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In today's world, there is an increasing emphasis on the responsible use of fiber reinforced materials in the automobile applications, construction of buildings, machinery, and appliances as these materials are effectively reused, recycled, or disposed with minimum impact on the environment. As such, it has become mandatory to incorporate sustainable, environmental friendly and green concepts in the development of new materials and processes. The primary objective of this study is to manufacture composites using fibers obtained from Thespesia Lampas plants, which are known for their soft, long fibers that are commonly used in various domestic products. The composites are made by combining these fibers with a general purpose polyisocyanurate resin, and their potential applications in both domestic and commercial products are explored. To evaluate the properties of these composites, tests are conducted for tensile strength, flexure, and water absorption.

Titanium alloys are deemed as one amongst the light weight material most preferably adopted in numerous engineering applications due to its exceptional features such as corrosive resistance and thermal strength. These alloys are predominantly used in components of IC engines such as valves and springs, connecting rods. Especially Ti-Grade 5 adopted in aircraft, automobile parts ski plates and bicycles. The preliminary goal of this present research is to optimize the machining variables for Wire Electrical Discharge Machining (WEDM) of Ti-6Al-4V (Grade 5) to accomplish improved rate of material removal and surface finish. Taguchi’s design and analysis method was chosen for devising and examining the experiments by considering input factors (pulse duration and current). An L9 OA was utilized for experimentation to analyze the various output variables, such as surface finish and material removal rate, using the response analysis of Taguchi.

Due to their various features, aluminum alloy can be used in various applications. These include aerospace, automotive, and electrical and thermal applications. Compared to structural steels, aluminum offers superior corrosion resistance and specific strength. Aluminum alloy known as AA 2014 exhibits various mechanical properties. These include its improved strength and weight ratio. It can also be used in military and aircraft applications. Aluminum alloy is commonly used in various engineering applications, such as the manufacturing of structures and aircraft components. Due to its corrosion resistance, it can be utilized in severe environmental environments. Different methods are used in unconventional ways to generate complicated forms of electrical components. One of these is wire electro-discharge machine (WEDM). This process involves making intricate shapes out of conductive materials.

Precipitation Hardened Stainless Steel (PHSS) is one of the martensitic steels that possess exceptional strength and corrosion resistance. Because of its characteristics, this PHSS is exclusively adopted in numerous engineering uses such as nuclear, chemical and marine industries. Welding is one of the important methods of joining that helps to make weldments with better performance characteristics. Corrosion behaviour is one of the important characteristics that contribute hugely to marine and other corrosion-related environments and also this is the most common problem for most of the manufacturing industries. The goal of this study was to analyze the PHSS weldments’ corrosive behavior and compare it with that of the two commonly used welding processes, namely MIG and TIG. The corrosive properties of the weldments were evaluated using various mediums, such as nitric acid, ferric chloride, and Oxalic acid.

Nickel-based superalloys are most commonly engaged in a numerous engineering use, including the making of food processing equipment, aerospace components, and chemical processing equipment. These materials are often regarded as difficult-to-machine materials in conventional machining approach due to their higher strength and thermal conductivity. Various methods for more effective machining of hard materials such as nickel-based superalloys have been developed. Wire electrical discharge machining is one of them. In this paper, an effect has been taken to develop an adaptive neuro-fuzzy inference system for predicting WEDM performance in the future. To analyse the model’s variable input, the paper employs the Taguchi’s design and analysis techniques. The evolved ANFIS model aims to simulate the process’s various characteristics and predicted values. A comparison of the two was then made, and it was discovered that the predicted values are much closer to the actual outcomes.

Superalloys, also known as nickel alloys, are widely employed in a wide variety of engineering applications, including the creation of parts for the chemical processing industry and appliances for the food processing industry. Their high heat conductivity and strength, among other characteristics, make them challenging to machine using traditional techniques. Instead, cutting-edge techniques are typically created for the milling of such tougher materials. In this study, we use a modern method called wire electrical discharge machining, which is typically used for working with tougher materials. In order to anticipate WEDM variables, this paper aims to create a Grey-based Artificial Neural Network (ANN) Model and Adaptive Neuro Fuzzy Inference System. The paper uses a Taguchi method to investigate the model’s varying inputs. The purpose of this model is to visualize the process’s varying performance characteristics.

Scrap collection from any location is handled with mortal interference in several places and companies which may be extremely harmful or even dangerous to humanity. The demand for robotization has risen rapidly in recent years, owing to cutting-edge technologies that minimize manpower and threat-taking training directly or indirectly. The main objective of the paper is to study, analyze, investigate the main contribution of waste collecting by workers while cleaning in the Mechanical Industry. In order to ensure the safety of the workers during cleaning we had implemented the Automatic Trash Collecting Machine in the industry. For Fabricating the Trash collecting Machine first we had analyzed the problem in the industry and then we had started the free hand sketch of Trash Collecting Machine. Then the design work of Automatic Trash Collecting Machine is done in the modeling software Catia V5. Then the material selection for our model has been done.

