In the Food and Beverage manufacturing industry, scaling digital transformation across multiple plants often hits a major roadblock: the lack of uniformity among industrial devices. One global producer of natural ingredients with over 9000 team members was no exception.
To build a flexible and future ready production ecosystem, they chose a digital first approach. They achieved this by building a complete Industrial DataOps infrastructure paired with Edge technology.
1. The Practical Operational Challenges
Like many large scale manufacturing companies, they faced three core issues:
- Fragmented operational environments: Their global plants had different levels of technological maturity, using a wide variety of machinery and industrial platforms.
- Rising cloud costs: Sending massive amounts of raw data directly to the cloud led to soaring storage and processing expenses.
- Sustainability goals: They are committed to optimizing water and energy resources, which requires real time monitoring and deep analysis.
2. Deploying a Unified Data Infrastructure
Instead of rolling out isolated software tools, they embraced an edge computing platform to completely resolve connectivity and data collection right at the source.
- Exceptional deployment speed: Thanks to hundreds of built in industrial communication drivers, connecting with shop floor devices was established in just minutes. Through automated processes, they successfully connected a diverse fleet of equipment across multiple plants within just three months of starting the project. This brought everything under one common data infrastructure.
- Centralized management: The entire global scaling and operational process is easily synchronized through a central manager.
3. Remarkable Data Driven Breakthroughs
Shifting the mindset from just utilizing individual products to building a comprehensive solution architecture brought them highly measurable results:
3.1. Standardizing OEE and Establishing a Common Namespace
Overall Equipment Effectiveness is a vital metric for the supply chain. However, to accurately calculate OEE globally, the data must be completely reliable. The new system helped standardize and contextualize data right at the edge before sending it to the cloud. Notably, the platform achieved a 90% data compression rate. This drastically cut cloud costs while keeping a unified namespace structure across all facilities.
3.2. Optimizing Energy Consumption
The new infrastructure allowed them to apply a dynamic energy monitoring strategy. Anomaly detection and data models at the edge helped experts immediately spot optimization opportunities. Impressively, they realized actual energy savings within just a few days of system use.
4. The Takeaway
Their story proves a great point: Factory digital transformation does not start with blindly pushing all data to the cloud. It begins with building a smart edge data infrastructure.
By collecting, standardizing, and compressing data right on the factory floor, manufacturers gain a reliable overview of OEE while mastering global cost and energy optimization. This approach aligns perfectly with the core vision of our upcoming Digitalization Drive this June, helping factories transition smoothly toward true digital efficiency.
If you want to see more case studies in the F&B industry, please click here.
