Smart Factory Modernisation for an Industrial Components Group
CYVERRA designed and implemented an end-to-end digital factory transformation, connecting legacy shop-floor machinery with cloud-based production intelligence. The program harmonised production telemetry, eliminated manual quality logging, and delivered real-time operational visibility across four manufacturing sites.
Mid-tier precision equipment manufacturer operating four European production plants
- +14%
- Overall equipment effectiveness (OEE)
- -28%
- Production scrap rate
- -34%
- Unplanned machine downtime
- -85%
- Quality logging turnaround
The Challenge
The manufacturer operated multiple fabrication and assembly facilities that relied on disparate industrial protocols and manual shift reporting. Key machine metrics such as cycle times, spindle speeds, and thermal variances were recorded on paper logs or locked inside isolated programmable logic controllers (PLCs), causing a 24-hour lag in operational reporting. Without centralised, real-time visibility into line performance, maintenance teams operated reactively, and quality deviations were often discovered only during downstream testing. This operational opacity resulted in elevated scrap rates, frequent micro-stoppages, and inaccurate production scheduling against core enterprise demand forecasts.
Our Approach
CYVERRA architected an industrial Internet of Things (IIoT) edge-to-cloud data ingestion layer. Edge gateways and protocol translators were deployed across legacy CNC units, stamping presses, and automated testing rigs to capture and standardise operational telemetry via MQTT and OPC UA without disrupting continuous line operations. At the cloud layer, an event-driven architecture processed high-frequency sensor streams through an analytics pipeline integrated with the plant's production execution systems. CYVERRA built live supervisory dashboards and automated condition-monitoring triggers, providing line supervisors with real-time visibility into overall equipment effectiveness (OEE) and calibration anomalies. To close the operational loop, automated digital quality inspection workflows replaced manual clipboards. Operators were equipped with ruggedised tablets connected directly to core manufacturing execution workflows, enabling immediate tagging of defective parts and dynamic job rerouting.
The Outcome
The digital factory implementation established a single source of operational truth across all four production sites. Real-time condition monitoring enabled maintenance teams to shift to predictive service intervals, cutting unplanned machine downtime and extending tooling lifespan. By catching thermal and mechanical drifts early in the production cycle, plant teams dramatically decreased material waste and shortened batch changeover windows, unlocking additional capacity without requiring capital expenditure on new heavy machinery.
Technology used
- AWS IoT Core
- Apache Kafka
- PostgreSQL
- Docker
- Node-RED
- Grafana
- Python
- MQTT
Connecting our shop-floor telemetry to real-time analytics gave our plant supervisors immediate control over line efficiency and product quality across every shift.