Abstract This research proposes an ontological inference process to automate the process of searching for the most appropriate work items, which is limited to tiling in this case study. The proposed ontological approach can help engineers to find work items with greater ease and consistency. Sugges...
Abstract This research proposes an ontological inference process to automate the process of searching for the most appropriate work items, which is limited to tiling in this case study. The proposed ontological approach can help engineers to find work items with greater ease and consistency. Suggestions are also made for further research on ways of improving the accuracy of BIM-based quantity take-off, and developing a methodology to match between work items which are expressed as different terms; however, the proposed approach emphasizes the automation of searches using BIM data to find items suitable for building elements and materials. To enable automated inference, this study establishes (1) a work condition ontology that consists of the determinants required to select work items, (2) a work item ontology, which consists of the factors defining the tiling method, and (3) semantic reasoning rules. By conducting a case study to demonstrate the proposed ontological inference process in a real-world situation, we confirm that the proposed process can provide consistent results; however, since work items differ depending on construction type and technological advancement, the work item ontology should be continually revised and updated. The ontological inference process removes the need for the intervention of a cost estimator's subjectivity in searching for an appropriate work item. Also, if ontology is elaborately defined by the knowledge of experienced engineers, then accurate and consistent results can be obtained. In addition, the proposed process will assist cost estimators to use BIM data more easily, and it will help the expansion of BIM-based construction management. Highlights We develop the ontology that enables automated search of most appropriate work items The scope of ontology is limited to tile work. We propose ontological approach to building cost estimation.
Abstract This research proposes an ontological inference process to automate the process of searching for the most appropriate work items, which is limited to tiling in this case study. The proposed ontological approach can help engineers to find work items with greater ease and consistency. Suggestions are also made for further research on ways of improving the accuracy of BIM-based quantity take-off, and developing a methodology to match between work items which are expressed as different terms; however, the proposed approach emphasizes the automation of searches using BIM data to find items suitable for building elements and materials. To enable automated inference, this study establishes (1) a work condition ontology that consists of the determinants required to select work items, (2) a work item ontology, which consists of the factors defining the tiling method, and (3) semantic reasoning rules. By conducting a case study to demonstrate the proposed ontological inference process in a real-world situation, we confirm that the proposed process can provide consistent results; however, since work items differ depending on construction type and technological advancement, the work item ontology should be continually revised and updated. The ontological inference process removes the need for the intervention of a cost estimator's subjectivity in searching for an appropriate work item. Also, if ontology is elaborately defined by the knowledge of experienced engineers, then accurate and consistent results can be obtained. In addition, the proposed process will assist cost estimators to use BIM data more easily, and it will help the expansion of BIM-based construction management. Highlights We develop the ontology that enables automated search of most appropriate work items The scope of ontology is limited to tile work. We propose ontological approach to building cost estimation.
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