Understanding structural behavior from telemetry data isn’t always straightforward, especially when using tools not built for multivariate analysis. Spreadsheets are great for tabular data entry but lack the structure, modeling, visualization, and auditability for standards such as APQP/AS9100/AS9145.
Whether it’s the tool or the approach, many engineers face challenges in identifying relationships that drive anomalies. From changes in operating conditions to interactions between variables to shifts in structural response, anomalies can remain hidden until they are exposed visually.
In this 30-minute session, we take the guesswork out of this process. Using an aerospace case study, we explore how different visualization and analysis approaches reveal patterns that are often missed. We then present a clear, structured workflow for investigating structural behavior in complex systems.
About the presenter
Kemal Oflus, Principal Systems Engineer
Kemal Oflus is a Principal Systems Engineer for JMP Statistical Discovery, which creates interactive and highly visual statistical discovery software designed for scientists and engineers. He supports sales and customer development in the Southwest region of the U.S. as technical lead.
An applied physicist by training, Oflus previously worked as a rocket scientist using statistical methods to support risk assessment on the design and simulation of several projects for NASA and U.S. Air Force. He is a member of the American Society for Quality and the American Statistical Association. Oflus regularly delivers talks and keynotes on data mining and predictive modeling; he also teaches data science at the University of California Riverside as a part-time lecturer.
