Ontology-based mapping approach for automatic work packaging in modular construction

Xiao Li, Chengke Wu, Fan Xue, Zhile Yang, Jinfeng Lou, Weisheng Lu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)

Abstract

Many cross-knowledge domain tasks involving various professional backgrounds have been transferred from construction sites to factories in modular construction (MC). In MC, forming optimal work packages which can handle the complexity of product breakdown structures and dynamic project progress is critical for task planning and execution. However, forming MC work packages is time-consuming and ineffective because it is performed manually while not adequately considering domain knowledge. To address the problem, this study proposes a dynamic ontology-based mapping (DOM) approach to automatically generate semantic-enriched work packages. For this purpose, ontologies of MC products, topology, and tasks are established to incorporate domain knowledge. Then, a customized Latent Dirichlet Allocation (LDA) model for mapping products to tasks and a weighted hierarchical clustering model for grouping dynamic tasks into work packages are developed. The effectiveness of the DOM approach is tested in an MC case project and controlled experiments. The results demonstrate that the DOM approach can significantly increase the accuracy and efficiency of the dynamic work packaging process while reducing planning time compared to conventional methods, which thus improve the collaborative management and performance of MC projects.

Original languageEnglish
Article number104083
JournalAutomation in Construction
Volume134
DOIs
Publication statusPublished - Feb 2022

Keywords

  • Hierarchical clustering
  • Latent Dirichlet allocation
  • Modular construction
  • Ontology
  • Project planning
  • Work package

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction

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