Multiobjective optimization-based decision support for building digital twin maturity measurement [1]
Tytuł | Multiobjective optimization-based decision support for building digital twin maturity measurement |
Publication Type | Journal Article |
Rok publikacji | 2024 |
Autorzy | Chen Z-S [2], Chen K-D [3], Xu Y-Q [4], Pedrycz W [5], Skibniewski MJ [6] |
Journal | Advanced Engineering Informatics |
Volume | 59 |
Date Published | 01/2024 |
Słowa kluczowe | Building digital twin; Maturity model; Fairness concern; Multiobjective optimization; Probability distribution function [7] |
Abstract | The digital twin [8] (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 [9] 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. |
DOI | 10.1016/j.aei.2023.102245 [10] |