Beverage production digital platform

Facing faster competition and changing demand, a beverage manufacturer wanted a more automated production and management system. They combined EMQ’s manufacturing stack with Azure to improve efficiency, quality, and time-to-market.

Challenges

• Data silos

  Lines used equipment and systems from many vendors, each with its own data format and protocol. Heterogeneous data blocked unified management and analysis.

• Slow response

  Traditional collection and analysis lagged behind the need for real-time monitoring and decisions, which limited how quickly the plant could adjust production.

• Integration

  Connecting many production systems and devices was difficult. Compatibility and interoperability became a bottleneck.

• Weak analytics

  Without better tools, it was hard to extract value from large volumes of production data, which limited intelligent production and predictive maintenance.

• Edge computing

  To improve latency and reduce load on central servers, the plant needed to process data close to the source so critical tasks could run with low delay.

Solution

The manufacturer chose EMQ’s manufacturing solution on Azure. Core pieces:

• EMQX Neuron: industrial edge gateway for multi-protocol collection and edge computing—collect, process, analyze, and forward data from devices and production systems.
• EMQX ECP: industrial data platform for cloud–edge management of Neuron instances, including SSO.
• Azure Event Hubs: cloud message queue for high-throughput streams from the edge.
• Azure Data Factory: managed service for persistence and enterprise analytics.
• Azure Active Directory (AD): identity and access management, integrated with ECP SSO.
• Azure Kubernetes Service (AKS): container platform that simplifies ECP deployment and improves reliability.

Highlights

• Lightweight edge rollout

  Neuron on K3s was deployed to about 50 plants. The model fits limited shop-floor compute while keeping the system observable.

• Broad data collection

  OPC UA pulls data from SCADA. Incremental reads from SQL Server integrate third-party production systems (see SQL source templates).

• Edge compute and real-time analysis

  Preprocessing and analysis at the line standardizes data and reduces load on central systems.

• Reliable transport

  Neuron publishes to Azure Event Hubs with checkpointing so streams stay complete across interruptions.

• Cloud–edge operations

  ECP provides centralized lifecycle management for Neuron at 50 sites: remote configuration, monitoring, and anomaly detection.

• Stronger security

  ECP SSO plus Azure identity improves both security and day-to-day access.

Results

The plant built a data-driven manufacturing platform:

• Connected data: Unified collection, management, and sharing across the factory.
• Live production insight: Key metrics available in time for operators and management to act.
• Lower cost and less downtime: Remote monitoring reduced maintenance cost and unexpected stops.
• Faster response: Digital workflows shortened the path from market change to production change.

Summary

With EMQ, this beverage manufacturer improved efficiency and quality, and gained a live data foundation for further manufacturing platforms. Flexible Neuron deployment plus ECP cloud–edge management supports continued product and process innovation.