首页|Reports Outline Machine Learning Findings from University of Carlos III Madrid ( Spot-checking Machine Learning Algorithms for Tool Wear Monitoring In Automatic Drilling Operations In Cfrp/ti6al4v/al Stacks In the Aircraft Industry)
Reports Outline Machine Learning Findings from University of Carlos III Madrid ( Spot-checking Machine Learning Algorithms for Tool Wear Monitoring In Automatic Drilling Operations In Cfrp/ti6al4v/al Stacks In the Aircraft Industry)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Data detailed on Machine Learning have been prese nted. According to news originating fromMadrid, Spain, by NewsRx correspondents , research stated, “In aircraft manufacturing, where diversematerials, includin g Carbon Fiber-Reinforced Plastics (CFRP), aluminum, and titanium alloys, are employed, the assembly process heavily relies on creating thousands of holes. Thes e holes accommodatebolts and rivets, facilitating the secure interlocking of st ructural components within the aircraft fuselage.”Financial supporters for this research include Airbus France S.A.S., State Inves tigation Agency,MCIN/AEI, European Union “NextGenerationEU”/PRTR.”
MadridSpainEuropeAlgorithmsCybor gsEmerging TechnologiesMachine LearningUniversity of Carlos III Madrid
NETL
NSTL
