Inferring the Interactions in Complex Manufacturing Processes Using Graphical Models

Abstract

The new trends in manufacturing toward modularity and flexibility result in a larger number of interdependent operations in a process, leading to complex multistage manufacturing processes. Identifying the variation flow and implementing quality control in such processes is very challenging because of the complex interactions among different stages. This article presents a systematic model building methodology to identify the underlying interactions among stages through the integration of advanced statistical techniques in graphical models and engineering insights to manufacturing processes. A statistical testing procedure is developed to efficiently construct the chain graph of the key product characteristics in a process, making use of identified relationships at previous stages. A case study validating the effectiveness of the proposed procedure is also presented.