Statistical Methods for Additive Manufacturing

Catalog description

This course explores the theoretical and practical underpinnings of statistical methods and tools for additive manufacturing (AM). It is primarily directed to engineering students working in fields outside of statistics and data science to design and develop statistical methods and tools for data analytics in AM. The primary areas of focus are statistical methodologies such as statistical process control, statistical design and analysis of experiments, predictive analytics, and reliability modeling. In addition to understanding statistical methodologies, students will apply the course teachings to design and implement the appropriate methodologies to model and analyze AM processes. Through this analysis, students will develop the skills for data-driven manufacturing informatics and decision making. Recommended preparation for the course includes basic concepts on probability and statistics, and the use of computing software (e.g., Matlab or Python).