CAREER: Transfer Learning Based Quality Improvement in Spatially-Temporally Complex Systems

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The research objective of this Faculty Early Career Development (CAREER) award is to develop "transfer learning" based methodologies for quality improvement of manufacturing systems featured by a high product variety and short life cycles (called spatially-temporally complex systems). Such systems typically exist in semiconductor and renewable-energy manufacturing industries. The methodological innovation - transfer learning - refers to the capability of leveraging the knowledge gained during quality control of one process (or past generations of a process) for quality control of other processes (or a new generation). A body of statistically rigorous and computationally efficient transfer learning based methods will be developed to achieve various quality control objectives such as process modeling, monitoring, root cause diagnosis, sensor uncertainty modeling, and sensor placement. Integrated with the research is an ambitious education plan aiming at equipping future workforce with new science and engineering knowledge and associated skills in quality improvement. If successful, the results of this research will significantly expedite the learning curve in quality improvement of each process in a manufacturing system through effective knowledge transfer from other processes and past generations. This will enable robust, real-time and even proactive quality control decision making to keep up with rapid product proliferation and generation changes. Through validation and application in semiconductor and solar energy manufacturing, this research will provide breakthrough technologies to significantly improve the quality, productivity, and cost-effectiveness of these industries. The research methodologies are also transferrable to the study of other systems such as health care delivery, human brain, and biological systems. A broad array of educational activities will be pursued, including new course development, industrial training sessions, undergraduate and minority students involvement, and K-12 students and teachers outreach. Research and education programs will be established through strong international collaboration to achieve global impact.