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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.

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.

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.

Inconel 718 is a superalloy made from nickel that has exceptional mechanical properties. It has been widely used in the manufacturing of various components such as nuclear and aerospace aircraft. Due to its exceptional corrosion resistance, this material can be utilized in various environments. Due to the increasing number of challenges that come with conventional methods of welding, the use of advanced techniques has been developed to produce better and sound quality joints. One of these is Laser Beam Welding (LBW) technique. This method utilizes a high-intensity beam to create a better and more quality weld joints with improved mechanical properties. This study aims to develop multiple regression models that can be used to analyze the performance of laser beam welding on Inconel 718 alloy joints.