Optimization of the Surface Grinding Process by Means of Modern Methods of Statistical Design of Experiments

Weinert, K.^{1, a}; Mehnen, J.^{1, b}; Webber, O.^{1, c}; Henkenjohann, N.

1)

Institut für Spanende Fertigung, Universität Dortmund, Baroper Str. 301, 44227 Dortmund

a) weinert@isf.de; b) mehnen@isf.de; c) webber@isf.de

Kurzfassung

The peripheral longitudinal surface grinding process with conventional corundum grinding wheels is often used to manufacture high precision surfaces. Inadequate process parameter settings may lead to the formation of visible patterns on the workpiece surface, which are difficult to measure with common roughness measuring methods. Needing only very few experiments, modern statistical methods are able to find optimal parameter settings to avoid these damages. Second order models, spatial regression, and proportional odds models are used to describe the grinding process results quantitatively as well as qualitatively. The different models are compared theoretically and practically with respect to their efficiency and prediction quality.

Schlüsselwörter

Production Process, Surface Grinding, Design of Experiments

Veröffentlichung

Production Engineering. Research and Development, 11 (2004) 1, S. 49-54