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.

This book provides a systematic description about the development of Isogeometric Topology Optimization (ITO) method using the density, and then addresses the effectiveness and efficiency of the ITO method on several design problems, including multi-material structures, stress-minimization structures, piezoelectric structures and also with the uniform manufacturability, ultra-lightweight architected materials with extreme bulk/shear moduli, auxetic metamaterials and auxetic meta-composites with the NPRs behavior in microstructures. A detailed MATLAB implementation of the ITO method with an in-house code "IgaTop" is also presented.

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 summarizes a series of research work on integrated process planning and scheduling (IPPS) done by the authors, focusing on discussing the properties, novel solution methods and applications of process planning, scheduling and IPPS problems under different machining environments. It is a valuable reference resource for teachers, students and researchers working in the fields of engineering, management science and other related disciplines.

This book offers a systematic overview of polymer joining and highlights the experimental and numerical work currently being pursued to devise possible strategies to overcome the technical issues. It also covers the fundamentals of polymers, the corresponding joining processes and related technologies. A chapter on the extrapolation of finite element analysis (FEA) for forecasting the deformation and temperature distribution during polymer joining is also included. Given its breadth of coverage, the book will be of great interest to researchers, engineers and practitioners whose work involves polymers.

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.

This book provides a systematic description about the development of Isogeometric Topology Optimization (ITO) method using the density, and then addresses the effectiveness and efficiency of the ITO method on several design problems, including multi-material structures, stress-minimization structures, piezoelectric structures and also with the uniform manufacturability, ultra-lightweight architected materials with extreme bulk/shear moduli, auxetic metamaterials and auxetic meta-composites with the NPRs behavior in microstructures. A detailed MATLAB implementation of the ITO method with an in-house code “IgaTop” is also presented.

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.

The development of miniature ion trap mass spectrometers has been an active area, fueled by the promising analytical capabilities and the convenience of fast in situ analysis. The objective is to miniaturize mass spectrometers in weight, size, and power consumption while retaining the analytical capabilities of mass spectrometry at the same time. The book focuses on the instrumentation of miniature ion trap mass spectrometers, including ionization, ion transfer, mass analyzer, ion detection and related vacuum and electronic techniques. Two miniature mass spectrometers, a 10 kg Mini 10 with electron impact ionization source, developed in 2005 and a 5 kg Mini 11 with multiple ionization sources, developed in 2008, are introduced. The technical details of key components are discussed. Special focus is given to a glow discharge electron impact ionization source, which is an ideal substitute for the filament electron source used in the electron impact ionization, and a discontinuous atmospheric pressure interface, which enables the implementation of atmospheric pressure ionization sources in miniature ion trap mas spectrometers with limited pumping capabilities.