The welding of dissimilar materials finds a wide variety of applications in the fields of industrial construction and manufacturing, where the characteristic features of the different materials are optimized for the desired application to result in cost effectiveness and value addition. Non-fusion welding methods such as solid state welding and high energy beam welding are more popular for welding dissimilar metal combinations, due to fewer complications, than fusion welding, which melts the base metal and forms brittle intermetallic compounds (IMCs) that may lead to failure. Various factors have to be considered when assessing the feasibility of welding dissimilar metals and producing a sound weld joint. This paper presents a broad classification of the most commonly used welding processes for dissimilar materials, discusses some of the commonly used welding processes with examples of some common material combinations, critical factors for good welding, and practical difficulties arising from the physical and chemical properties of materials. From the findings, it can be inferred that continuous improvement and research is still required in the field of dissimilar metal welding, particularly in the light of increasing demand for tailored material for modern engineering and industrial applications.
Technical innovations in robotic welding and greater availability of sensor-based control features have enabled manual welding processes in harsh work environments with excessive heat and fumes to be replaced with robotic welding. The use of industrial robots or mechanized equipment for high-volume productivity has become increasingly common, with robotized gas metal arc welding (GMAW) generally being used. More widespread use of robotic welding has necessitated greater capability to control welding parameters and robotic motion and improved fault detection and fault correction. Semi-autonomous robotic welding (i.e., highly automated systems requiring only minor operator intervention) faces a number of problems, the most common of which are the need to compensate for inaccuracies in fixtures for the workpiece, variations in workpiece dimensions, imperfect edge preparation, and in-process thermal distortions. Major challenges are joint edge detection, joint seam tracking, weld penetration control, and measurement of the width or profile of a joint. Such problems can be most effectively solved with the use of sensory feedback signals from the weld joint. Thus, sensors play an important role in robotic arc welding systems with adaptive and intelligent control system features that can track the joint, monitor in-process quality of the weld, and account for variation in joint location and geometry. This work describes various aspects of robotic welding, programming of robotic welding systems, and problems associated with the technique. It further discusses commercially available seam-tracking and seam-finding sensors and presents a practical case application of sensors for semi-autonomous robotic welding. This study increases familiarity with robotic welding and the role of sensors in robotic welding and their associated problems.
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