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This paper proposes a 3‐Dimensional Finite Element Model (FEM) for the simulation of magnetic flux distribution in a Magnetically Impelled Arc Butt (MIAB) welding process. The electromagnetic force responsible for the arc rotation in MIAB welding process is governed by the magnetic flux density in the gap, the arc current and the arc length (gap size). To be precise the radial magnetic flux density is a critical factor in arc rotation and weld quality. The aim of this study is to explore the interdependence of the magnetic flux density and the existing current in the coils using finite element code ANSYS. The results of this analysis are verified with the available experimental data for steel pipes (outer dia 50mm and 2mm thickness). The results of the numerical simulation emphasize that the magnetic flux density in the gap between the pipes is proportional to the exciting current.

This paper aims to investigate two control mechanisms on the two parameters, namely, spindle speed and tool pin position, while performing friction stir welding (FSW) for aluminium metal matrix composites (Al-MMC) using the concept of system identification.

FSW is a feasible choice for joining of Al-MMC over the fusion welding due to the formation of the narrow heat-affected zone and minimizing the formation of intermetallic compounds at weld interface. The goal in FSW is to generate enough thermal energy by friction between the workpiece and rotating tool. Heat energy is generated due to mechanical interaction because of the difference in velocity between the workpiece and rotating tool. The generated heat is proportional to the tool pin position and the spindle speed. In the present work, a Smith Predictor Control scheme and adaptive control scheme are developed during joining of Al6061/SiC/B4C Al-MMC by FSW. Adaptive controller is developed to control the tool pin position while Smith Predictor control is developed to control the spindle speed. Initially, the Al-MMC plates are prepared at five combinations of SiC and B4C reinforcements and welded at three level parameter settings followed by tensile testing. The experimental data are used in estimating the plant transfer function model using system identification. The control schemes are then developed for the estimated plant model and the same are validated using a standard PID controller. In both the control schemes, PID controller results in a sluggish response. Experimental validations are performed for the developed control schemes followed by microscopic studies of the weldments.

In both the control schemes, PID controller results in a sluggish response. Experimental validations are performed for the developed control schemes followed by microscopic studies of the weldments.

Results from the study concluded that the developed MRAC and Smith predictor scheme effectively controlled the vibrations and spindle speed effectively.

It is observed that the scanning electron microscopy micrographs of the Al-MMC’s welded using developed control schemes resulted in good boding with homogenous distribution of reinforcement particles.