Optimizing Design Structure Matrices Using Markov Chain Modeling and Community Detection

This paper proposes a new method to enhance the efficiency of the design process in Systems Engineering. Our approach involves utilizing a Markov Chain based on the Design Structure Matrix (DSM). By creating a transformation matrix using DSM and converting it into a Markov Chain, we enable faster convergence of process iterations and improved decoupling between modules or clusters. The Markov Chain is plotted as a tree using a layered layout algorithm and partitioned into communities using the Louvain algorithm. We applied our method to two types of DSM data, Component-based and Parameter-based, and the results showed valuable insights into the design process. Our approach is a valuable tool for managing complex systems, especially as systems become increasingly complex and challenging for engineers to manage during the design process.