Advanced Automation Techniques in Adaptive Material Processing

Advanced Automation Techniques in Adaptive Material Processing

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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. Contents:Overview of Material Processing AutomationProcess Development and Approach for 3D Profile Grinding/PolishingAdaptive Robotic System for 3D Profile Grinding/PolishingAcoustic Emission Sensing and Signal Processing for Machining Monitoring and ControlTechniques of Automatic Weld Seam TrackingWeld Pool Geometry Sensing and Control in Arc WeldingAutomatic GTAW System Control and TeleoperationLaser Material Processing and Its Quality Monitoring and Control Readership: Graduate students, academics and researchers in robotics a automated systems as well as electrical a electronic, mechanical and materials engineering. Keywords:The automated system shortens the cycle time from 10 minutes (manual polishing) to an average of 5.75 minutes, resulting in an improvement of 42.5%. 7 . Results Before ... It has been benchmarked for the first stage vane of JT9D-7Q engine.

Title:Advanced Automation Techniques in Adaptive Material Processing
Author: Xiaoqi Chen, Aik Meng Fong, Rajagopalan Devanathan
Publisher:World Scientific - 2002-09-06

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