Application of Stochastic Regression for the Configuration of Microrotary Swaging Processes

Abstract EN

In micromanufacturing, a precise adjustment of manufacturing, handling, and quality control processes constitutes an essential factor for success.

The continuing miniaturization of workpieces and production devices results in ever decreasing tolerances, whereas machines and processes become increasingly more specialized.

Thereby, the so-called size effects render the direct application of knowledge from the area of macromanufacturing impossible.

In this context, this paper describes the application of the μ-ProPlAn method for the configuration of an infeed rotary swaging process for microcomponents.

At this, the cause-effect relationships between relevant process parameters are analyzed using stochastic regression models, in order to determine cost-efficient process configurations for the manufacturing of bulk and tubular microcomponents.