Shao, Koric partner for game-changing big data manufacturing research
Assistant Professor Chenhui Shao is working in collaboration with MechSE Research Associate Professor and Technical Assistant Director at NCSA, Seid Koric, on a project that uses big data and high-performance computing to advance smart manufacturing. This work has significant potential to transform the manufacturing industry.
Shao’s project “Big Data Enabled Multi-Level Decision Making for Smart Manufacturing” aims to establish theoretical foundations and a new paradigm for multi-level decision-making by leveraging big data and HPC. He will be working as a Scholar-in-Residence at NCSA for the one-year project.
“Working with Dr. Koric’s team at NCSA, we will design big data based solutions for manufacturers, including NCSA’s industrial partners, and equip them with toolkits for smart sensing, monitoring, control, diagnosis, prognostics, etc.,” Shao said.
Big data can be used to transform the way the manufacturing industry incorporates smart decision-making across multiple levels, including processing, machine, station, factory, enterprise, and supply chain.
Koric and Shao hope to implement online intelligent 3D sensing based on HPC along with a new sampling algorithm Shao developed. In their recent work together, utilizing parallel computing, efficient data structures, and code optimization, they have improved the computing efficiency by more than 10 times and reduced the computing time to just several hours.
“The rapid development of sensing, communication, computing, and information technologies and infrastructure promotes the arrival of the big data era for manufacturing,” Shao said. “High-performance computing plays a key role in enabling real-time big data analytics and transforming the manufacturing industry with intelligence, responsiveness, and digitalization.”
However, the development of smart manufacturing is still in its beginning stages, and Shao has experience working with industry partners in manufacturing and is one of the few faculty working at the intersection of manufacturing, big data, and machine learning.
“Data-intensive analytics are expanding rapidly in both industry and academia, driven by powerful new scientific instruments, sensor networks, and more muscular HPC systems,” Koric said. “Extracting knowledge from these big data sets and providing predictive value to NCSA’s customers and users represent a challenge. Professor Shao represents one of the very few faculty members at Illinois who is working in this highly promising research area, and we are looking forward to collaborating by leveraging big data and HPC capabilities and expertise at NCSA.”
Additional NCSA collaborators include Dora Cai and Qiyue Lu. The project is expected to last until the summer of 2018, with the hope that a successful completion will lead to change in industry and new funding for further research.