Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

Parametric CFD analysis lets users statistically determine the fluid flow around a device. Fluid dynamics is one of the primary engineering sciences used to design a wide variety of vehicles, machines ...

In the post-parametric era, one key challenge for architectural design is the acquisition, processing, and integration of data. Designers already have an enormous amount of computable data from ...

Sharing data from design to the field can improve reliability, but it raises other questions for which there are no clear answers today. SE: How can the industry ensure system-level reliability in ...

During my earlier career as a process integration engineer, one of my primary responsibilities was to find yield enhancement opportunities by investigating underlying relationships between bin ...

Parametric release and real-time testing use manufacturing data to ensure that products are made according to defined standards. PharmTech talks to Boehringer Ingelheim's Heribert Hausler about these ...