Hometown: Odesa, Odesskaya, Ukraine
Graduation date: Spring 2025
Additional details: Honors student
FURI | Fall 2023
Deep Gaussian Process and Reinforcement Learning Approach to Adaptive Maintenance Scheduling in Semiconductor Manufacturing
This study’s objective is to examine the viability of an adaptive maintenance system in semiconductor manufacturing using Deep Gaussian Processes (DGPs) and Reinforcement Learning (RL). This innovative approach could revolutionize maintenance procedures, offering proactive solutions that increase equipment reliability and reduce operational downtimes, providing substantial benefits to the semiconductor industry. The research may also open doors to broader manufacturing optimizations, leveraging machine learning synergies. Future endeavors should further validate the system’s applicability across diverse manufacturing environments and refine real-time adaptation mechanisms.
Mentor: Andi Wang
Sponsored project | Fall 2023
Mykhaylo Mykhaylov’s FURI project is sponsored by TSMC.
TSMC is a global leader in the semiconductor foundry business. The company’s industry-leading process technologies and portfolio of design enablement solutions help its customers and partners unleash semiconductor innovation. With its recent expansion into Phoenix, TSMC sees the benefit of a strong partnership with ASU faculty and student researchers. TSMC supports the FURI program by providing additional funding for exceptional research projects related to the semiconductor industry. FURI student researchers who pursue a project related to the Semiconductor Manufacturing research theme are eligible for this sponsorship. TSMC-supported FURI students receive a $2,600 stipend and $400 to use for materials. Exceptional research proposals that align with the research theme of Semiconductor Manufacturing will be considered for this additional funding.