In a teleservice system, the data collected from multiple in-field units are sent through a communication network to a back office for processing and decision making. These teleservice systems consist of three major components: (i) in-service units, (ii) communication infrastructure (iii) back-office data processing center. The goal of this project is to establish failure prognosis and service decision-making solutions that are tailored to address both the significant opportunities and the challenging needs of emerging sensor enabled teleservice systems. The solutions will allow to leverage the rich data available through sensor technology and communication infrastructure, and facilitate the transformation from a data-rich into a decision-smart environment. In particular, the research team will establish a series of predictive analytics methodologies to predict the remaining useful life of system components where the predictive results will be inputted to a decision making framework to provide optimal predictive control and maintenance decision making. The overarching goal is to enhance operation safety and reduce operational costs.
Raed Al Kontar and Eunshin Byon receive M-Cubed funding

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Industrial and Operations Engineering
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Assistant Professor
Associate Professor