Alexander Klinger
Papers
4
Total Citations
35
H-Index
3
About
Alexander Klinger is a leading researcher in Prognostics and Health Management (PHM) for industrial robotics and manufacturing systems. His work focuses on developing measurement science to enhance the monitoring, diagnostics, and prognostics of automated workcells—critical for smarter factory-floor decision-making. Klinger’s most impactful contribution is a hierarchical decomposition methodology that increases manufacturing process and equipment health awareness (24 citations), providing a systematic framework for identifying degradation sources in complex robotic systems. He also led the development of a robotic work cell test bed at the National Institute of Standards and Technology (NIST), which serves as a foundational platform for advancing PHM technologies and benchmarking their effectiveness. By examining kinematic chains to pinpoint positioning degradation, Klinger has directly addressed the growing complexity of industrial automation. His research is instrumental in reducing troubleshooting time and improving system reliability, making him a key figure in bridging the gap between advanced sensing technologies and practical manufacturing applications.
Research Focus
Key Achievements
Top Papers
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