Attend the next School of Manufacturing Systems and Networks seminar exploring the use of artificial intelligence in industrial applications.
Industrial Artificial Intelligence for Maintenance and Service Innovations in Next Generation Industry Systems
Presented by Xiaodong Jia, University of Cincinnati
Driven by the rapid growth of sensor technology, the Internet of Things, or IoT, and machine or deep learning algorithms, the research field industrial artificial intelligence emphasizes the systematic integration of human experts, learning and decision-making analytics, and digital and automation technologies into industry systems for efficiency improvements and waste reduction, is emerging as a core technology that facilitates the smart and digital transformation in industry systems. According to Manufacturing x Digital (MxD), industrial AI in the manufacturing industry will maintain a 33.5% compound annual growth rate in the next seven years and the market size will grow from 1.4 billion in 2020 to 16.7 billion in 2028. Amongst all the smart manufacturing capabilities, enhanced sensing and monitoring and advances in analyzing data and trends hold the greatest economic impact according to the latest NIST economic analysis briefing.
This seminar will focus on industrial AI for maintenance and service innovations by demonstrating the representative works related to semiconductor manufacturing and high-precision optical lens manufacturing. In the first case study, a semi-automated toolkit for multivariate trace data analysis is developed and applied to the critical semiconductor manufacturing processes (e.g., semiconductor etching, chemical mechanical polishing, etc.) for yield enhancement. In the second study, a virtual lens assembly methodology is developed to recommend the optimal lens angles in final assembly and enhance the production yield. After demonstrating these ongoing research activities, this seminar will discuss future research initiatives for the upcoming five years and identify research opportunities related to the multi-modal sensing system in the medicare/pharmacy field, intelligent operation and maintenance of complex industry systems, and cyber-manufacturing.
About the speaker
Xiaodong Jia currently serves as a Research Assistant Professor in the Mechanical and Materials Engineering Department at the University of Cincinnati, leading multiple research projects sponsored by NIST, Applied Materials, Hitachi High-Tech, Taiwan Semiconductor Manufacturing Company, United Microelectronic Corporation, Winbond Electronics, Mitsubishi Electric, among others. He received his doctorate in mechanical engineering at the University of Cincinnati in 2018 and worked as a postdoc fellow for one year in 2019. Jia’s research focuses on developing advanced analytical solutions, including advanced sensing and monitoring and advanced data analytics, for maintenance and service innovations in next-generation industry systems (industry 4.0). His research works have been successfully implemented in a broad range of applications, including semiconductor manufacturing processes, high-precision optical lens manufacturing, traumatic brain injury prognosis, high precision linear motion equipment, wind turbines, among others. To date, Jia has published more than 45 peer-reviewed articles, led more than research projects sponsored by industry companies and government agencies, and maintained close collaborations with 30+ industry companies around the globe. Also, he is currently teaching two engineering courses at the University of Cincinnati, introduction to industrial AI and reliability engineering.