Ontology-driven automated and dynamic construction work scheduling using openBIM data

Shakharov, Azamat ORCID: https://orcid.org/0009-0008-9197-9176 2026. Ontology-driven automated and dynamic construction work scheduling using openBIM data. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

Construction projects are complex undertakings that involve many stakeholders. These projects often experience delays due to several reasons, such as budgetary limitations, ineffective management, logistical difficulties, poor design, poor communication, and environmental concerns. Construction work scheduling is one of the key elements in planning and delivering projects efficiently. Conventional scheduling methods widely used in the industry worldwide heavily rely on human expertise and manual effort. These methods are weakly integrated with digital information and generally treat project duration as static rather than adaptable to changing conditions. This research has identified that there is a lack of fully automated and adaptive scheduling systems that incorporate dynamic factors, the integration of digital technologies such as BIM is underexplored, interoperability between tools has limitations, and there is a lack of validation in real-life environments. The main aim of this research is to understand how more dynamic and accurate automated construction scheduling can be achieved by considering delay factors before and during construction, compared with traditional scheduling methods. This aim will be addressed through systematic literature reviews, survey and case study. These will provide an evidence-based foundation for developing an automated dynamic scheduling framework. Implementing the framework in the real-world project will demonstrate its ability to produce more realistic and context-sensitive schedules. This thesis’ systematic literature review of representation of knowledge and experience as the rules for automated construction scheduling will provide a comprehensive analysis of the current state of the field. This understanding will help to identify the necessary rules for an automated scheduling framework. Another systematic literature review of global construction delay factors will provide comprehensive understanding of the delay factors identified by studies from various regions. The findings will be incorporated into the survey. The survey will capture practitioner perspectives on delays under the specific climatic and industrial conditions of Kazakhstan. A third systematic literature review will be conducted to identify the information required for construction project scheduling. The identified data types will be analysed for their alignment with the OpenBIM data structure. This analysis will demonstrate the capability of the OpenBIM format to effectively store and share the data types necessary for scheduling. Based on these findings an automated construction work scheduling framework will be developed. Delay factors will then be incorporated to enhance the adaptability of the framework. The case study then provides a basis for evaluating the proposed framework against conventional scheduling practice. Validation on a Kazakhstan case study will demonstrate that the framework can automatically generate list of tasks, assign them to meaningful stages, and produce both static and weather-adjusted dynamic schedules. The generated schedules will be compared with the actual baseline and as-built schedules of the case. The validation results reveal that integrating weather considerations enhances scheduling dynamism, yet it does not entirely bridge the gap between predicted and actual performance of the project. The results have shown that an automatically generated schedule considering dynamic factors such as weather was 20% more accurate when compared to manual scheduling. This indicates that integrating dynamic factors enhances the overall accuracy of the schedule. It also demonstrates that the framework is able to generate a static schedule from geometric and semantic model data and effectively incorporates external environmental constraints into duration calculations. The thesis contributes a semantically rich scheduling framework that connects BIM data, scheduling knowledge, and weather information to support more transparent and adaptive construction scheduling. The results of the validation of this framework show that the weather-adjusted schedule was closer to actual construction outcomes than the baseline static schedule, although it still did not fully reproduce the final as-built result. This indicates that weather explains an important part of delay, but not all of it, and that construction performance is also shaped by the other factors. Thus, overall, this thesis demonstrates that the framework can be used as a basis for future integration of additional delay factors and regulatory constraints.

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Schools > Engineering
Uncontrolled Keywords:	1. Construction scheduling 2. OpenBIM 3. Automated scheduling 4. Dynamic scheduling 5. IFC 6. Ontology
Date of First Compliant Deposit:	29 September 2026
Last Modified:	30 Sep 2026 09:33
URI:	https://orca.cardiff.ac.uk/id/eprint/189870

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