首页|Lorraine University Researcher Publishes New Study Findings on Machine Learning (Towards Optimizing Multi-Level Selective Maintenance via Machine Learning Predictive Models)
Lorraine University Researcher Publishes New Study Findings on Machine Learning (Towards Optimizing Multi-Level Selective Maintenance via Machine Learning Predictive Models)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on artificial intelligence. According to news reportingfrom Metz, France, by NewsRx journalists, research stated, “The maintenance strategies commonly employedin industrial settings primarily rely on theoretical models that often overlook the actual operatingconditions.”The news correspondents obtained a quote from the research from Lorraine University: “To addressthis limitation, the present paper introduces a novel selective predictive maintenance approach based on amachine learning model for a multi-parallel series system, which involves executing multiple missions withbreaks between them. For this purpose, the proposed selective maintenance approach consists of finding,at each breakdown, the optimal structure of maintenance activities that provide the desired reliability levelof the system for each mission. This decision is based on a component’s actual age, as determined by theprediction model.”
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