Photonic crystals are materials for controlling and manipulating the light flow. Nano photonic devices deal with behavior of the light in the nanomaterial and devices. It works on the interaction of nano devices with light. They are periodic structures with different refractive indices. The wave guides can be constructed will have sharp and low-loss bending enabling high integration density of several orders of magnitude. On silicon surfaces, nano- and microstructures are created to lower reflection and increase light absorption. It can be applied to enhance infrared (IR) bolometer applications based on MEMS. In this work Silicon nanowires photonic crystals are grown and the electric characteristics and frequency characteristics are modeled, simulated and studied using finite element method. Waveguide is created by removing a set of wires making a path for signal flow for the frequency within the band gap.

Due to their inherent properties and superior performance over titanium-based materials, nickel-based superalloys are widely utilized in the manufacturing industry. Monel 400 is among them. This nickel-copper alloy possesses exceptional corrosion resistance and mechanical properties. Monel 400 is primarily utilized in the chemical industry, heat exchangers, and turbine component manufacturing. Due to the properties of Monel 400, it is deemed as hard to machine materials with the aid of conventional methods. For investigating the performance of this process, a three-level analysis was carried out. Pulse on duration and applied current at three levels are the independent parameters used for designing the experiments. In this present article, a single-response analysis technique is used which is known as Taguchi to investigate the impact of the various process parameters on the output variables.

Wire Electrical Discharge Machining (WEDM) is a variant of the electrical discharge machining (EDM) process, which represents an innovative method for the removal of material from a workpiece. The aforementioned process is frequently employed for the machining of harder materials that possess intricate geometries. Titanium alloys are a class of lightweight materials that find extensive utilization in many technical applications. Titanium Grade-5 is a titanium-based alloy that exhibits enhanced mechanical strength and improved resistance to corrosion. The objective of this exploratory analysis is to establish empirical correlations between the selected input variables, namely ‘Pulse on,’ ‘Pulse off,’ and peak current, and the desired output measures, which are material removal rate and surface roughness. The experimental design employed the Taguchi method to effectively organize the combination of tests by considering input factors.

Monel 400, a type of nickel alloy which is adopted in numerous engineering fields, such as high-temperature devices. Owing to its better strength and thermal diffusion, it can be difficult to machine with conventional methods. In order to avoid the disadvantages of conventional methods, various advanced material removal techniques have been developed. One of these is Wire Electro Discharge Machining (WEDM). This process is an evolution of the electrical discharge method. In the process of WEDM, difficult materials with intricate forms are usually machined. In this study, the performance of this method on Monel 400 has been analyzed. The three independent variables that are considered when it comes to analyzing the performance of this process are the pulse on, the applied current, and the pulse off. The experiments were performed using the design approach of Taguchi, which involves using an L27 orthogonal array.

SS304 is a type of stainless steel that is well-known for its high ductility and resistance to corrosion; as a result, it is typically utilized in a variety of applications, such as the exhaust systems of automobiles and the springs that are used in seatbelts. Because of its qualities, it will eventually be employed in a variety of body parts, including fuel tanks and chassis, among other things. Due to its properties, SS304 is known to be incredibly difficult to machine using conventional methods. Through a wire electrical discharge machining process, it is easier to cut complex materials with high surface finishes. In this study, a study was conducted on the WEDM process parameters of SS304 to optimize its machining process. The study was carried out using the DoE approach, which involved planning the various experiments. The parameters of the process, such as the pulse on time, peak current, and off time, were analyzed to determine their performance.

Magnesium alloy, known for its high strength and lightweight properties, finds widespread utilization in various technical applications. Aerospace applications, such as fuselages and steering columns, are well-suited for their utilization. These materials are frequently employed in automotive components, such as steering wheels and fuel tank lids, due to their notable corrosion resistance. The performance of magnesium alloy components remains unimproved by normal manufacturing methods due to the inherent characteristics of the material. This work introduces a contemporary approach to fabricating complex geometries through the utilization of Wire-Electro Discharge Machining (WEDM). The material utilized in this study was magnesium alloy. The investigation also considered the input parameters associated with the Wire Electrical Discharge Machining (WEDM) process, specifically the pulse duration and peak current.

Nickel-based superalloys are frequently adopted in various engineering applications, such as the production of food processing equipment, aerospace parts, and chemical processing equipment. Because of higher strength and thermal conductivity, they are often regarded as difficult-to-machine materials in certain processes. Various methods were evolved for machining the hard materials such as Nickel-based superalloys more effective. One of these is wire electrical discharge machining. In this paper, we will discuss the development of an artificial neural network model and an adaptive neuro-fuzzy inference system that can be used to predict the future performance of Wire Electrical Discharge Machining (WEDM). The paper uses the Taguchi and Analysis of Variance (ANOVA) design techniques to analyze the model’s variable input. It aims to simulate the various characteristics of the process and its predicted values.

