The Challenge
A Thai manufacturing facility operating 3 production lines was experiencing 6–10 unexpected equipment failures per year, each causing production shutdowns of 6–12 hours. Beyond the lost production, emergency repairs cost 3–5x more than planned maintenance. The engineering team had no early warning system — failures were only discovered when machines stopped working.
The facility ran 24/7 but had no real-time visibility into equipment health, vibration patterns, temperature trends, or performance degradation — all known precursors to failure.
The Solution
LYNXFUSE deployed Synapse Gateway — a custom IoT monitoring and AI analysis platform:
IoT Sensor Integration
Connected vibration, temperature, power consumption, and acoustic sensors to all critical equipment via MQTT protocol
Real-Time Telemetry Dashboard
Live equipment health metrics visible from any device — production floor tablets, management mobile, maintenance laptops
AI Anomaly Detection
Machine learning model trained on normal operating parameters — automatically detects when patterns deviate from baseline
Predictive Alert System
When anomaly detected, automatic alerts via LINE OA to maintenance team with severity classification and recommended action
Maintenance Scheduling Integration
High-confidence predictions automatically create maintenance tickets in the team's scheduling system
Historical Analysis
All telemetry data stored and used to continuously improve prediction accuracy over time