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Proceedings / IGLC 32

IGLC 32 · Auckland, New Zealand · 2024

Digital Twin Based Integrated Decision Support System for Enhanced Decision-Making in the Last Planner System

  1. PhD Student, Department of Civil and Environmental Engineering, Faculty of Engineering, University of Alberta, Canada, zhong15@ualberta.ca, 0000-0002-7113-3439
  2. PhD Student, Department of Civil and Environmental Engineering, Faculty of Engineering, University of Alberta, Canada, sabek@ualberta.ca, 0009-0005-2906-9874
  3. PhD Student, Department of Civil and Environmental Engineering, Faculty of Engineering, University of Alberta, Canada, yulun6@ualberta.ca, 0000-0003-4281-4961
  4. Assistant Professor, Department of Civil and Environmental Engineering, Faculty of Engineering, University of Alberta, Canada, qipei@ualberta.ca, 0000-0003-1409-3562
  5. Assistant Professor, Department of Civil and Environmental Engineering, Faculty of Engineering, University of Alberta, Canada, gaang@ualberta.ca, 0000-0002-6341-2585
  6. Professor, Department of Civil and Environmental Engineering, Faculty of Engineering, University of Alberta, Canada, vagonzal@ualberta.ca, 0000-0003-3408-3863

https://doi.org/10.24928/2024/0117

Abstract

This paper discusses the enhancement of decision-making within the Last Planner System (LPS) through digitalization, emphasizing the role of a Digital Twin-based Integrated Decision Support System (DT-IDSS) aligned with Lean Construction 4.0 principles. The proposed conceptual framework DT-IDSS aims to address the challenges in LPS decision-making in terms of autonomation, data integrity, user-centricity, and decision-making rapidness, by integrating user-centric design with advanced technologies such as Digital Twins, Internet of Things, Blockchain, and Artificial Intelligence. It features a decentralized reality capture flow for data processing and storage, and an information loop fostering collaborative stakeholder engagement. The system's user-centric development loop adopts an agile, iterative approach, meeting the dynamic needs of construction projects. The integrations of workflows and technologies in the proposed framework has a huge potential in addressing challenges in the deficiency in system integration, which are essential to effectively support information, computation, visualization, and services, thereby enabling stakeholders to make informed decisions. Future research will focus on assessing decision-making effectiveness, enhancing system scalability, improving data management security, and achieving interoperability with existing management systems. This research contributes to the digital transformation of decision-making process, aiming to provide guidance for future developments in this rapidly evolving field.

Keywords

  • Last Planner® System (LPS)
  • Lean Construction 4.0
  • Integrated Decision Support System (IDSS)
  • Digital Twin
  • Smart Digital Technologies (SDTs)

Cite this paper

APA 7th edition

Wang, Z., Sabek, M., Wu, Y., Mei, Q., Lee, G., & González, V. A. (2024). Digital Twin Based Integrated Decision Support System for Enhanced Decision-Making in the Last Planner System. In D. B. Costa, F. Drevland, & L. Florez-Perez (Eds.), Proceedings of the 32nd Annual Conference of the International Group for Lean Construction (IGLC 32) (pp. 609–621). https://doi.org/10.24928/2024/0117

Shortened reference for IGLC papers

Wang, Z., Sabek, M., Wu, Y., Mei, Q., Lee, G., & González, V. A. (2024). Digital Twin Based Integrated Decision Support System for Enhanced Decision-Making in the Last Planner System. IGLC32. https://doi.org/10.24928/2024/0117