In addition to traditional methods, there are also non-traditional techniques that can be used to overcome the challenges of conventional metal working. One such technique is wire electrical discharge (WEDM). This type of advanced manufacturing process involves making complex shapes using materials. Utilizing intelligent tools can help a company meet its goals. Nickel is a hard metal to machine for various applications such as nuclear, automobile and aerospace. Due its high thermal conductivity and strength, traditional methods are not ideal when it comes to producing components using this material. This paper aims to provide a comprehensive analysis of the various steps in the development of a neural network model for the manufacturing of Inconel 625 alloy which is used for specific applications such as exhaust couplings in sports motor vehicle engines. The study was conducted using a combination of computational and experimental methods.

A wide range of engineering domains, such as aeronautical, automobiles, and marine, rely on the use of Metal Matrix Composites (MMC). Due to the excellent properties, such as hardness and strength, Aluminum base MMC are generally adopted in various uses. Due to the increasing number of reinforcement materials being added to the MMC, its properties are expected to improve. In this exploratory analysis, an effort was given to develop a new aluminium-based MMC. The analysis of the machinability of the composite was also performed. The process of creating a new MMC using a stir casting technique was carried out. It resulted in a better and more reinforced composite than its base materials. The reinforcement materials were fabricated using different weight combinations and process parameters, such as the temperature and duration required to stir. Due to the improved properties of the composite, the traditional machining method is not feasible for machining of these materials.

One of the most common types of lightweight materials used in aerospace is magnesium alloy. It has a high strength-to-weight ratio and is ideal for various applications. Due to its corrosion resistance, it is commonly used to manufacture of fuselages. Unfortunately, the conventional methods of metal cutting fail to improve the performance of magnesium alloy. One amongst the most common methods used for making intricate shapes in harder materials is through Wire-Electro-Discharge (WEDM). In this study, we have used magnesium alloy as the work material. The independent factors were selected as pulse duration and peak current. The output parameters of the process are the Surface Roughness (SR) and the Material Removal Rate (MRR). Through a single aspect optimization technique, Taguchi was able to identify the optimal combination that would improve the effectiveness of the WEDM process.

Among the challenging materials used in high-temperature applications is Inconel 625. Due to its low thermal coefficient and greater strength, traditional methods tend to produce poor results when it comes to turning Inconel 625. In order to overcome these issues, a new approach has been proposed that utilizes unconventional techniques. WEDM is a variant of the electrical discharge manufacturing process that is commonly used in the production of complex components. It is mainly utilized for the hard to machine parts. A study on the process parameters of WEDM for the machining of Inconel 625 was performed by utilizing the analysis of Taguchi. The study focused on the various parameters of the process, such as peak current, pulse on time, and off time. The performance measures that were considered in this study included surface roughness and material removal rate. The results of the analysis revealed that the various process variables affected the performance indicators.

With the progress of manufacturing industries being critical for economic development, there is a significant requirement to explore and scrutinize advanced materials, particularly alloy materials, to facilitate the efficient utilization of modern technologies. Lightweight and high-strength materials, such as aluminium alloys, are extensively suggested for various applications requiring strength and corrosion resistance, including but not limited to automotive, marine, and high-temperature applications. As a result, there is a significant necessity to examine and evaluate these materials to promote their effective use in the manufacturing sectors. This research paper presents the development of an Artificial Neural Network (ANN) model for Computer Numerical Control (CNC) drilling of AA6061 aluminium alloy with a coated textured tool. The primary aim of the study is to optimize the drilling process and enhance the machinability of the material.

This study mainly focuses on the blending of Alumina and Titanium oxide nanoparticles (NP’s) in Spirulina biodiesel blends (SB20) to estimate the influence of engine (combustion, performance and emission) parameters of a diesel engine. The characterization of Al2O3 and TiO2 NP’s like SEM were reported. By using various fuel samples such as Diesel, SB20, SB20+40 ppm AO, SB20+80 ppm AO, SB20+40 ppm TO and SB20+80 ppm TO, the engine tests on the diesel engine were conducted at various load conditions. The BTE for SB20+80 ppm AO were enhanced by 12.35% and 8.4 % compared to the SB20 fuel and SB20+40 ppm AO fuel samples. The combustion parameters were improved for the NP’s as additives (Al2O3 and TiO2) fuels than the SB20 fuel sample because NP’s contain oxygen content. The parameters of engine exhaust emissions such as HC, CO and smoke are drastically diminished for the SB20+40 ppm AO, SB20+80 ppm AO, SB20+40 ppm TO and SB20+80 ppm TO fuels compared to the SB20 fuel.