) techniques. Nevertheless, identifying brain disorder like AD and tumor is still challenging, and for classification, it requires a highly discriminative feature representation to separate similar brain patterns. Present state of AD detection techniques using various deep learning (DL) models is studied here. Features of personal data, genetic information, and brain scans were focused. This includes required preprocessing steps with neuro-imaging data that extracted from single and multiple modalities. Performance of deep learning mechanisms and their accuracy values obtained are described. Although deep learning has achieved notable performance in detecting AD, there are several limitations, especially regarding the availability of datasets and training procedures.

Unified power quality conditioner (UPQC) is a custom power device (CPD) which can be used for voltage quality (VQ) and current quality (CQ) improvement. In this paper, the working of UPQC is given with AI techniques like “fuzzy logic controller” (FLC), “artificial neural networks” (ANN), and “adaptive neuro-fuzzy-inference system” (ANFIS). MATLAB software is used for simulation, and Simulink results are verified. Total harmonic distortion (THD) of source current and load voltage of system are calculated with each of these three methods, and the results are compared.

The transient nature of forces produced in the system requires vibration analysis to determine their behavior patterns accurately. Modal analysis represents the dynamic response of the bridge structure via modal descriptive terms: natural frequencies, mode shapes, and damping ratios. Accurate measurement of these dynamic characteristics for structures allows for better evaluation of structural stability and structural health monitoring of such systems. It is time-saving as well as useful to use force vibration analysis to approximate modal parameters. Natural frequencies are derived from the observations of force vibration analysis techniques. Modified power spectral analysis and cross-power spectral analysis are carried out to identify the structure’s resonant frequency. From the experimental analysis, the range of resonant frequencies observed is 0.9766–4.8828 Hz in longitudinal direction, 1.9531–4.88828 Hz in transverse direction, and 2.9297–4.8828 Hz in vertical direction. Accurate modal parameters estimation of the structures allows better evaluations of structural stability and structural health monitoring.

With exponential increases in population, the need for water has equally gone up. Water resources are rapidly drying up, whether it is used for drinking or agricultural and industrial purposes. The main aim is to study aquaponics systems that would efficiently use water and analyze methods of monitoring and controlling the parameters concerning water quality. This paper focuses on the study and analysis of different techniques to enhance aquaponics systems’ efficiency through IoT-supported automation techniques. AVR microcontroller is interfaced with aquaponics systems through IoT to obtain readings to monitor the system parameters remotely. With this automation process, it can be more convenient to maintain an environment optimal for both the plants and fish. The results reveal methods used to balance the water quality conditions and how automation increases system efficiency.

The outbound operation of steel plate yard is a time-consuming job in shipbuilding. Crane should retrieve outbound plates from different stacks. If the outbound plates are blocked by other plates, relocation is required in advance to replace blocking plates to other stacks. To reduce the unproductive relocation, the retrieval and relocation operation should be well-planned. In this paper, we proposed a stack-based outbound operation method. Outbound plates are retrieved based on a specific stack sequence and blocking plates are relocated as much as possible to stacks without outbound plates. We proposed the mathematical model of this method, and a heuristic algorithm is introduced. The computational experiment shows that our method can get good results in a short time.

The paper focuses on the processing of FSW and to have the position of conditions to improve the efficiency for welding of the materials to improve the strength. The research has taken place innovative manner for different input process parameters for significance taken place by studying and understanding of a lot of literature survey for different speeds and tool angles. The position of the tool takes a major role in the designing of the tooltip to have the particular position to weld today’s scenario of the investigations. The experimental design and microstructural investigations were planned with the help of the Taguchi method. The responses are calculated based on experimental work to get the position of the optimal welding process of the technology to help the society satisfying environmental conditions. The responses are calculated and carried on the optimization techniques of multiple responses applicable and helpful for this method. It is quite possible to optimize the optimal conditions for the output responses more than one. So, this method is very helpful and proved to be very effective in finding the multiple responses which can yield the optimal results.

The experimental and simulation investigations are meted out to review heat transfer, friction characteristics of twisted and plain ducts. In the present work, Reynolds number varied from 7000 to 40,000 the flowing fluid is considered as air. Twisted duct is a new invention to reduce pressure drop and also increases heat transfer. The practical work has meted out and also experimental setup depends on plan of investigations to induce the best possible warmth transmit and less significant in pressure fall. Then, numerous parameters are such as: hotness, flow rapidity, mass flux, inserts. Twisted ratio of the duct is considered as 6.12. All values and analysis are considered in terms of Nusselt number and Reynolds number and friction factor. The outcome of the experiment shows that twisted duct Nusselt number shows 1.90 times more than the plain duct and also thermal performance of the twisted duct is obtained as 1.43. In this current work, numerical simulations are performed by using ANSYS 18.2FLUENT. In the present work hotness transmit, statistical flow patterns like heat transmit, frictional resistance graphs of twisted and smooth ducts are studied.

