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The numerous applications and desirable attributes of Monel 400 urge many researchers to undertake multiple systematic evaluation studies for diverse manufacturing operations. Because of their exceptional mechanical qualities and great corrosion resistance, nickel-based alloys, particularly Monel 400, are increasing in popularity in a variety of applications. Because of their tendency for rapid work hardening and low thermal conductivity, these materials are particularly difficult to machine using traditional manufacturing techniques. Advanced material removal methodologies have been applied to eliminate such drawbacks and are regarded as a suitable alternative approach to traditional machining processes. Based on the Electrical Discharge Machining technique, Wire Electrical Discharge Machining was developed, which a sophisticated machining technology is used to machine hard materials with complex forms in any electrically conducting materials.

In view of the improvements in manufacturing sectors, which are an important component of any economy’s growth, there is a significant need for new and advanced materials, particularly alloy materials need to be analysed and investigated so that new technologies may be effectively utilized. Materials with low weight and high strength, such as aluminium alloys, are recommended for a variety of applications that require both strength and corrosion resistance, such as marine applications and high-temperature applications. Aluminium alloy Al 5052, a nonferrous material with outstanding properties is an Al-Mg alloy with high thermal conductivity and corrosion products that are non-toxic. Minimum Quantity Lubrication (MQL) is a cost-effective and environmentally friendly method of lubrication employed in a variety of machining processes. The investigation of CNC milling of AA5052 alloy with standard Tungsten Carbide (WC) tool inserts with MQL settings are detailed in this paper.

The alloy investigated in this research is Precipitation Hardened Stainless Steel (PHSS) 15-5, which provides good corrosion, high strength and hardness. 15-5 Stainless Steel is extensively employed in a variety of applications, including aero plane components, high-pressure corrosive environments that include valves, fasteners, shafts, fittings and gears. In this current exploration, an analysis of the machinability of PHSS is analyzed with textured inserts and the outcomes as compared to conventional inserts. To increase the machinability conditions, two distinct types of textures were produced on the rake face of the tool inserts and employed for this machining procedure utilizing a Wire Electric Discharge Machine (WEDM).The dimensions of the textures were cut on the trial-and-error method. Three different machining parameters with three different levels were chosen. Cutting Speed, feed rate and depth of cut were chosen as the input parameters.

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.

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.

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.

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.

Considering the advancements in manufacturing industries, which are crucial for economic growth, there is a substantial demand for exploration and analysis of advanced materials, especially alloy materials, to enable efficient utilization of new technologies. Lightweight and high-strength materials, like aluminium alloys, are highly recommended for various applications that necessitate both strength and resistance to corrosion, such as automobile, marine and high-temperature applications. Therefore, there is a significant need to investigate and analyse these materials to facilitate their effective application in manufacturing sectors. This study investigates the machinability of drilling AA6061 using a micro-textured tool and proposes an Adaptive Neuro Fuzzy Inference System (ANFIS) model for investigating the machinability of drilling AA6061 aluminium alloy with a micro-textured uncoated tool.