Predictive Maintenance System for Manufacturing

Description

An AI-driven predictive maintenance platform that monitors industrial equipment in real time to forecast failures before they occur. The system ingests sensor data from IoT devices, applies machine learning models to detect degradation patterns, and generates maintenance schedules that minimise downtime and extend asset life. It provides a dashboard for maintenance teams with alerts, trend visualisation, and work order integration. The platform supports deployment across single facilities or multi-site operations.

Alterations

• Custom ML models trained on equipment-specific failure modes
• Integration with SCADA, PLC, and existing IoT sensor networks
• Work order generation and CMMS integration (SAP PM, IBM Maximo)
• Custom alert thresholds and escalation chains
• Digital twin modelling for complex equipment
• Edge computing deployment for low-latency environments
• Multi-site aggregation and fleet-level analytics
• Regulatory compliance reporting for safety standards