JERMI Käsewerk in Laupheim, one of Germany's leading manufacturers of processed and sliced cheese products, relies on Transaction-Network to optimize its production lines based on data and prevent downtime in the long term.
The goal is a seamless, AI-powered service and production process: from data analysis through cycle automation to predictive automation - embedded in Transaction-Network's industrial service ecosystem.
Starting Point: Complex Production Lines with High Demands
JERMI Käsewerk operates several highly automated production lines for processed and sliced cheese. The systems must meet the highest quality standards while maximizing production availability.
Unplanned downtime means not only production loss, but also quality losses and high consequential costs.
The central challenge: How can machine data be systematically captured, evaluated, and used for predictive maintenance - without disrupting production?
Solution: Transaction-Network as the Central Platform
JERMI chose Transaction-Network as the central platform to bundle, analyze, and use all relevant machine data for predictive automation.
The project is structured in three phases:
- Phase 1: Data capture and analysis - All relevant sensor data is captured in real time and stored centrally in Transaction-Network.
- Phase 2: Cycle automation - Based on the captured data, production cycles are optimized and automatically adjusted.
- Phase 3: Predictive automation - AI-powered models recognize patterns and enable predictive maintenance before failures occur.
Result: More Transparency, Less Downtime
By using Transaction-Network, JERMI has created a seamless data foundation that not only makes current production transparent, but also forms the basis for predictive maintenance.
The benefits are obvious: fewer unplanned downtimes, higher production availability, and better planning of maintenance work.
- JERMI Käsewerk
Outlook: AI-Powered Optimization as Standard
The project at JERMI shows exemplarily how machine data can not only be captured, but actively used to optimize production processes. Transaction-Network serves as the central platform that bundles all relevant data and makes it available for AI-powered analyses.
The next steps will further expand predictive automation, so that maintenance work can not only be planned, but automatically triggered - an important step toward autonomous production.
From data analysis to fully automated maintenance: JERMI shows what the future of food production looks like.
