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Authors: Dr. SELVARAJ MANICKAM, Er. D. KARUNAKARAN, Dr. S. SENTHIL MURUGAN,
Dr. HARI PRASADARAO PYDI.
Welding is a complex process that necessitates careful
consideration of various factors, including welding speed, arc
voltage, and arc current, along with features related to joint
geometry. Elements such as base material thickness, joint shape
(fillet, butt, or corner joint), joint grooves and gaps, weld bead
height, and weld penetration play crucial roles in achieving a
successful weld. The nonlinear nature of welding makes it
challenging to identify the interconnected components and factors
involved in the process. In the past, automated welding was
predominantly utilized for lengthy and intricate projects. However,
recent advancements in digital technology have facilitated the
integration of robots into welding equipment, thanks to their
capabilities. This has led to the exploration of programmable cells
for specialized applications, marking a shift from traditional
assembly structures to more adaptive and agile systems. The
constant consideration of updated automation in these systems,
coupled with the adaptability and programmability of mechanical
robots, has made them integral in a wide range of modern
assembly structures. The current surge of interest in neural
networks may be attributed to the recognition that the brain
performs calculations differently than traditional digital
computers. While computers excel at swiftly and accurately
executing operations based on explicit instructions, the unique
Format | Paperback |
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Language | English |
No. of Pages | 198 |