CAREER: Collaborative Modeling for Distributed Sensing and Real-time Intelligent Control to Improve Battery Manufacturing Productivity and Efficiency

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This Faculty Early Career Development (CAREER) Program award is an integrated research and education study centered on collaborative sensing information processing, and an intelligent online control framework for battery manufacturing. It aims to integrate decision theory with real-time control, which will allow the full potential of distributed sensor networks to improve production system responsiveness, productivity and overall efficiency. The methodology includes the following tasks: 1) establish a virtual multi-layer sensing framework and event-based modeling to directly model distributed-sensor systems, 2) develop a collaborative information processing framework to effectively identify system transient loss and root causes of system inefficiency, and create a system learning method to optimize sensor network design, 3) establish an intelligent online control method to integrate decision theory with control for adaptive resource allocation and distributed management, and 4) validate these methods using simulation and real data through collaboration with industrial partners. If successful, this CAREER project will advance the state of the art on distributed sensor networks by contributing new concepts, criteria, and algorithms to its system level real-time decision making capabilities, and create an enabling methodology for next-generation plant-wide sensing, information processing and control. Accomplishing these goals will lead to dramatic cost reductions as a result of reduced downtime, improved quality and system efficiency, boosting the competitiveness of U.S. industries and the nation's economy. The CAREER education program will make a positive contribution to workforce training through curriculum and lab development, real-world problem solving and other outreach activities, with a focus on broadening participation of underrepresented groups. Dissemination through conference/journal publications and international/industrial collaborations will lead to exposure of these research results to a wide range distributed sensor networks that are of vital importance to the nation's economic growth.