Peng, L.; Yang, H.; Ju, A.; Li, X. and Jiang, Z. (2026) Data-driven real-time digital twin framework for tunnel boring machine monitoring. Journal of Construction Engineering and Management, 152(9): 04026134, ISSN 0733-9364
Abstract
Construction enterprises often face challenges related to organizational complexity, cross-departmental coordination, and data redundancy. In full-face tunnel boring machine (TBM) construction, these challenges can impede the timely and accurate dissemination of information, thereby reducing the efficiency of project scheduling. To address these challenges, data-driven monitoring and management systems have proven to be an effective solution. The data-driven model replaces the conventional general model, reduces cross-departmental coordination time, and enables rapid development of differentiated monitoring systems for various projects. We assess system effectiveness by analyzing specific cases using real-time data. In terms of cutter head damage, 65% of potential damage has been successfully prevented. This helps reduce construction delays caused by equipment downtime, enhances overall management capabilities, and supports the efficient operation of construction activities.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | consolidated supervision; data fusion; decision support systems; digital twins; intelligent systems; tunnel boring machine |
| Index terms: | management system, dissemination, complexity, efficiency, face, construction delay, construction activity, data fusion, real-time data, redundancy, coordination, project scheduling, system effectiveness, tunnel, monitoring, supervision, intelligent system, decision support, digital twin |
| Subjects: | control systems, data science, automation and robotics, management, project controls, assessment methods, construction operations, systems engineering, psychology, knowledge translation, data management, infrastructure and transport systems, decision analysis, digital engineering, performance management |
| Topics: | Organizational Design, Risk Management, Human Resources, Engineering Principles, Digital Applications, Research Practice, Time Control, Project Management, Quality Management, Information Management, Site Management |
| Descriptive scope: | 3 PCA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here