- Ph.D., Pennsylvania State University, 2007
- Quality Engineering
- Time Series Analysis
My research is in the general areas of applied statistics, quality engineering and condition monitoring. In particular I am interested in the following topics:
- Variation reduction in manufacturing processes
In this topic we study on-line robust process optimization methods for variation reduction in discrete-part manufacturing. We develop time series models to predict quality characteristics of dynamic systems and sequential design of experiments and feedback control approaches to determine cost-effective adjustment strategies.
- Uncertainty quantification of computer models
Computer models are very useful for modeling variety of engineering systems however careful consideration is required to quantify errors associated with modeling assumptions. In this research we utilize statistical approaches and experimental data to understand how much uncertainty or error is involved with computer model prediction for real world applications. Some of the computer models we study are finite element analysis for composite manufacturing and wind energy models for wind turbines.
- Sensor placement and damage identification for condition monitoring.
Condition monitoring is becoming popular for complex engineering systems and infrastructure for improved safety and cost effective maintenance. In this topic we develop statistical approaches for damage identification and localization and reliability models for remaining useful life prediction with various sensor systems. Sensing systems we use include ultrasonic guided-waves and piezoelectric sensors to measure crack growth and force sensors to predict pressure distribution.