首页|Reports from Indian Institute of Information Technology Add New Study Findings t o Research in Machine Learning (Machining Process Automation in Computer Numeric al Control Turning Using Robot-Assisted Imaging and CNN-Based Machine Learning)
Reports from Indian Institute of Information Technology Add New Study Findings t o Research in Machine Learning (Machining Process Automation in Computer Numeric al Control Turning Using Robot-Assisted Imaging and CNN-Based Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on artificial intelligence are presented in a new report. According to news reporting from Chennai, India, by NewsRx journalists, research stated, "With the emergence of the Industrial In ternet of Things and Industry 4.0, industrial automation has grown as an importa nt vertical in recent years. Smart manufacturing techniques are now becoming ess ential to keep up with the global industrial competition." The news reporters obtained a quote from the research from Indian Institute of I nformation Technology: "Decreasing machine's downtime and increasing tool life a re crucial factors in reducing machining process costs. Therefore, introducing c omplete process automation utilizing an intelligent automation system can enhanc e the throughput of manufacturing processes. To achieve this, intelligent manufa cturing systems can be designed to recognize materials they interact with and au tonomously decide what actions to take whenever needed. This paper aims to prese nt a generalized approach for fully automated machining processes to develop an intelligent manufacturing system. As an objective to accomplish this, the presen ce of workpiece material is automatically detected and identified in the propose d system using a convolutional neural network (CNN) based machine learning (ML) algorithm. Furthermore, the computer numerical control (CNC) lathe's machining t oolpath is automatically generated based on workpiece images for a surface finis hing operation. Machining process parameters (spindle speed and feed rate) are a lso autonomously controlled, thus enabling full machining process automation. Th e implemented system introduces cognitive abilities into a machining system, cre ating an intelligent manufacturing ecosystem."
Indian Institute of Information Technolo gyChennaiIndiaAsiaComputersCyborgsEmerging TechnologiesMachine Lea rningRobotRobotics
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