Crate.io > Case Studies > Industry 4.0 at ALPLA

Industry 4.0 at ALPLA

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Technology Category
  • Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
  • Packaging
Applicable Functions
  • Business Operation
Use Cases
  • Factory Operations Visibility & Intelligence
Services
  • Data Science Services
The Challenge

As the complexity of production machinery increases, so does the need for highly-trained specialists in each factory. This creates the following challenges:

  1. Higher personnel costs in every plant
  2. Harder to recruit experienced talent at each location
  3. Personnel turnover becomes more costly
  4. Less experienced operators run the machines sub-optimally, impacting resource consumption and overall equipment effectiveness (OEE).
The Customer
About The Customer

ALPLA is a world leader in the area of packaging solutions, producing high-quality packaging for Coca-Cola, Unilever, and other brands in the food, drinks, cosmetics, and cleaning industries. ALPLA employs 20,900 employees at 181 locations across 46 countries.

The Solution

The switch to Crate IoT Data Platform: 250x faster...

After learning about the Crate IoT Data Platform, they decided to migrate the project to Crate. Powered by CrateDB, the Crate IoT Data Platform is purpose-built for IoT workloads like ALPLA’s, and it was attractive for the following reasons:

  1. SQL: Easy to migrate data and code to Crate IoT Data Platform from SQL Server
  2. Distributed: Easy and economical to scale on elastic clusters of inexpensive servers
  3. Dynamic schema: Allowed ALPLA to combine all their 900 different sensor readings into a single table for easier maintenance and faster querying
  4. Real-time performance: Columnar indexes cached in me­mory enable the Crate IoT Data Platform to execute dashboards queries 250x faster than SQL Server (in milliseconds, not minutes).
Operational Impact
  • [Cost Reduction - Labor]

    Lower personnel costs by requiring fewer experts

  • [Data Management - Data Analysis]
    • Perform cross-plant analysis to get new insights.
    • Get immediate insight and control instead of next-day quality reporting.

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