Advances in Science and Technology Vol. 130

Abstract: Fundamental investigation of mechanical properties on different types of dissimilar welded joints was described in this paper. Dissimilar metal welding was generally employed in chemical and petrochemical plants, oil and gas industries, nuclear power plants and aerospace industries etc. For enriching the structural integrity of aerospace industries, material with high temperature resistance and high corrosion resistance is needed. For fulfilling the above criteria, Inconel 718 (IN 718) was selected due to its felicitous strengths such as yield, tensile, and creep at high temperatures with significant corrosion properties. This paper reviews the different welding processes and the impact they have on mechanical properties, as well as some difficulties related to welding dissimilar metals. Gas Tungsten Arc Welding (GTAW) process comprises high micro-hardness and tensile strength properties during dissimilar welding of IN 718. SS 410 and Inconel 625 materials hold high micro-hardness and tensile strength values respectively. The effect of IN 718 filler metal has also been discussed in this paper. Some of the dissimilar welding defects can be eliminated by IN 718 filler metal. This paper will give better directions to the researchers to focus on future studies.

Abstract: Friction stir welding (FSW) is a solid–state joining process that is increasingly being used in various industrial applications due to its numerous advantages over conventional welding techniques. FSW uses a non-consumable rotating tool to generate frictional heat and plasticize the material in the joint, resulting in a defect-free, high-quality bond between two pieces of metal without the need for any filler material or shielding gas. The process is particularly well-suited for welding lightweight and high-strength materials, such as aluminium, magnesium and titanium and is known for its ability to produce joints with superior mechanical properties, including high fatigue strength and improved corrosion resistance. This paper addresses the need for future development in Friction Stir Welding.

Abstract: Additive manufacturing (AM) is gradually occupying a unique place as a viable industrial manufacturing technology for parts with complex geometry and difficult-to-machine materials. The capability of AM to apply to such parts in various sectors of industry, including automotive, aerospace, and medical devices, stems from the layer-by-layer building process and manufacturing directly from computer-aided design (CAD) models. All AM processes share a common set of steps and characteristics but are distinct in the type and form of raw material, energy source, and supply to the target location to build the layers. Based on these differences, the AM processes have been classified into different types: material extrusion-based processes, powder bed fusion (PBF) processes, direct energy deposition (DED) processes, and photo-polymerization processes. All the AM processes induce certain defects in the parts, making the final mechanical properties inferior. A capability to edict the mechanical properties of the parts by identifying defects in layers can help in designing parts and planning for AM to reduce those defects. The present work investigates the feasibility of applying a machine learning (ML) based technique to identify typical AM defects. The idea of transfer learning of a pre-trained network, namely, AlexNet, with a limited-size dataset of defect images generated from the layer images has been studied. A novel yet simple and effective experimental setup has been devised to capture high-resolution images of the layers of the part in a fused deposition modeling (FDM) machine. From these layer images, a total two hundred defect images have been captured and converted into an input image dataset for transfer learning. After suitable modification of the pre-trained network, the training and validation gave an accuracy of about 62%. Two different techniques of hyper-parameter tuning were then conducted, through which the accuracy of training improved to more than 95%. Based on the success achieved, further possible tracks of future research have been suggested.

Abstract: Friction Stir Process (FSP) is considered one of the most convenient, effective, and environmental friendly manufacturing processes. In these processes, a tool involves a pin that blends the material around it and a shoulder that creates frictional heat. On the other hand, the pin mixes the soft material to refine the grain structure. This paper aims to investigate a thermal model using Altair to numerically simulate the temperature distribution profiles of 7075 Aluminum Alloy material using FSP. Using a novel technique called Smoothed-Particle Hydrodynamics (SPH), we extracted the temperature distribution in the Stir Zone (SZ) for 900 RPM, 1200 RPM, and 1500 RPM Tool Rotational Speed (TRS) with constant Tool Traverse Speed (TTS). The temperature results obtained are incremental with increasing TRS. As a result, the temperature achieved from 900 RPM to 1500 RPM has increased by 21.20%. In addition, the obtained temperature is almost 50% of the melting point. The material flow on both Advancing Side (AS) and Retreating Side (RS) shows the thorough material mixing. The SPH technique helps to investigate the proper material flow modeling by dividing the AS and RS nodes and it was observed that they have thoroughly been mixed near the FSP tool pin.

Abstract: The metals and metal oxides that are synthesized at the nanoscale have found a wide range of applications in a variety of fields including textile, food, automotive, cosmetic and pharmaceuticals. These nanoparticles (NPs) possess unique properties including surface area, shape, size, optical properties, low toxicity, huge band gap and high binding energy. As a simple, affordable, and secure material for human welfare, ZnO NPs are of particular importance among the other NPs, which possess exceptional thermal and chemical as well as distinctive optical properties. The green manufacturing technique of ZnO NPs using plant/herbage extract has been documented by various researchers over the past decade. But still, there is number of prevailing issues that prevent the large-scale production of NPs and subsequent applications. This article reviews the recent (2021 and 2022) literature on the simple, efficient, affordable and environmentally friendly green methods for bio-synthesis of Zinc salts such as zinc sulphate (ZnSO₄), zinc nitrate (Zn (NO₃)₂) and zinc acetate (Zn (CH₃CO₂)₂) using different plant/herbage extract which are collected from various locations. Zinc salts were utilized as a precursor in this method and phytochemicals presents in the plant extract reduces the zinc salt to zinc oxide and stabilize the NPs. Discussion has been done for characterization of synthesized ZnO NPs and also the activities including Anti-cancer, Anti-fungal, and Anti-bacteria.

