A model-based approach to refine process parameters in smart manufacturing

Abstract

This article describes a model-based approach for defining and refining process parameters in dynamically changing, smart manufacturing environments. This approach uses equation-based models to predict how part quality will respond to changes in that environment. The results from these models provide the major inputs into a process-parameter-optimization technique, which is used to set the values for various process parameters. In developing these models, we integrated various concepts from process improvement frameworks, such as Define–Measure–Analyze–Improve–Control and Monitor–Analyze–Plan–Execute–Knowledge, with techniques from model-based engineering. After describing the approach, we demonstrate its use in an additive manufacturing process example.