首页|New Robotics Data Have Been Reported by Researchers at University of Applied Sci ences (Fatigue Behaviour of Automatically Hfmi-treated Welds)

New Robotics Data Have Been Reported by Researchers at University of Applied Sci ences (Fatigue Behaviour of Automatically Hfmi-treated Welds)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Robotics is now availab le. According to news reporting originating from Munich, Germany, by NewsRx corr espondents, research stated, "Due to notches, welds are most critical regarding fatigue failure within cyclic loaded constructions. Therefore, various post-weld -treatment techniques like post-weld treatment by high-frequency mechanical impa ct (HFMI) treatment have been invented to improve the fatigue strength of welded details." Financial support for this research came from Central Innovation Programme for S MEs (ZIM) funded by the Federal Ministry of Economics and Climate Protection (BM WK) (Zentralen Innovationsprogramms Mittelstand (ZIM) Bundesministerium fr Wirts chaft und Klimaschutz (BMWK)). Our news editors obtained a quote from the research from the University of Appli ed Sciences, "The benefit, resulting from HFMI treatment, has already been prove n by numerous studies. Since a manual HFMI treatment must be performed by a skil led and trained person to ensure an acceptable treatment quality, an automated a pplication of HFMI treatment is supposed to result in a more reliable and consis tent treatment result, which does not depend on the operator. Furthermore, a rob otic application of HFMI treatment enables an economic implementation of HFMI tr eatment of automated welded constructions like offshore wind energy converters a nd various mechanical components, as these parts do not have to be taken out of the production chain to manually perform HFMI treatment."

MunichGermanyEuropeEmerging Techno logiesMachine LearningRoboticsRobotsUniversity of Applied Sciences

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Mar.8)