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03 Produktion — Building block

Try it first, then switch.

What-if on screen — before you touch the real line.

Want to run faster or change a recipe? Try it on the digital twin first. You see what would happen without wasting material or stopping production. Only when it fits does it go to the real line.

Open sourceSelf-hostedDSGVONIS2-ready
DIGITAL_TWIN_SIMULATION

Produktion — Module

digital twin
R Shiny
Python models (scikit-learn)
what-if simulation
DEPLOYMENTSELF-HOSTED · ON-PREM

From everyday work

Test a new setting without risking a single batch

Before the shift tries a faster run, the twin plays it through: yield up, a bottleneck at one station made visible. The station is relieved beforehand — and the real changeover runs smoothly, on the first attempt.

How it fits together technically +

A digital replica of the line is fed from the historical process data and enables what-if scenarios: shift parameters, predict throughput and quality, spot bottlenecks. Interactive models run as browser-based apps — from simple KPI calculators to data-driven prediction models. That turns collected data into a tool for decisions, not just an archive.

Technology used

What it's built on

R Shiny

Turns data into interactive what-if apps in the browser — move a slider, see the result instantly.

Also used by: Widely used in pharma and finance.

scikit-learn

The machine-learning toolbox — spots patterns and predicts outcomes.

Also used by: J.P. Morgan and Spotify build on it.

JupyterLab

The data pro's computational notebook — analysis, charts and explanation in one place.

Also used by: NASA and Netflix use it.

Live demo

Open demo ↗

Pain list → solution

Send us your pain list.

Send pain list → or email: hallo@datendrang.com