Project monitoring and control of EPC projects are dynamic tasks, because each project has its own unique challenges that have to be addressed and resolved. For that reason, project management would be far more effective and predicable if you had a reliable way to capture knowledge in data form and analyse that data into useful information that would help toward better decision-making. That brings up the question of AI and how it can be leveraged in project monitoring and control.

AI-based project monitoring and project controls can be a game-changer in modern EPC projects. An AI-based project monitoring system would be able to ‘learn’ about the way a company handles resource management, project scheduling, supply chain management, quality, and safety from past project data and would be able to analyse those learnings to improve future outcomes. By teaching the system Machine Learning algorithms based on historical data, it is conceivable that an AI-based system would be able to analyse various potential possibilities and suggest the most suitable option. In this way, past data/knowledge can help an AI-based system correct previous mistakes and predict future outcomes with a high degree of accuracy, and also significantly optimize planning, resource management, and real-time decision-making.

Let’s break down the areas of application of AI in project monitoring:

1. Predictive Analytics:

Forecasting Demand: Analyze historical data of the various work packages and predict material, labor, and equipment needed in future, thereby ensuring that resources are available when needed.

Identifying Risks: Identify potential risks and bottlenecks by analyzing patterns and trends, thus allowing for proactive risk mitigation.

2. Scheduling Optimization:

Dynamic Scheduling: Optimize project schedules by adjusting task sequences and resource allocations in real-time, thus minimizing delays and maximizing efficiency.

Scenario Analysis: Simulate different project scenarios to determine the best course of action, thus helping planners to make informed decisions.

3. Resource Management:

Automated material Tracking: Track material usage and availability in real-time to ensure timely replenishment, thus reducing shortages.

Equipment Utilization: Optimize equipment usage by predicting maintenance needs and scheduling downtime, thus reducing idle time and improving availability.

4. Supply Chain Optimization:

Supplier Performance Analysis: Evaluate supplier performance based on delivery times, quality, and reliability, thus helping to select the best suppliers and negotiate better terms.

Just-In-Time Delivery: Coordinate with suppliers to ensure materials get delivered just in time, thus reducing storage costs and minimizing delays.

5. Site Monitoring and Management:

Real-Time Data Collection: Drones and IoT sensors can collect real-time data on site conditions, progress, and resource utilization, thus providing actionable insights for project managers.

Automated Inspections: Automate site inspections to identify potential issues, thus ensuring work fronts are ready for the next phase of construction.

6. Communication and Collaboration:

Virtual Assistants: Virtual assistants can facilitate communication and coordination among project stakeholders, thus ensuring everyone is informed and aligned.

Document Management notification: Ensure access through automated notification about the latest information, thus reducing delays caused by outdated or missing documents.

7. Quality Control and Safety:

Defect Detection: Analyze images and data from the construction site to detect defects and quality issues early, thus preventing rework and delays.

Safety Monitoring: Monitor safety conditions on-site and predict potential hazards, thus ensuring a safe working environment and reducing accidents.

8. Optimizing Workflows:

Lean Construction: Help implement lean construction principles by identifying and eliminating waste, thus optimizing workflows and improving overall efficiency.

Continuous Improvement: Continuously learn from project data, thus providing insights for ongoing process improvements and better resource utilization.

From the above we can see that even a cursory analysis of the effects of an AI-based system on project monitoring shows immediate and tangible benefits that affect the entire project lifecycle and increase the chance of successful project delivery.