Identification of influential function modules within complex products and systems based on weighted and directed complex networks

Abstract

As a cost saving and profit-making strategy, a modular design is being employed in developing complex products and systems (CoPS) in recent decades. At the early stage of design, the reliability of a product can be improved by identifying the influential function modules based on the modular function architecture. In this study, the weighted LeaderRank algorithm and susceptible-infected-recovered (SIR) model of weighted and directed complex networks (WDCNs) are employed to identify the influential function modules of modular CoPS at the conceptual design stage. First, the structure of the function module is obtained and is mapped into a WDCN. Second, based on the similarity between the behaviors of nodes in the WDCN and function modules in the CoPS, a node-identification approach based on the weighted LeaderRank algorithm is employed to identify the influential function modules, whose influences are then verified through the SIR model. The influential function modules of a modular large tonnage crawler crane are determined as a case study to demonstrate the effectiveness and validity of the developed method.