https://doi.org/10.24928/2024/0134
An Ontology for Representing Crawler Crane Operational Space Requirement on Semantic Web
Ajay Kumar Agrawal1, Yang Zou2, Long Chen3, Hongyu Jin4 & Mohammed Adel Abdelmegid5
1PhD Candidate, Department of Civil and Environmental Engineering, University of Auckland, Auckland, New Zealand, [email protected], orcid.org/0000-0001-8669-32552Senior Lecturer, Department of Civil and Environmental Engineering, University of Auckland, Auckland, New Zealand, [email protected], orcid.org/0000-0001-6150-6126
3Lecturer, School of Architecture, Building and Civil Engineering, Loughborough University, Leicestershire, UK, [email protected], orcid.org/0000-0002-6771-752X
4Lecturer, Department of Civil and Environmental Engineering, University of Auckland, Auckland, New Zealand, [email protected], orcid.org/0000-0001-9316-6971
5Lecturer, School of Civil Engineering, University of Leeds, Leeds, UK, [email protected], orcid.org/0000-0001-6205-570X
Abstract
Lookahead planning incorporates checking and removing operational constraints to develop achievable plans. The manual constraint-checking process is arduous because (1) Construction constraints are dynamic due to constantly changing project conditions, and (2) The information concerning constraints, e.g., attributes and status, are dispersed across heterogeneous databases. While semantic web technology has been used to automate constraint-checking and address these issues, space constraints, e.g., space needed for resource operation, have often been ignored. Cranes are crucial construction resources, necessitating checking of associated space constraints for developing constraint-free lookahead plans. Representing crane operational space requirements on the semantic web should be the first step for such checking. However, existing ontologies cannot do so. This study aims to develop a Crane Space Representation Ontology (CSRO) to represent different components of the operational space of a crawler crane with a lattice boom. Built using Ontology Development 101 methodology, CSRO includes four classes, 19 subclasses, nine object properties, and seven datatype properties, representing crane operational space with diverse geometries like bounding box, cylinder, and cone. Automated consistency checking and task-based evaluation confirm the CSRO's consistency and effectiveness in addressing the competency questions regarding various aspects of space requirements for crane operation.
Keywords
Last Planner® System, Lookahead Planning, Constraint Analysis, Semantic Web, Crawler Crane.
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Reference
Agrawal, A. K. , Zou, Y. , Chen, L. , Jin, H. & Abdelmegid, M. A. 2024. An Ontology for Representing Crawler Crane Operational Space Requirement on Semantic Web, Proceedings of the 32nd Annual Conference of the International Group for Lean Construction (IGLC 32) , 648-659. doi.org/10.24928/2024/0134
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