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Modern automobile applications such as petrol, diesel, and gaseous fuel injection system use dissimilar Inconel 718 (IN718) and Stainless Steel 304 (SS 304) joints. IN 718 is a precipitation-hardened austenitic nickel-based superalloy with exceptional qualities such as high strength, resistance to corrosion, greater toughness, as well as resistance to thermal induced fatigue at elevated temperatures (between 150 and 1500oC), while SS 304 is a T 300 Series austenitic stainless steel alloy that can be used successfully in wide range of applications due to greater resistance to corrosion, good high and low temperature strength and ductility with excellent weld ability and formability. To get a better understanding of the mechanical characteristics of these heterogeneous weldments, these alloy joints were created using laser beam welding, one of the most modern joining techniques for high-strength materials.

Laser Beam Welding (LBW) is one of the advanced methods of joining metals by fusion. The LBW process exhibits comparatively better welding performance than conventional processes and this method of welding approach is exclusively employed in higher volume applications such as automotive industries. One of the most common nickel alloys used in various engineering fields is Inconel 718. This material has high strength and corrosion resistance properties, and is commonly used in high-temperature applications, such as gas turbines and rocket engines. In this study, we aim to develop an artificial intelligence tool that can analyze the influence of various process variables on the design and performance of a metal. The experiments were planned using the design approach of Taguchi. An L27 orthogonal array was used for the experiments. The three performance measures are the top width, bottom width, and penetration.

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.