Case Study
AI-Powered Predictive Maintenance System for Critical Terminal Equipment
Port cranes fail silently mid-lift, disrupting vessels and schedules for a major international operator where fixed maintenance schedules drove up costs for Ship-to-Shore cranes, Rubber-Tyred Gantry cranes, and automated vehicles—replacing parts unnecessarily yet missing breakdowns. InTech transformed reliability by building an AI-powered predictive maintenance system with IoT sensors and machine learning, detecting issues weeks ahead to enable proactive fixes during planned windows, slash emergency shutdowns, minimize downtime, and optimize costs while ensuring seamless operations.
