|Book Name:||[PDF] Advanced Automation Techniques in Adaptive Material Processing|
Advanced Automation Techniques in Adaptive Material Processing by XiaoQi Chen
This volume presents the editors’ research as well as related recent findings on the applications of modern technologies in electrical and electronic engineering to the automation of some of the common manufacturing processes that have traditionally been handled within the mechanical and material engineering disciplines.
In particular, the book includes the latest research results achieved through applied research and development projects over the past few years at the Gintic Institute of Manufacturing Technology, Singapore. It discusses advanced automation technologies such as in-process sensors, laser vision systems, and laser strobe vision, as well as advanced techniques such as sensory signal processing, adaptive process control, fuzzy logic, neural networks, expert systems, laser processing control, etc. The methodologies and techniques are applied to some important material processing applications, including grinding, polishing, machining, and welding. Practical automation solutions, which are complicated by part distortions, tool wear, process dynamics, and variants, are explained.
The research efforts featured in the book are driven by industrial needs. They combine theoretical research with practical automation considerations. The techniques developed have been either implemented in the factory or prototyped in the laboratory.
- Overview of Material Processing Automation
- Process Development and Approach for 3D Profile Grinding/Polishing
- Adaptive Robotic System for 3D Profile Grinding/Polishing
- Acoustic Emission Sensing and Signal Processing for Machining Monitoring and Control
- Techniques of Automatic Weld Seam Tracking
- Weld Pool Geometry Sensing and Control in Arc Welding
- Automatic GTAW System Control and Teleoperation
- Laser Material Processing and Its Quality Monitoring and Control
Advanced automation techniques in adaptive material processing PDF
Author(s): Xiaoqi Chen, Rajagopalan Devanathan, Aik Meng Fong
Publisher: World Scientific, Year: 2002
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