Center for Intelligent Maintenance Systems Proposal #1127924 Proposal #1127922
This proposal seeks funding for the Center for Center for Intelligent Maintenance Systems sites at the University of Cincinnati and the Missouri Institute of Science and Technology. Funding Requests for Fundamental Research are authorized by an NSF approved solicitation, NSF 10-601. The solicitation invites I/UCRCs to submit proposals for support of industry-defined fundamental research.
Prognosis of industrial systems and the management of their health based on system data typically requires significant analysis and design prior to implementation of an effective detection and management system. The proposed work seeks to accelerate the process of collection and assessment of data in order to reduce the life cycle of Prognosis and Health Management (PHM) research. The work plans to explore a framework with unified systematic methods to ensure the precision of Remaining Useful Life (RUL) estimations that are essential for effective health management.
The proposed work promises to significantly improve methods to estimate the usable lifetime of industrial equipment, thus enabling efficient maintenance of operating production systems and reducing overall cost. The work is supported by the Industry Advisory Board as well as individual industry members of the center and has the potential to extend the center?s portfolio by virtue of the framework to be established by the work. The center will involve graduate students, teachers and undergraduates in the work emphasizing involvement of minority and female students.
The major goals of this project are to investigate, develop and validate an advanced framework and methodology for conducting Accelerated Life Testing. The ultimate goal of this Accelerated Life Testing effort is to significantly reduce the time, effort and financial investment needed to understand, model and produce the operating data that is often required to develop an effective prognostics and health management (PHM) system for an asset or product. This ALT framework can also be utilized for new products or assets for which no historical data exists, which could result in the availability of a prognostics system at the beginning of an asset's life-cycle, further preventing failures before they can occur and broadening the applicability of PHM solutions. Most notably, this work has resulted in a novel, and more accurate, approach to determining the health, capacity and state of charge of lithium-ion batteries for Electric Vehicle applications. The research conducted in this area will continue beyond this project, culminating the development of an integrated system for delivering a more information-rich experience for EV operators, which will include improved range estimation, state of charge, state of health and route optimization. In addition, the work conducted under this project on Accelerated Life Testing for industrial manufacturing applications is relevant beyond the application addressed within this project. Is the Center's goal to expand the tools and methods developed to additional industrial applications and fields in which life-cylce data is difficult to acquire, such as wind turbines and industrial valves.
