New ME course focuses on engineering design and failure prognostics

A graph that demonstrates engineering design under uncertainty, one of two major foci of the course
A graph that demonstrates “Deterministic vs. Probabilistic Design”

A new graduate-level course offered by the mechanical engineering department for spring 2018 will focus on reliability as well as uncertainty in engineering system design and post-design failure prognostics.

The 1986 Chernobyl disaster in Russia, the 2007 collapse of the I-35W bridge in Minnesota, and the 2016 spurt of exploding batteries in the Samsung Galaxy Note 7 smartphone are just a few instances that called into question the reliability of engineered systems. This course aims to address the issues that led to these failures.

ME assistant professor Chao Hu
Hu

The course – ME 591X: Probabilistic Engineering Analysis and Design – will be taught by ME assistant professor Chao Hu and will cover the tools and techniques for two main areas: (1) engineering design under uncertainty and (2) post-design failure prognostics and how to use these tools and techniques to increase system/product safety, availability, and reliability.

“This course will cover state-of-the-art probabilistic and statistical methods for reliability analysis and design of engineered systems and post-design failure prediction and prevention of the systems,” said Hu. “It will be focused on practical applications of probabilistic analysis and design to enable development of reliable system functions and proactive prognostics and prevention of system failures.”

The course offers “hands-on learning of various probabilistic and statistical design methods, such as Design of Experiments, surrogate modeling, uncertainty quantification, reliability-based design, and robust design” and also “covers Bayesian estimation and machine learning methods for post-design failure prognostics,” according to the syllabus. Hu said this kind of course is important since the current course catalog does not adequately cover issues of reliability and uncertainty in design and post-design prognostics.

“This course will introduce this knowledge to students so that they can directly apply it to their own research studies where uncertainty and/or reliability may play an important role. Students will gain a hands-on experience on the applications of probabilistic and statistical methods to analyze and improve the reliability of engineered systems,” Hu said.

The course is mainly geared toward graduate students from various engineering disciplines, but is open to all students.

For more information about this course, check out the syllabus or contact Dr. Hu at chaohu[at]iastate.edu or 515-294-0771

Graph that shows Health Sensing Function, Health Reasoning Function, Health Prognostics Function, and Health Management Function
A graph that demonstrates “prognostics and health management,” one of two major foci of the course.