Modern tunneling faces significant challenges due to geotechnical variability and the need to optimize the operational efficiency of tunnel boring machines (TBM). Digitalization and Big Data have emerged as key tools to improve decision-making, reduce risks, and increase productivity in these projects. This article explores the impact of these technologies on TBM data management and how advanced systems can transform the excavation process.
TBM excavation is a complex process that requires continuous analysis of multiple operational and geotechnical variables. Historically, decision-making in these projects relied on retrospective data analysis, leading to delays in problem detection and operational adjustments. With digitalization, it is now possible to access real-time data and apply predictive models to optimize excavation.
Impact of Big Data on Tunneling
Big Data enables the massive analysis of information collected by TBM sensors, offering several advantages:
Real-time monitoring: Immediate access to key data such as thrust, torque, and TBM revolutions.
Trend analysis and data visualization: Identifying correlations between operational and geotechnical parameters to improve excavation strategies.
Optimization of penetration rates: AI-based predictive modeling to forecast TBM advance rates.
Real-time geotechnical recalibration: Dynamic adjustment of ground parameters at the end of each excavated ring.
Incident logging and categorization: Tracking operational, geotechnical, and logistical events to enhance performance.
Predictive Models and Geotechnical Recalibration
One of the most significant advancements in TBM digitalization is the use of predictive models based on artificial intelligence. These models can forecast TBM advance rates considering machine performance and soil characteristics. Additionally, they allow for the automatic recalibration of geotechnical parameters at the end of each excavated ring, ensuring that excavation adapts to real ground conditions in real time.
Implementation of Technologies in TBM Management
Data management platforms have revolutionized the way tunneling projects are handled. These tools centralize critical information and facilitate:
Trend visualization and correlation analysis through customized plots.
Categorization and logging of geotechnical and operational incidents.
Generation of detailed reports for future analysis and continuous improvement.
Real-time assistance for TBM operators, facilitating operational adjustments.
DAARWIN: A Comprehensive Data-Driven Tunneling Solution
DAARWIN is an advanced TBM data management platform that integrates real-time monitoring, predictive modeling, and artificial intelligence. Thanks to its tools, it is possible to:
Real-time monitoring: Centralize and oversee TBM data continuously.
Predictive penetration rate modeling: Use AI to forecast TBM advance rates based on soil conditions and machine performance.
Geotechnical recalibration: Dynamically adjust ground parameters for each excavated ring.
Trend visualization and analysis: Assess TBM performance using customized plots.
Incident logging and categorization: Facilitate the analysis of geotechnical, operational, and logistical events.
Dynamic operator assistance: Provide real-time recommendations to optimize excavation.
Digitalization and Big Data are transforming TBM excavation, enabling more efficient, safer, and cost-effective management. The use of platforms like DAARWIN demonstrates that integrating real-time data, predictive analysis, and automation can significantly enhance the productivity and sustainability of tunneling projects. As these technologies evolve, their adoption will become a standard for the industry.
