Eunshin Byon

Associate Professor

Location

2773 IOE

Additional Title(s)

IOE Diversity Ally

Primary Website

http://ebyon.engin.umich.edu/

Research Interests

• Analytics
  Predictive Data Analytics
• Applications
  Energy
  Manufacturing
• Risk Management
  Reliability
• Industrial Operations
  Operations & Maintenance Optimization
  Sustainability
• Operations Research Tools
  Simulation
  Stochastic Opt. & Control
• Quality & Applied Statistics
  Bayesian Statistics
  Design of Experiments
  Fault Diagnosis & Condition Monitoring
  Reliability & Maintainability
  Statistical Quality Control

Biography

Dr. Byon’s research interests include reliability evaluation, fault diagnosis/condition monitoring, predictive modeling and data analytics, and operations and maintenance decision-making for stochastic systems. Her recent research focuses on uncertainty quantification of stochastic systems using stochastic simulations, reliability analysis and improvement of large-scale, interconnected systems with applications to renewable power power systems and manufacturing processes. She is a member of IIE, INFORMS, and IEEE.

Publications

• Byon, E., Choe, Y., Yampikulsakul N., Adaptive modeling and prediction in time-variant processes with application to wind power systems, to appear in IEEE Transactions on Automations Science and Engineering.
• Choe, Y., Byon, E., and Chen, N., 2015, Importance sampling for the reliability evaluation with stochastic simulation models, Technometrics, Vol. 57, No. 3, pp. 351-361.
• Ko. Y and Byon, E., Reliability analysis of large-scale systems with identical units, 2015, IEEE Transactions on Reliability, Vol. 64, No. 1, pp. 420-434.
• Yampikulsakul N., Byon, E., Huang S., Sheng S. and You M.*, 2014, Condition monitoring of wind turbine system with nonparametric regression-based analysis, IEEE Transactions on Energy Conversion, Vol. 29, No. 2, pp. 288-299.
• Byon, E., 2013, Wind turbine operations and maintenance: A tractable approximation of dynamic decision-making, IIE Transactions, Vol. 45, No. 11, pp. 1188-1201
• Lee, G., Byon, E., Ntaimo, L., and Ding. Y, 2013, Bayesian spline method for assessing extreme loads on wind turbines, Annals of Applied Statistics, Vol. 7, No. 4, pp. 2034–2061
• Byon, E., Shrivastava, A. K., and Ding, Y., 2010, A classification procedure for highly imbalanced class sizes, IIE Transactions, Vol. 42, No. 4, pp. 288-303
• Byon, E., Ding, Y. and Ntaimo, L., 2010, Optimal maintenance strategies of wind turbine systems under stochastic weather conditions, IEEE Transactions on Reliability, Vol. 59, No. 2, pp. 393-404.