Big Data Analytics for Intelligent Sensing and Measurement

Robert X. Gao, Ph.D.

Cady Staley Professor and Chair

Department of Mechanical and Aerospace Engineering

Case Western Reserve University

Abstract

Continued advancement in sensing and measurement technologies has led to an ever-increasing amount of data of a broad variety of forms and physical natures to be acquired from virtually all aspects of industrial and commercial fields. As rich information are embedded within these “big data”, how to efficiently leverage them by means of effective data analytic methods to enhance manufacturing and contribute to economic development has become both a challenge and an opportunity.

This talk presents essential elements of and promising solutions enabled by big data analytics that complement measurement systems in the interpretation of high volume, broad variety, and low veracity data through enhanced pattern recognition and information extraction, with applications in machinery fault diagnosis, service life prognosis, and product quality control, to ultimately contribute to value creation. Case studies of machine learning methods such as deep learning in analyzing time series and image data and revealing mechanisms underlying manufacturing processes are discussed. Using assembly in manufacturing as a scenario, the talk highlights how multiphysics sensing and data analytics can be integrated for the recognition of current and prediction of future human actions during assembly operations to realize human-robot collaboration (HRC) in smart factories of the future.

Biographical Sketch

Dr. Gao is the Cady Staley Professor of Engineering and Department Chair of Mechanical and Aerospace Engineering at Case Western Reserve University in Cleveland, Ohio.  Since receiving his Ph.D. degree from the Technical University of Berlin, Germany in 1991, he has been working on multi-physics sensing, design and modeling of instrument systems, and machine learning techniques for improving the observability of dynamical systems such as manufacturing equipment and processes.  Dr. Gao is a Fellow of the Institute of Electrical and Electronic Engineers (IEEE), American Society of Mechanical Engineers (ASME), International Academy for Production Engineering (CIRP), and Society of Manufacturing Engineers (SME). He currently serves as a Senior Editor for the IEEE/ASME Transactions on Mechatronics, and is a recipient of the IEEE Best Application in Instrumentation and Measurement Award, IEEE Instrumentation and Measurement Society Technical Award, ASME Blackall Machine Tool and Gage Award, SME Eli Whitney Productivity Award, an NSF Early CAREER Award.