The Industry/University Cooperative Research Center (I/UCRC) program is aimed at developing long-term partnerships among industry, academe, and government. These centers are catalyzed by a small investment from the National Science Foundation (NSF) and are primarily supported by center members, with NSF taking a supporting role in their development and evolution. I/UCRCs stimulate highly leveraged industry/university cooperation by focusing on fundamental research recommended by Industrial Advisory Boards (IAB). Each center is established to conduct research that is of interest to both the industry and the university with which it is involved, with the provision that the industry must provide major support to the center at all times. The centers rely primarily on the involvement of graduate students and some full time researchers in their research projects, thus developing students and scientists who are knowledgeable in industrially relevant research. With industrial and other support totaling 10 to 15 times the NSF investment, I/UCRCs are a premier example of "leveraged" funding model. Over the past two decades, the I/UCRCs have led the way to a new era of partnership between universities and industry, featuring high-quality, industrially relevant research, strong industrial support of and collaboration in research and education, and direct transfer of university developed ideas, research results, and technology to U.S. industry to improve its posture in competitive world markets.
Due to rapid advances in sensors, micro-electromechanical systems (MEMS), and with stringent performance requirements and environmental regulations, modern day industrial systems are becoming more and more complex. Intelligent sensor-based decision making agents with wireless communication technologies, when deployed in these complex systems as monitoring/diagnostic/prognostic (M/D/P) tools, will result in better system performance, minimal unscheduled downtime, and reduced maintenance and operating costs. The estimated downtime costs per year for various industries are: Financial $9.4B, Energy $5.7B, Telecommunications $4.2B, Manufacturing $3.3B, and Retail $2.1B. We recently established a Missouri University of Science and Technology (Missouri S&T) site of the NSF I/UCRC on Intelligent Maintenance Systems (IMS) to address the issues of such industrial systems.
Complex industrial systems are truly nonlinear, contain deterministic and stochastic terms, and have spatial and temporal characteristics. They may comprise of numerous components but their sum effect is not just an aggregation of individual outputs. They may have component or system failures. At present it is very difficult to diagnose or predict component failures in such systems and the proposed center intends to fill this void. The mission of the proposed center is to provide an opportunity for cooperative research between Missouri S&T researchers and industrial partners to develop appropriate technologies in order to bridge this gap in the areas of M/D/P with industrial applications.
Missouri S&T’s research expertise includes component health monitoring, diagnostics and prognostics of industrial systems, sensor development, decision making and control, and advanced simulation relevant to M/D/P. Significant funding has been awarded and patents have been granted to Missouri S&T faculty on this topic. Missouri S&T has teamed up with University of Cincinnati (UC) and University of Michigan (UM) to accelerate the pace of becoming a national leader in M/D/P research. Missouri S&T IMS Center intends to build a quality research program in M/D/P and associated educational activities supported by a well-defined plan for technology transfer to industries.
A critical piece in the economic success of any industry that involves the operation of such complex systems is to minimize the downtime. The availability of such complex systems requires novel sensors, decision making capability, and computer control with suitable communication schemes for various subsystems. A major goal of this Center is to find effective ways to investigate relevant M/D/P tools and technologies for solving important industrial problems by bringing together faculty with expertise in M/D/P and domain-specific knowledge.