Received his B.S. in Mechanical Engineering in 2007 from the University of Illinois at Urbana‐Champaign. While an undergrad at Illinois, he workedas a Transportation Management Co‐op for Norfolk Southern in Decatur, Illinois.
After completion of his Bachelor's degree, Bryan began his M.S. study in Civil and Environmental Engineering in the Railroad Engineering Program at Illinois. In the first year of his research, he was part of a multidisciplinary team studying the feasibility of using machine vision technology to automatically inspect freight car underbodies. After completion of that project, Bryan moved on to a more comprehensive study of automated condition monitoring technologies to understand the safety and economic impacts of improved rolling stock inspection and maintenance. As a graduate student, he also helped found the AREMA Student Chapter at the University of Illinois and served as the first chapter President. Bryan has accepted a position with Norfolk Southern and will begin work with their Mechanical Department in Roanoke, Virginia in January of 2011.
The effectiveness and efficiency of railcar inspection directly impacts rail network operations. Current railcar inspection practices are intended to identify defects prior to failure, but they often do not provide predictive maintenance capabilities due to the limitations of manual, visual inspection. As a result, automated wayside condition monitoring technologies have been developed to monitor rolling stock condition and facilitate predictive maintenance strategies. By improving the effectiveness of railcar condition monitoring, these technologies have the potential to reduce equipment-caused in-service failures, eliminating system waste and reducing variability in mainline operations. In addition, automated railcar condition monitoring can improve railroad terminal efficiency as a result of reduced inspection times and improved rail terminal operations.
This research applies Lean Manufacturing methods to the railcar maintenance process, quantifying both direct and indirect waste. To assess benefits to mainline efficiency, dispatch simulation software was used, quantifying the length and variability of equipment-caused mainline delays as a function of traffic level. To assess benefits to terminal efficiency, the railroad terminal was compared to a manufacturing production system and lean production techniques were used to identify sources of waste and variability in the car inspection process. Through application of these methods, we provide a basis for developing cost-effective strategies for technology integration and improved railcar maintenance.