Predictive maintenance for logistics equipment

Develop AI systems that predict when warehouse and logistics equipment will fail, allowing for preventive maintenance that saves massive downtime costs. Your platform analyzes vibration sensors, temperature data, usage patterns, and performance metrics from forklifts, conveyor systems, sorting machines, and loading docks. Machine learning models predict optimal maintenance windows 2-8 weeks in advance. Charge $500-2500/month per major piece of equipment plus installation and setup fees of $3000-15000. Target distribution centers, airports, ports, and manufacturing facilities where equipment downtime costs $5000-50000 per hour.