In the world of high-complexity projects, uncertainty and cost overruns are constant challenges that jeopardize the viability, timelines, and profitability of the work. These issues are especially critical in sectors such as construction, mining, and large infrastructures, where the conditions of the terrain and the environment are dynamic and difficult to predict. However, the advancement of artificial intelligence (AI) is transforming the way these risks are managed.
Uncertainty: The Silent Enemy
Uncertainty in high-complexity projects arises from factors such as:
Geotechnical variability: Terrain conditions, such as resistance, fractures, and stability, are difficult to model accurately before the work begins.
Limitations in data collection: Traditional terrain characterization technologies, such as drilling and surveys, provide limited data in space and time.
Traditional predictive models: Analytical models often oversimplify the behavior of the terrain, leading to errors.
Economic impacts: Budget and schedule deviations are common, affecting the financial viability of the project and generating conflicts among stakeholders.
AI as a Catalyst for Precision and Efficiency
Artificial intelligence offers tools to significantly reduce uncertainty, thanks to its ability to:
Integrate and analyze large volumes of data in real time, improving the accuracy of geotechnical models.
Predict complex behaviors using machine learning algorithms that identify hidden patterns and correlations in geotechnical data.
Simulate scenarios with greater detail and dynamism, allowing for decision adjustments during project execution.
One of the most notable technological developments in this field is DAARWIN, a solution developed by SAALG Geomechanics that has revolutionized the geotechnical management of high-complexity projects. DAARWIN combines AI with data analysis to provide a deep and dynamic insight into how the terrain behaves during construction.
How Does DAARWIN Minimize “Unforeseen” Costs in Project Budgets?
Real-time monitoring:
DAARWIN integrates data from geotechnical sensors installed in the ground, such as piezometers, inclinometers, and deformation monitoring systems. This allows for real-time observation of terrain behavior and quick adjustments to unforeseen variations.
Dynamic predictive analysis:
The platform uses advanced AI algorithms to update geotechnical models as new data is collected. This means decisions are not based solely on initial studies but on updated information throughout the project.
Design and execution optimization:
DAARWIN not only detects potential problems but also recommends optimal solutions based on the analysis of thousands of simulated scenarios. This reduces response times and minimizes budget deviations.
Cost-overrun reduction:
By identifying geotechnical risks before they occur, DAARWIN allows teams to take proactive measures, such as reinforcing specific areas of the terrain or adjusting construction methods. This results in a significant reduction in cost overruns due to delays or structural failures.
Tangible Impact on Complex Projects
Projects that have adopted DAARWIN have reported:
A reduction of up to 30% in cost overruns related to unforeseen geotechnical issues.
Better relationships between contractors, engineers, and owners, thanks to communication based on objective data.
Increased sustainability of the project by optimizing the resources needed to address risks.
The Future of Risk Management in Construction
The integration of AI-based technologies, such as DAARWIN, marks the beginning of a new era in project engineering. Beyond solving problems, these tools offer a preventive approach, where risks are not only mitigated but also anticipated with precision.
In a context where margins of error are shrinking, the ability to make informed and dynamic decisions thanks to AI is becoming an essential standard for the successful management of high-complexity projects.
