Data-driven Continuous Improvement Process framework for railway construction projects
- Conference Paper
Delays and cost overruns are frequent in infrastructure construction projects. Traditionally, deviations are often identified late, and it is very difficult to trace back the causes. Decisions are often taken by experience and not with the support of data directly coming from site. Moreover, schedules are often static and thus not able to reflect the real conditions on-site. Emerging technologies like Building Information Modeling (BIM), mobile cloud computing, and advanced sensors can help to overcome the previously mentioned issues. The collection of production data by sensors with the aim to compare production metrics with the schedule in order to introduce a Continuous Improvement Process (CIP). In the paper, we propose a framework for a digital platform to gather production data in real-time and to identify early on bottlenecks that could potentially lead to delays and deviations. The proposed platform should support in collecting, analyzing, and structuring production data. Furthermore, the platform should give insights and support organizational decision making of a CIP. With a demonstration case we show the three main functionalities of the platform: 1) retrospective analysis, 2) live analysis and 3) predictive analysis. In future research, the platform will be implemented and validated within railway construction projects of the company Rhomberg Sersa Rail Group AG. Show more
Book titleProceedings of the 38th International Symposium on Automation and Robotics in Construction
Pages / Article No.
PublisherInternational Association for Automation and Robotics in Construction (IAARC)
SubjectReal-time data; Construction; Lean construction management; Data analysis; Production control
Organisational unit09624 - Hall, Daniel M. (ehemalig) / Hall, Daniel M. (former)
NotesConference lecture on November 4, 2021.
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