Lucas Beverlin, PhD
Title: Challenges in Statistics in the Semiconductor Industry
Abstract: Statisticians in the semiconductor industry face many challenges in order to assist engineers in creating sellable material. While the main goal is to create as much sellable material as possible, we at times look at large data sets and small data sets in order to increase yield. Increasing yield can be done in many ways, such as reducing the number of particles that are present on the material or implementing improvements that decrease down time for the tools that process material. While money is the biggest factor, we also must consider many other factors depending on the situation, such as physical constraints, detection limits, and sampling plans. This talk looks at these various challenges and the factors that play into them.
About Dr. Beverlin: Lucas Beverlin is a statistician at Intel, where he assists fab engineers with optimizing statistical process control and teaches statistics courses on basic statistics and design of experiments. He graduated from Louisiana State University with master's degrees in mathematics and applied statistics, and from Iowa State University with a Ph.D. in statistics. His research interests include nonlinear modeling, reliability, and machine learning.