Data-driven and production-oriented tendering design using artificial intelligence

Paper i proceeding, 2024

Construction projects are facing an increase in requirements, making requirement management
labour intense. Therefore, this research project explores possibilities to automate the requirement
analysis in the bidding phase and link these requirements to verifications in the production phase.
The first part of the research targets the requirement analysis and applies natural language
processing techniques for automation possibilities. The second part of the research explores
production data as a data-driven verification method and how the data can be used in knowledge
feedback loops. The results show that applying natural language processing techniques for analysing
construction project requirements is a possible step towards systematic requirements
management. Furthermore, production data can be used as a knowledge base for quality
improvement in construction companies.