This work presents a comparison between a predictive control and a PID control applied to a flow process, covering technical and theoretical aspects that range from the acquisition and estimation of mathematical models, to the design and implementation of controllers using an OPC communication gateway. The evaluation of its performance is carried out based on the characteristic parameters of a transient response to a step-type signal, and additionally its behavior is also evaluated in the face of disturbances of external origin, thus allowing to establish causes for the implementation of one or another controller in the control of the flow variable.

Small and medium enterprises (SMEs) are investing in adoption of digital manufacturing technologies to scope system complexity, increase information visibility, improve production performance, and gain competitive advantages in the global market. This article presents an analysis of the technology adoption models for the implementation of digital manufacturing to identify which factors influence the implementation process. We discuss the methodology for using technology adoption models. We hope this work will help multidisciplinary research efforts to advance in the adoption of digital manufacturing technologies in SMEs.

Titanium is one of the super-hard alloys and the fastest-growing materials used in defense, aerospace, and biomedical sectors due to its outstanding properties like high strength to weight ratio, better corrosion resistance, and good fatigue life. In traditional machining methods like turning, milling, and grinding, the required surface finish for biomedical and aerospace applications cannot be obtained for titanium alloys. To overcome these problems in aerospace and medical areas, one of the latest innovative methods employed is cryogenic burnishing and HA powder burnishing. In this work, surface characterization is studied using the scanning electron microscope and corrosion analysis is studied using an electrochemical corrosion test. SEM micrographs and corrosion analysis confirmed that better surface roughness is obtained in traditional burnishing and better corrosion resistance is obtained in the HA powder burnishing.

The detection of defects in a product is one of required production process for quality control. Currently, the quality control process of metal screws uses many manpower for manual inspection. Hence, this study about to implement faster region-based convolutional neural network (faster R-CNN) to detect the micro-defects on metal screw surfaces. The defects of surface damage, stripped screw, and dirty surface screw considered in this research. Raspberry Pi 3 with a camera module is used for image acquisition of the metal screws in determining various kinds of defects. The image is also acquired to be used for the training of the faster R-CNN. A testing is carried out to test the performance of the model. The experiment outcome shows that the detection accuracy of the model is 98.8%. The model also shows superiority in this project detection method compared with the traditional template-matching method and single-shot detector (SSD) model.

Electrical submersible pumps (ESP) are a pump classification, which is typically connected to an application of transporting fluids located in submersible elevations into supply pipelines. These pumps type can be found in offshore oil and gas facilities and are often used as transfer pumps for liquefied natural gas (LNG) terminals. In multiphase applications such as in LNG transport, operational challenges from the presence of air pockets and bubbles present a cavitation and degradation risk to the pump components. This paper proposed a computer simulation model using CFD analysis in ANSYS Fluent to study the effects of multiphase flow (gas–liquid flow) on ESP while varying the rotational speed with constant flow rate and inlet gas volume fraction (IGVF). Flow rate and IGVF kept constant with 20 L\min and 1%, respectively, while rotation speed varied by 500, 900, 1500, 2000, and 2500 rpm. The CFD results show that at low rotation speeds a large gas pocket performed at impeller inlet. However, by increasing the rotation speed, this gas pocket collapses to bubbly flow at the impeller inlet which leads to losses in high kinetic energy and concentration of bubbles at the impeller outlet and volute.

Screws are essential and widely used hardware because of their ease of use and very high joint force. A screwdriver is a device utilized for screwing and unscrewing the screws. For years, screwdriver somehow got very little attention, and hence, very little innovation in the designing and manufacturing took place within the years. This paper presents the design of the “pistol”-type VSR (variable speed reversible) electric screwdriver and an economical and effortlessly assembled open-source screwdriver based on the Arduino micro-controller chip platform. This design allows users to avoid using awkward wrist postures, attempting to fasten or unfasten screws with manual screwdrivers. The 3D model of electric screwdriver is designed and optimized in PTC Creo Parametric 3.0. The apparatus contains planetary gear system, a DC motor, optical groove coupler module, and a variety of sensors. Additional features, such as an LCD, are placed to display torque, and RPM is added to the screwdriver.