Akhil Garg – författare

This book presents the fundamentals of arc phenomena, various arc welding power sources, their control strategies, welding data acquisition, and welding optimization. In addition, it discusses a broad range of electrical concepts in welding, including power source characteristics, associated parameters, arc welding power source classification, control strategies, data acquisitions techniques, as well as optimization methods. It also offers advice on how to minimize the flaws and improve the efficacy and performance of welds, as well as insights into the mechanical behavior expressed in terms of electromagnetic phenomena, which is rarely addressed. The book provides a comprehensive review of interdisciplinary concepts, offering researchers a wide selection of strategies, parameters, and sequences of operations to choose from.

This book presents machine learning as a set of pre-requisites, co-requisites, and post-requisites, focusing on mathematical concepts and engineering applications in advanced welding and cutting processes. It describes a number of advanced welding and cutting processes and then assesses the parametrical interdependencies of two entities, namely the data analysis and data visualization techniques, which form the core of machine learning. Subsequently, it discusses supervised learning, highlighting Python libraries such as NumPy, Pandas and Scikit Learn programming. It also includes case studies that employ machine learning for manufacturing processes in the engineering domain. The book not only provides beginners with an introduction to machine learning for applied sciences, enabling them to address global competitiveness and work on real-time technical challenges, it is also a valuable resource for scholars with domain knowledge.