会议名称：2019年IEEE预测与健康管理会议（PHM2019）
报告时间：2019年7月1日（星期一）下午15:00-18:00
报告地点：铁道学院电子楼302会议室
报告人1：陆运佑
报告题目：Fault Detection, Diagnosis, & Prognosis towards Autonomous Health Management and Maintenance Optimization for Rail Vehicle Systems
报告摘要:Prognostics andHealth Management (PHM)play an increasinglyimportantrole in transportation system. The presentationintroducesthe development of equipment health management technology, PHM technology system, design and development processof PHMandsomerepresentativeapplicationcasesin rail transit system.
报告人2：汤晅恒
报告题目：Industrial AI for Maintenance and Repair: Recent Advances and New Applications
报告摘要：Industrial AI for maintenance and repair helps increase asset availability, increase asset utilization, improve product quality, increase safety and reliability of operations, reduce operations and maintenance cost and enhance operational control and planning. The maintenance and repair problems include following three parts: descriptive analytics, predictive analytics and prescriptive analytics. The descriptive analytics give insights of the present, then the predictive analytics provide a view of the future, and finally the prescriptive analytics decide the recommendation of best action.
报告人3：杨佳俊
报告题目：Whatcomes after prognostics
报告摘要：Post-prognostic decision making realizes the true benefit of PHM. Decision-Making can be framed as a Multi-Objective Dynamic Problem. Insight necessary to make right operational decisions. Complexity of information that needs to be processed exceeds cognitive, information processing capacity of human decision-makers. Optimization crucial to success of effective PHM DSS. It’s important to allow PHM user to collaborate in decision-making process
