Online capability-based resource allocation for on-site construction operations utilizing digital twin models

Abstract

Planning and controlling on-site construction operations are complex and dynamic procedures, mainly manually executed without algorithmic decision support. An initial challenge is to allocate available resources to construction processes based on required and available capabilities. Due to the dynamic nature of construction projects (e.g., redesigns, resource failure, unpredictable restrictions), there is a demand for frequent reallocation of resources. In recent years, researchers studied capability-based resource allocation approaches by defining ontologies to describe the capabilities of resources. However, since most of the existing approaches focus on ontologies for resources in production environments (e.g., industrial robots), the modeling and application of the models for online allocation in dynamic construction environments remain unsolved. In this study, an ontology-based Digital Twin model, adopted from a production engineering background, is used to enable online capability-based resource allocations for construction-specific approaches. The Digital Twin model can be updated by a lightweight, publish-subscribe network, triggering an update of capability-based feasibility checks for resource allocations. The resulting framework is tested on a demo construction project from the research project “Internet of Construction (IoC)”. The results contribute to the automation of planning and controlling resource allocations for dynamic on-site construction operations. Using machine-readable ontologies, the transition from manually performed activities to robotically supported tasks is enabled.

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