A case study on integrating data analysis and process mining in conventional tunnel construction

Conventional tunnel construction often relies on manual methods of construction process analysis, using tools such as paper-based cycle diagrams or spreadsheets, which lack immediate updates and capabilities, limiting performance evaluation, communication, and decision-making. As a result, moving to a fully digital process incorporating business intelligence capabilities can deliver benefits by improving data-driven decision-making, operational efficiency and resource allocation. This paper presents a case study using construction documentation to evaluate the applicability of data and process analytics in conventional tunnelling. We also present a novel approach to visualising and analysing construction sequence deviations. The study demonstrates how data and process analysis can be utilised to evaluate the activity sequences, the duration of single activities, advance rates, and general project performance. By adhering to established industry standards, this research examines the practical implementation of data analysis methods in operational tunnelling environments, contributing to the development of integrated digital workflows. • Statistical methods and process mining enhance resource allocation and activity monitoring in conventional tunnelling. • The proposed prototype helps identify deviations from expected construction sequences and activity durations. • Visualisation of construction data helps identify documentation errors and optimise processes. • A case study demonstrates the benefits of digital documentation and business intelligence in tunnelling.