By Xiaoqi Chen, Rajagopalan Devanathan, Aik Meng Fong
This quantity offers the editors' study in addition to similar findings at the purposes of contemporary applied sciences in electric and digital engineering to the automation of a few of the typical production methods that experience generally been dealt with in the mechanical and fabric engineering disciplines. particularly, the textual content contains the newest learn effects completed via utilized learn and improvement initiatives over the last few years on the Gintic Institute of producing expertise, Singapore. It discusses complex automation applied sciences reminiscent of in-process sensors, laser imaginative and prescient structures, and laser strobe imaginative and prescient, in addition to complicated options equivalent to sensory sign processing, adaptive strategy regulate, fuzzy good judgment, neural networks, professional structures, laser processing keep an eye on, and so on. The methodologies and strategies are utilized to a few vital fabric processing functions, together with grinding, sprucing, machining, and welding. sensible automation recommendations, that are complex by way of half distortions, software put on, technique dynamics, and variations, are defined.
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Intuitive Tool Calibration (ITC). During machine re-calibration, setup or re-installation, position data of tool stations, measurement stations, and index table can be manually clocked. These data are keyed into the database. The mathematical model of workspace and robot kinematics is automatically generated. Optimal Profile Fitting (OPF). It generates the actual profile based on the in-situ measurement data. The robust fitting algorithm uses the sectional data as templates, and maps them with the measurement points.
However, processes that are poorly understood and those that demonstrate variable behaviour are particularly difficult to model, and alternative methods have to be used. In recent years, intelligent control techniques have been extensively studied. Many of these techniques derive from the rapidly expanding field of artificial intelligence, such as fuzzy logic, neural networks, genetic algorithms, case-based reasoning, term subsumption systems, intelligent agents, and so forth. These technologies empower manufacturing systems with sophisticated sensor integration, high level of machine intelligence, and extendable control capabilities and functionalities.
To start a cycle, the finishing robot picks up a workpiece from the feeding unit. It then performs in-situ measurement on selected points of the airfoil profile. The measurement data of the airfoil is sent to the host computer. By using those measurement data and the design airfoil profile, the template-based optimal profile fitting is performed. Based on the fitted profile, robotic grinding/polishing paths are computed and downloaded to the robot controller. After receiving the grinding/polishing paths, the finishing robot carries the workpiece and performs the specified grinding/polishing process on the grinding/polishing stations.