首页|Study Results from McMaster University Broaden Understanding of Machine Learning (An Integrated Framework for a Multi-material Surface Roughness Prediction Mode l In Cnc Turning Using Theoretical and Machine Learning Methods)
Study Results from McMaster University Broaden Understanding of Machine Learning (An Integrated Framework for a Multi-material Surface Roughness Prediction Mode l In Cnc Turning Using Theoretical and Machine Learning Methods)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on Machine Learning is now available. According to news reportingoriginating in Hamilton, Canada, by News Rx journalists, research stated, “Indirect monitoring and predictionof surface roughness for computer numerical control (CNC) machining enables manufacturers t oensure quality outcomes are achieved, increase process productivity, and decre ase the risk of scrappedcomponents. Several approaches have been examined for s urface roughness prediction in CNC turning;however, few studies have explored t he development of models for multiple materials.”
HamiltonCanadaNorth and Central Amer icaCyborgsEmerging TechnologiesMachine LearningMcMaster University
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