Knowledge-based cost modelling system for offsite manufacturing in construction
Ontologies are aimed at providing a shared conceptualisation of a domain knowledge within a particular field. Although they are mainly used for knowledge representation, ontologies have also been adopted in reasoning to facilitate decision support and in computations. However, choosing between offsite and conventional method of construction still poses a major challenge for construction professionals as a result of certain misconceptions and lack of appropriate knowledge-based costing tools. Hence, offsite knowledge is fragmented, thereby inhibiting the realisation of its value relative to other methods of construction, especially in terms of cost comparison. The research proposes an ontology-based approach for organising and formalising offsite knowledge in order to generate accurate cost estimates.
At the end of the study, the project will develop a proof-of-concept automated system to estimate cost for offsite manufacturing methods by using semantic web and ontologies for supporting long-term value realisation from built assets. The project contributions will be beneficial in that:
It will add to existing knowledge on cost modelling for OSM and the published ontology can be accessed by researchers willing to further expand on the subject matter.
For clients in design and build projects, the research will facilitate easy access to data on offsite components, possible production processes and resulting cost savings (through the published ontology) so as to supports decision making for stakeholders wanting to plan, design, construct and operate built assets by appraising the cost of their choices and decisions. For offsite manufactures, it will be useful in evaluating and choosing offsite options based on accessing value-adding techniques/processes to deliver a proposed project.
Kudirat Olabisi Ayinla, Zulfikar Adamu, (2018) "Bridging the digital divide gap in BIM technology adoption", Engineering, Construction and Architectural Management, Vol. 25 Issue: 10, pp.1398-1416, https://doi.org/10.1108/ECAM-05-2017-0091