Addresses important technical issues concerning welding robots, such as intelligent technologies and systems, analysis, and designFocuses on the development of intelligent modeling, controlling, monitoring, evaluating and optimizing manufacturing processes in connection with joining technologies

Presents the scientific outcomes of the 2018 International Conference on Robotic Welding, Intelligence and Automation

Autorentext
Dr. Shanben Chen (SB Chen) received his BS degree in industrial automation from Dalian Railway Institute (Dalian Jiao Tong University) in 1982, and received his MS and PhD in control theory and application from Harbin Institute of Technology, China, in 1987 and 1991, respectively. He worked as a postdoctoral fellow at the National Key Laboratory of Advanced Welding Production of China in Harbin Institute of Technology (HIT) from 1993 to 1995, and as a professor from 1995 to 2000.  From 2000 to present, he has served as the Special Professor, Cheung Kong Scholar Program of the Ministry of Education of China & Li Ka Shing Foundation, Hong Kong, and engaged at Shanghai Jiao Tong University, China, where he is also director of the Intelligentized Robotic Welding Technology Laboratory. Prof. Chen has also been a visiting professor at the University of Western Sydney (UWS) in connection with the ARC Linkage collaboration since 2009. 

Currently, Prof. Chen is a senior me

mber of the IEEE; a member of the American Welding Society; Chair of the Robotics & Automation Committee of the Chinese Welding Society (CWS); Deputy Secretary-General of the Chinese Welding Society; and a standing member of the Board of Directors, CWS.

Yuming Zhang - FAWS, FASME, FSME, SIEEE, Professor and James Boyd Professor in Electrical Engineering - has been with the University of Kentucky, Lexington, USA since 1991, and became a Full Professor in 2005. He received his BS and MS degrees in control theory and application from Harbin Institute of Technology (HIT), China, where he completed his PhD degree in welding in 1990. He has published 180 peer-reviewed journal papers and holds 8 US patents. 

Dr. Zhili Feng leads the Materials Joining Team, and is a Distinguished R&D Staff at Oak Ridge National Laboratory, where he manages 10 scientists and supporting staff, conducting both fundamental and applied R&D and pursuing technological innovations for diverse interdisciplinary subjects related to materials joining and materials manufacturing processes, with an annual R&D budget of $15 million. 

Klappentext
Transactions on Intelligent Welding Manufacturing (TIWM) mainly publishes selected high quality papers from the proceedings of the conference series International Workshop on Intelligentized Welding Manufacturing (IWIWM) and International Conference on Robotic Welding, Intelligence and Automation (RWIA), as well as freely contributed and peer-reviewed original research papers.

Zusammenfassung
The primary aim of this volume is to provide researchers and engineers from both academia and industry with up-to-date coverage of recent advances in the fields of robotic welding, intelligent systems and automation. It gathers selected papers from the 2018 International Conference on Robotic Welding, Intelligence and Automation (RWIA 2018), held Oct 20-22, 2018 in Guangzhou, China. The contributions reveal  how intelligentized welding manufacturing (IWM) is becoming an inescapable trend, just as intelligentized robotic welding is becoming a key technology. The volume is divided into four main parts: Intelligent Techniques for Robotic Welding, Sensing in Arc Welding Processing, Modeling and Intelligent Control of Welding Processing, and Intelligent Control and its Applications in Engineering.

Inhalt
Intelligentized technologies for robotic welding.- Advanced welding robot technologies.- Programming and simulation of welding robots.- Vision guiding and tracking technologies of welding robots.- Quality control of robotic welding.- Tele-control and network technologies for robotic welding.- Sensing technologies for welding process.- Robotic welding under special environment.- Intelligentized and digital welding equipments.- Intelligentized technologies for industrial process.