UMD Workshop: Introduction to the Reliability Modeling Toolkit for Reliability and Accelerated Testing Analysis

The University of Maryland’s Center for Risk and Reliability (CRR) is offering a workshop and training session during the RAMS symposium. The workshop titled “Introduction to the Reliability Modeling Toolkit for Reliability and Accelerated Testing Analysis” will be offered free on Sunday, January 18th, 2026, from 1:30 pm to 5:30 pm.  Bring your laptop to obtain the most benefit from the workshop.

Note:  The workshop is offered free of charge to the first 75 to sign up and complete their registration. Please follow this link to register or update your existing registration.

Overview:

The Reliability Modeling Toolkit (RMT) is a free R-based library designed to execute several computationally involved and challenging reliability modeling calculations based on probabilistic physics of failure (PoF) and accelerated testing.  In this workshop, brief overviews of certain reliability concepts will be presented, including some widely used PoF models, regression modeling of PoF models, probability plotting, maximum likelihood estimation (MLE), Bayesian estimation and analysis, evaluation of accelerated life testing and accelerated degradation testing data.  The course will then apply each of these concepts to specific tools within the RMT and instruction on how to use them will be given through live demonstration on example problems and case studies.  The workshop will be hands-on, with the participants bringing their laptops to the workshop, engaging with each other and the instructor to use the RMT, and solving several examples.  Basic knowledge of probability and statistics, mathematics, reliability analysis, and simple programming is recommended.  Knowledge of the R platform is useful but not required.

Tentative Timeline:

Instructor’s BIO:

Dr. Reuel Smith is a faculty specialist and lecturer at the Center for Risk and Reliability and the Systems, Risk and faculty at the A.J. Clark School of Engineering at the University of Maryland, College Park.  His research areas of study include reliability modeling, data analysis, crack propagation and detection modeling, and the development of learning tools for reliability engineering courses.  He received his Ph.D. in reliability engineering in 2017, an M.S. in mechanical engineering in 2011, another M.S. in aerospace engineering in 2007, and a Bachelor’s degree with Honors in aerospace engineering in 2005; all from the University of Maryland, College Park.  He is the lead developer of the University of Maryland’s R-based reliability modeling library, the Reliability Modeling Toolkit.