The Problem
They faced critical challenges due to reliance on reactive and time-based maintenance. The core issue was a complete lack of real-time visibility into the actual condition of their high-value assets.
The solution
Biotz designed and deployed a comprehensive Industry 4.0 Predictive Maintenance System, integrating a full-stack architecture to turn raw machine data into actionable intelligence.
- IoT Integration: Sensors were deployed on critical machinery to stream high-frequency data (vibration, temperature, power consumption) to the Biotz IoT Platform.
- Digital HMI (Human-Machine Interface): A centralized web dashboard was created for the maintenance team, providing a visual "health score" for every machine. The system automatically generated and dispatched predictive work orders only when the AI model flagged an impending issue.
The impact
Operational StabilitySubstantial reduction in unplanned downtime.Manufacturing capacity became more reliable and predictable, fulfilling client commitments with greater confidence.
Maintenance CostOptimization of maintenance scheduling and spend.Shifted resources from costly, reactive emergencies to planned, condition-based interventions, lowering labor and spare parts inventory costs.
ProductivityIncreased Overall Equipment Effectiveness (OEE).Maximized the productive use of high-value machinery, directly contributing to greater output and profitability.
Future ReadinessEstablished a scalable digital foundation.Guibe is now equipped to integrate further AI and automation tools across its manufacturing processes for continued future growth.
