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- Publisher Website: 10.36680/J.ITCON.2023.011
- Scopus: eid_2-s2.0-85158057822
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Article: AN ONTOLOGY-BASED COST ESTIMATION FOR OFFSITE CONSTRUCTION
Title | AN ONTOLOGY-BASED COST ESTIMATION FOR OFFSITE CONSTRUCTION |
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Authors | |
Keywords | Building Information Modeling DfMA Linked Building Data Offsite Construction Ontology Engineering |
Issue Date | 2023 |
Citation | Journal of Information Technology in Construction, 2023, v. 28, p. 220-245 How to Cite? |
Abstract | Design for manufacturing and assembly (DfMA) has been widely applied to support the decision-making process in offsite construction. With a DfMA approach, cost estimation requires taking product design and production processes into consideration. Current studies conduct cost estimation built upon quantity takeoffs. However, they do not provide a vocabulary to relate cost estimates to offsite construction processes. This paper presents a new domain ontology, Offsite Housing Ontology (OHO) using the NeOn methodology framework to support cost estimation considering products, resources, and production processes. OHO semantically defines offsite construction domain terminology and relationships. This supports a unified model, required for efficient collaborative design management. The efficiency and effectiveness of the OHO approach are demonstrated in a real-world DfMA scenario through the development of a Knowledge-Based Engineering tool to automate cost estimation. The approach can be adapted and extended to accommodate a very wide range of offsite housing, delivering important optimization and automation benefit from DfMA solutions. |
Persistent Identifier | http://hdl.handle.net/10722/354988 |
ISSN | 2023 Impact Factor: 3.6 2023 SCImago Journal Rankings: 0.733 |
DC Field | Value | Language |
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dc.contributor.author | Vakaj, Edlira | - |
dc.contributor.author | Cheung, Franco | - |
dc.contributor.author | Cao, Jianpeng | - |
dc.contributor.author | Tawil, Abdel Rahman H. | - |
dc.contributor.author | Patlakas, Panagiotis | - |
dc.date.accessioned | 2025-03-21T09:10:28Z | - |
dc.date.available | 2025-03-21T09:10:28Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | Journal of Information Technology in Construction, 2023, v. 28, p. 220-245 | - |
dc.identifier.issn | 1874-4753 | - |
dc.identifier.uri | http://hdl.handle.net/10722/354988 | - |
dc.description.abstract | Design for manufacturing and assembly (DfMA) has been widely applied to support the decision-making process in offsite construction. With a DfMA approach, cost estimation requires taking product design and production processes into consideration. Current studies conduct cost estimation built upon quantity takeoffs. However, they do not provide a vocabulary to relate cost estimates to offsite construction processes. This paper presents a new domain ontology, Offsite Housing Ontology (OHO) using the NeOn methodology framework to support cost estimation considering products, resources, and production processes. OHO semantically defines offsite construction domain terminology and relationships. This supports a unified model, required for efficient collaborative design management. The efficiency and effectiveness of the OHO approach are demonstrated in a real-world DfMA scenario through the development of a Knowledge-Based Engineering tool to automate cost estimation. The approach can be adapted and extended to accommodate a very wide range of offsite housing, delivering important optimization and automation benefit from DfMA solutions. | - |
dc.language | eng | - |
dc.relation.ispartof | Journal of Information Technology in Construction | - |
dc.subject | Building Information Modeling | - |
dc.subject | DfMA | - |
dc.subject | Linked Building Data | - |
dc.subject | Offsite Construction | - |
dc.subject | Ontology Engineering | - |
dc.title | AN ONTOLOGY-BASED COST ESTIMATION FOR OFFSITE CONSTRUCTION | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.36680/J.ITCON.2023.011 | - |
dc.identifier.scopus | eid_2-s2.0-85158057822 | - |
dc.identifier.volume | 28 | - |
dc.identifier.spage | 220 | - |
dc.identifier.epage | 245 | - |