Areas of Focus
Advances in smart sensors have created a unique opportunity to monitor and coordinate the performance of physical engineering systems with broader enterprise operations, such as manufacturing operations, service logistics, maintenance management, after-sales services, etc. This transformation demands methodologies and solutions capable of analyzing and modeling in-situ multi-stream sensor signals to support and facilitate optimal decision making strategies. Combined with state-of-the-art real-time optimization techniques nearly instantaneous decision can be computed in fast changing business environments unlocking significant cost-savings.
In response to these industrial challenges, the Stewart School of Industrial and Systems Engineering 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.
Below are some of the key research areas: