Title:
Predictive Analytics within the Service Supply Chain
Predictive Analytics within the Service Supply Chain
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Author(s)
Gebraeel, Nagi
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Abstract
The 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.
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Date Issued
2017-03-29
Extent
52:21 minutes
Resource Type
Moving Image
Resource Subtype
Lecture