Predictive Maintenance as a Service
Building an IoT-driven predictive maintenance platform for maritime vessels, leveraging edge computing and machine learning to prevent equipment failures before they occur.
Downtime Reduction
40%
Maintenance Savings
25%
Business Model
SaaS
The Challenge
Maritime vessels face significant operational challenges due to unexpected equipment failures, leading to costly downtime and safety risks. Traditional maintenance approaches are either reactive or based on fixed schedules, resulting in:
- •Unplanned vessel downtime costing $50,000+ per day
- •Over-maintenance of healthy equipment wasting resources
- •Lack of visibility into equipment health across the fleet
- •Safety risks from unexpected failures at sea
The Solution
IoT Sensor Network
Deployed comprehensive sensor arrays monitoring vibration, temperature, pressure, and acoustic signatures across critical equipment including engines, generators, and propulsion systems.
Edge Computing
Implemented edge processing capabilities for real-time anomaly detection, reducing bandwidth requirements and enabling immediate alerts even with limited satellite connectivity.
ML Predictive Models
Developed machine learning models trained on historical failure data to predict equipment failures 30-60 days in advance with 85%+ accuracy, enabling proactive maintenance planning.
Multi-tenant SaaS Platform
Built scalable cloud platform supporting multiple shipping companies with isolated data, customizable alerts, and white-label options for enterprise customers.
Technology Stack
Key Results
42%
Reduction in unplanned downtime across pilot fleet
$2.5M
Annual savings per vessel from optimized maintenance
85%
Prediction accuracy for critical equipment failures
15
Enterprise customers in product pipeline
Ready to Prevent Failures Before They Happen?
Let's explore how predictive maintenance can transform your fleet operations.
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