Abstract: The dry turning was done on the high tensile low alloy steel. The Indoloy carbide tool was used. The input parameters were speed, feed, and depth of cut (DOC, d). The chip reduction coefficient (CRC) and von Mises stress (VMS) were the output responses. Universal tensile testing was done to find out the strength coefficient (K) and strain hardening exponent (n). "K" and "n" were incorporated to obtain the von Mises stress (VMS). The experiments were performed following the L₉ array (Taguchi). The analysis of variance (ANOVA) was done for the CRC, with the lower the better condition. The ANOVA was done for VMS with the lower-better condition. The ANOVA was done by developing a MATLAB program. The feed contributed strongly to both the CRC (80.1381% contribution) and VMS (33.1490% contribution) minimizations. A Taguchi-Fuzzy inference system (FIS) simulation was done (MATLAB software) to select optimal parameters. CRC and VMS were the inputs, and MPCI (multi performance characteristic index) was the output for the simulation. The simulation was done based on the rules. The optimal parameters were found at moderate speed, high feed, and moderate DOC. Machining chips were collected for different experimental conditions. The chip form study was done. The chip surfaces were examined in the scanning electron microscope (SEM). The simulation result was validated by chip form study and SEM observation of chip.

Abstract: Electric ship propulsion is no longer a revolutionary idea in the marine sector today. Lights were the first thing that needed electricity on board a ship, and it later applied to an electric ship propeller that is powered by an electric motor. Eventually, the idea of all-electric ships enters the picture, allowing all ship power sources to run both auxiliary and propulsion loads. Due to the great electric power constraints, numerous electric motors are used in industrial and naval ships, and the development of power electronics has made it easier to manage and regulate these motors. The switching resistance motor is becoming more popular despite its low dependability and straightforward design. Such benefits make SR motors superior to conventional adjustable speed devices. Due to their significant torque fluctuations, variable reluctance motors have recently been used in restriction traction systems. On the other side, torque ripple reduces motor performance by generating repeated noise and vibration. The suggested system controls the speed of an 8/6 pole SRM using a metaheuristic Grey Wolf Optimization Algorithm (GWO), Proportional Integral (PI) controller, and a (n+1) Semiconductor (n+1) Diode power conversion. This article's goal is to increase the proposed Switched Reluctance Motor's output cogging torque. GWO algorithm has been chosen as a promising strategy when compared to other algorithms because of its generality, decreased complexity, stability, and accuracy. MATLAB/Simulink was used to create the simulation tool.

Abstract: Mobile robots have gained popularity in recent decades, owing to its capacity to be deployed in dangerous environments without jeopardizing humans. Mobile robotic vehicles are frequently used today to carry out tasks including environmental recognition, inspecting urbanized and industrial terrains, for search and rescue activities. Presently, search and rescue robot technology is progressing from experimental and theoretical studies towards applicability. The proper execution of a mobile robotic movement in a working environment depends on being aware of the nearby obstacles and avoiding any collisions that may occur. Robots today are integrated with several smart technologies that are necessary to model the environment and localize their position, control the movements, identify obstructions, and avoid obstacles based on the terrain and surface they are employed on by applying navigational procedures. This paper explores the various mobile robotics systems and their working currently in place utilized for rescue and search operations.

Abstract: Remote sensing technology is essential to various industries such as agriculture, meteorology, surveillance, defence, manufacturing and processing industries. Several sectors widely adopt this technology, so much research has been conducted in this domain. In satellite applications, research in remote sensing has been performed for seven decades. Images and videos captured by satellites have less resolution, which undoubtedly reduces object detection and data analysis accuracy. After analysis, the imprecise nature of captured data might cause difficulties in fields such as defence and agriculture. To combat this problem, in this research, we developed a hexacopter-based modern remote sensing device that can fly with manual intervention and also has an emergency autopilot function. The proposed system is equipped with a compact high-resolution camera which captures images with a higher frame rate. The developed system uses the YOLO v4 algorithm, which is fast and accurate to recognise and track an item or a particular individual in real time. Logged data is shared with the ground station to perform the desired task. The hexacopter-based system has more mobility than the satellite-based system, which overcomes the drawback of the limited range of the proposed system. In this proposed system, we have connected a precise flight controller and a Raspberry Pi 3 Model A+ microprocessor board with other electronic components to more accurately control hexacopter flying and real-time object identification and tracking.