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
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.
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.
Keynote Speech 02——Song Zhang, Ph.D.
High-speed 3D Optical Sensing, Information Processing, and Applications
Song Zhang, Ph.D.
Professor and Assistant Head for Experiential Learning
School of Mechanical Engineering
West Lafayette, IN 47907, USA
Advances in optical imaging and machine/computer vision have provided integrated smart sensing systems for the manufacturing industry; and advanced 3D sensing could have profound impact on numerous fields, with broader applications including manufacturing, autonomous vehicles, and biomedical engineering. Our research addresses the challenges in high-speed, high-resolution 3D sensing and optical information processing. For example, we have developed a system that simultaneously captures, processes and displays 3D geometries at 30 Hz with over 300,000 measurement points per frame, which was unprecedented at that time (a decade ago). Our current research focuses on achieving speed breakthroughs by developing the binary defocusing techniques; and exploring novel means to store enormously large 3D data by innovating geometry/video compression methods. The binary defocusing methods coincide with the inherent operation mechanism of the digital-light-processing (DLP) technology, permitting tens of kHz 3D imaging speed at camera pixel spatial resolution. The novel methods of converting 3D data to regular 2D counterparts offer us the opportunity to leverage mature 2D data compression platform, achieving extremely high compression ratios without reinventing the whole data compression infrastructure. In this talk, I will present two platform technologies: 1) superfast 3D optical sensing; and 2) real-time 3D video communication. I will also cover some of the applications that we have been exploring including autonomous vehicles, biomedical engineering, forensic sciences, along with others.
Song Zhang is a Professor and the Assistant Head for Experiential Learning, School of Mechanical Engineering at Purdue University. He received his Ph.D. (2005) and M.S. (2003) degrees in Mechanical Engineering from Stony Brook University, and B.S. (2000) degree from University of Science and Technology of China. His primary research focuses on high-speed 3D optical sensing/imaging and optical information processing. He has over 200 publications including 130 journal articles and 2 books. 16 of his journal articles were selected as cover page highlights. His publications have been cited over 10,900 times with an h-index of 51. Besides being utilized in academia, technologies developed by his team have been used by Radiohead (a rock band) to create a music video House of Cards; and by the law enforcement personnel to document crime scenes. He has received awards including AIAA Best Paper Award, IEEE ROBIO Best Conference Paper Award, Best of SIGGRAPH Disney Emerging Technologies Award, NSF CAREER Award, Stony Brook University’s inaugural “Forty under 40 Alumni Award”, Discovery in Mechanical Engineering award, CoE Early Career Faculty Research Excellence Award from Purdue and Iowa State University, Purdue University Faculty Scholar. He was a technical editor for IEEE/ASME Transactions on Mechatronics. He currently serves as an associate editor for Optics Express, as well as Optics and Lasers in Engineering. He is a fellow of SPIE and OSA.
Keynote Speech 03——Fei Tao, Ph.D.
Digital Twin: State-of-the-art and Its Application
Fei Tao, Ph.D., Professor
School of Automation Science and Electrical Engineering
Beihang University, P.R.China
The global academic research of digital twin (DT) is first investigated, and a comparative analysis of digital twin research in USA, Germany, and China is then given out. Ten industry applications of digital twin are then introduced, especially the application of digital twin shop-floor. In order to better understand and use digital twin, some hot topics related to digital twin will be discussed, such as the concept of digital twin, the applicable guideline of digital twin, standards of digital twin, and so on.
Fei Tao is currently a Professor at the School of Automation Science and Electrical Engineering, Beihang University (BUAA), Beijing, China. His current research interests are digital twin driven product design/manufacturing and service, and smart manufacturing service. In these fields, he has authored 4 monographs as the first author and published over 50 papers in Nature, CIRP Annals and IEEE/ASME Transactions, of which 20 are ESI high cited papers, and his publication has over 15000 citations in Google Scholar. Prof. Tao is a Global Highly Cited Researcher in 2019. He is currently the Editor-in-Chief of the International Journal of Service and Computing-Oriented Manufacturing (IJSCOM), the Associate Editor of Robotic and Computer Integrated Manufacturing (RCIM). He is also a CIRP Associate Member and IEEE Senior Member. He is currently the Vice-Dean of the Research Institute of Science and Technology of BUAA.