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Crate.io > Case Studies > Industry 4.0 at ALPLA
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Industry 4.0 at ALPLA

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).
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 Customer

ALPLA

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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