Abstract

This article introduces a new mixed integer linear programming (MILP) approach to the modular architecture design problem based on the design structure matrix (DSM). The DSM modularization (clustering) problem aims to maximize the modularity (quantified by the Q-metric) under constraints reflecting practical design/manufacturing/maintenance considerations. A MILP formulation is developed to optimize a modular architecture under constraints. The developed formulation is verified through two case studies on the subsystems of an automobile and an electric train. Both case studies successfully demonstrate the proposed formulation's effectiveness, highlighting its practical applicability.

Issue Section:
Design Theory and Methodology
Keywords:
constrained clustering, design structure matrix, mixed integer linear programming, modular architecture design, decision theory, design for X, design optimization, multi-objective optimization, systems engineering
Topics:
Design

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