Variability monitoring of multistage manufacturing processes using regression adjustment methods

The recent trends in manufacturing toward modularity and flexibility result in complex multistage manufacturing processes that consist of many interrelated workstations. In such processes, it is highly desirable to differentiate between local and propagated variations, and implement process variability monitoring and reduction. In this paper, attention is focused on the properties of a widely used regression-adjustment-based method in the monitoring of variation propagation in multistage manufacturing processes. Particularly, the impacts of measurement errors and regressor selection on the monitoring scheme are investigated, and conclusions which can help guide the use of this method are summarized. Numerical examples are also presented to validate the analysis.