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dc.contributor.authorGebraeel, Nagi Z.
dc.date.accessioned2017-04-17T16:21:53Z
dc.date.available2017-04-17T16:21:53Z
dc.date.issued2017-03-29
dc.identifier.urihttp://hdl.handle.net/1853/56644
dc.descriptionPresented on March 29, 2017 at 12:00 p.m. in the Georgia Tech Callaway Manufacturing Building, Auditorium.en_US
dc.descriptionNagi Gebraeel is a Georgia Power Associate Professor in the Stewart School of Industrial & Systems Engineering at Georgia Tech. Dr. Gebraeel's research interests lie at the intersection of sensor-based Predictive Analytics, Machine Learning, and Asset Management. His key focus is on developing next-generation machine learning tools specifically tailored for real-time equipment diagnostics and prognostics that enable subsequent operational and logistical decision-making.en_US
dc.descriptionRuntime: 52:21 minutesen_US
dc.description.abstractThe Stewart School of Industrial and Systems Engineering at Georgia Tech established the Center for Predictive Analytics and Real-Time Optimization. (PARO). The center focuses on two main thrust areas. The first thrust area focuses on developing Predictive Analytic tools capable of synthesizing and extracting information from multi-stream sensor signals to predict future performance of complex engineering systems. The second thrust area deals with the development of real-time enhanced optimization models that compute optimal decision by leveraging the information embedded in the data. The development of modern methodologies allow for efficient updating when information changes as well as automatic model calibration using techniques from machine learning, information theory, and statistics. Housed in the Supply Chain and Logistics Institute, the Center for Predictive Analytics and Real-Time Optimization brings together experts from various disciplines. Drs. Gebraeel, Kvam, Paynabar, Pokutta, Ramudhin and Shi provide expertise in Data Mining and Statistical Analysis, Optimization, Diagnostics and Prognostics, Supply Chain, and Reliability, with domain expertise in the following industrial sectors; Automotive, Energy, Logistics, Airlines, Steel, Nanomanufacturing, Wind Power, and others. We provide various types of industries with a vehicle for addressing their problems through a single point of contact using a problem-driven approach.en_US
dc.format.extent52:21 minutes
dc.language.isoen_USen_US
dc.subjectPredictive analyticsen_US
dc.subjectService logisticsen_US
dc.titlePredictive Analytics within the Service Supply Chainen_US
dc.typeLectureen_US
dc.typeVideoen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Supply Chain and Logistics Instituteen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Industrial and Systems Engineeringen_US


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