Multiobjective optimization-based decision support for building digital twin maturity measurement

TitleMultiobjective optimization-based decision support for building digital twin maturity measurement
Publication TypeJournal Article
Year of Publication2024
AuthorsChen Z-S, Chen K-D, Xu Y-Q, Pedrycz W, Skibniewski MJ
JournalAdvanced Engineering Informatics
Volume59
Date Published01/2024
KeywordsBuilding digital twin; Maturity model; Fairness concern; Multiobjective optimization; Probability distribution function
Abstract

The digital twin (DT) represents a powerful tool for advancing construction industry to provide a cyber–physical integration that enables real-time monitoring of assets and activities and facilitates decision-making. Due to the inherent characteristics of the construction industry and the diverse possibilities with DT, proliferation of building digital twin (BDT) necessitates a comprehensive comprehension of its evolution and the creation of roadmaps. This paper aims to contribute to the formalization and standardization of BDT. It designs a novel assessment framework for the overall maturity measurement of existing BDT projects. The developed BDT maturity model incorporates a collective opinion generation paradigm based on a fairness-aware multiobjective optimization model to provide an expert-based evaluation system for evaluating the maturity of BDT projects. The effectiveness and feasibility of the proposed framework have been validated through a case study of an experimental BDT initiative. This paper establishes a generalizable framework for BDT maturity assessment that can offer insights into BDT maturity standards to construction practitioners to create effective strategies for the diffusion, development, and maturation of BDT.

DOI10.1016/j.aei.2023.102245

Historia zmian

Data aktualizacji: 19/12/2023 - 14:01; autor zmian: Żaneta Deka (zdeka@iitis.pl)