Process Optimization of a Superfinishing Machine through Experimental Design and Mixed Response Surface Models

摘要

This article deals with process optimization for a centrifugal compressor. More precisely, the technological problem concerns the reduction of the surface roughness of centrifugal compressor impellers through a new technology implemented by GE Oil & Gas called superfinishing. The new technology is studied through statistical methods in order to achieve a minimization of the final roughness according to the best set of levels for the abrasive component mixture and the time process. To this end, an experimental design is planned for three different materials-for example, three types of steel-and mixed response surface models are applied. The application of mixed models allows us to estimate random effects, useful for better controlling the process variance in a robust design approach. Within this framework, a random effect is the initial roughness, measured for each impeller vane before starting the superfinishing process. Furthermore, random effects are included in the final optimization step. The contribution of this article is the study of this new superfinishing process through mixed response surface models and robust design optimization, in order to set the best levels of the abrasive component mixture and time process to minimize the final roughness for a centrifugal compressor impeller.