Fireproofing has become a critical asset when handling large facilities like refineries, with millions of dollars spent on the cement-like compound across several facilities to ensure a safe working environment for employees and a minimized fire risk. However, fireproofing degrades in unpredictable ways over time, leading to a risk of potential infrastructure damage in the event of a fire or even human casualties from falling fireproofing pieces.
Discover how Kleinfelder leveraged LiDAR scanning technology and machine learning-powered solutions to help their clients save $1.2 million and almost 8,000 hours by modernizing their fireproofing quality inspections and maintenance methods for their refineries. In this session, Mark will talk you through how his team at Kleinfelder used 3D scanning technology to document the facility and develop an autonomous system that monitors the conditions of fireproofing materials within the plants. Find out how the machine learning solution uses these 3D scans to save time by detecting and prompting repairs of fireproofing deficiencies automatically while providing quality inspectors complete remote site access, eliminating the need for physical site visits.
