CTO
Casa Mendes Gonçalves (Portugal) started its industrial digitalization with fragmented machine data and a largely manual, outsourced setup that made scaling to additional legacy and new equipment difficult. Key challenges were heterogeneous “machine dialects”, unreliable monitoring/alerting, and the lack of a unified view of OT data for operations, quality, and energy management—while keeping costs under control and retaining flexibility for own dashboards. The team implemented an OPC UA–based architecture using Prosys OPC UA Forge as an aggregation server to build a unified namespace, bringing data from multiple systems into one OPC UA server and exposing it to Grafana. Data is collected at one‑minute intervals (≈500 data points/min) to enable dashboards, real-time alerts (e.g., cooling chambers, fermentation temperatures), and remote monitoring via VPN. The setup also supports next steps toward semantic information modeling to improve interoperability and prepare data for AI use cases. For IT/OT decision-makers, the outcome is measurable: faster integration of heterogeneous assets, stable data access for analytics, and cost reductions such as identifying compressed-air leaks worth ~€28k/year—plus a roadmap toward internal GenAI/chatbot solutions based on reliable, contextualized factory data.
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