ASQ RRD Series: An Introduction to Uncertainty Quantification for Reliability & Risk Assessments
Thu, Jan 10, 2019 12:00 PM – 1:00 PM EST
by Mark Andrews, Ph.D.
Numerical simulations have become the choice approach for performing analytics in many industrial sectors. With the phenomenal growth in computational power and significant advancements made in Computer-Aided Engineering (CAE) software, computer experiments of complex systems are now capable of reducing the dependency and costs of conducting physical experiments. While the prevalence of simulation tools offers unique potential to generate expedient analytics, simulation modeling of complex systems requires Uncertainty Quantification, an advanced analytical methodology capable of generating actionable results.
Uncertainty Quantification is a multi-disciplinary field that brings together statistics, applied mathematics, and computer science to quantify uncertainties in numerical simulations. Like Six Sigma, Uncertainty Quantification makes use of statistical models to find feasible solutions to problems involving variability. However, the two methodologies seek to meet different objectives.
This webinar will begin by introducing the topic of Uncertainty Quantification along with the basic methods and processes used to quantify uncertainties. Illustrative examples will be used to highlight how UQ can enhance Six Sigma.
Mark Andrews, Ph.D.
Dr. Mark Andrews, UQ Technology Steward, is responsible for advising SmartUQ on the industry’s UQ needs and challenges and is the principal investigator for SmartUQ’s project with Probabilistic Analysis Consortium for Engines (PACE) developed and managed by Ohio Aerospace Institute (OAI). He recently received the award for best training at 2018 the Conference on Advancing Analysis & Simulation in Engineering (CAASE). Before SmartUQ, Dr. Andrews spent 15 years at Caterpillar where he worked as Senior Research Engineer, Engineering Specialist in Corporate Reliability, and Senior Engineering Specialist in Virtual Product Development. He has a Ph.D. in Mechanical Engineering from the New Mexico State University.