Data Science × Manufacturing

Your machines know more
than your reporting shows

6 modules. 6 problems every manufacturer knows. 6 data-driven solutions that turn the data you already have – MES, ERP/SAP, sensor & SCADA data, production planning and inspection data – into measurable savings. No external data, no new hardware.

Calculated savings potential per year
€0
Model calculation for a sample plant with 48 machines · conservatively estimated
At a glance

Numbers you can trace back

Based on a mid-sized manufacturer: €85M revenue, 320 employees, 48 machines in 3-shift operation. Every figure is derived from the documented assumptions.

6
Modules
48
Machines in the sample plant
€2,911,000
Savings potential/year
4 wks
Pilot timeframe
The 6 modules

Each module solves a concrete problem

Click a module for the full analysis with visualisations, transparent model calculation and business impact.

Module 01
Predictive Maintenance
Survival models and LSTM detect machine failure before it happens – from sensor and maintenance history. Reduces unplanned downtime cost.
€921,600
Savings / year
SurvivalLSTM
Module 02
Scrap & Quality Forecast
Gradient boosting detects from batch, parameters and inspection data which production leads to scrap – lowers material and rework cost.
€419,000
Savings / year
Gradient BoostingXGBoost
Module 03
OEE & Bottleneck Optimisation
Process mining exposes setup times, cycle losses and bottlenecks. Capacity gained without investment – from MES and PPS data.
€604,800
Capacity value / year
Process MiningOptimierung
Module 04
Energy & Load Optimisation
Time-series models forecast consumption per machine and shift and smooth load peaks – cuts energy cost and peak-demand charges.
€312,000
Savings / year
ZeitreihenRegression
Module 05
Demand & Production Planning
Forecasting reduces over- and underproduction and tied-up stock. Less working capital, fewer rush orders – from ERP and PPS history.
€294,000
Savings / year
ForecastingGradient Boosting
Module 06
On-Time Delivery Forecast
Classification and survival models flag early which orders will be late – avoids contract penalties and protects customer relationships.
€360,000
Savings / year
KlassifikationSurvival
Savings potential by module – overview
Our approach

No theory - results in weeks

We work with the data you already have. No vendor lock-in, no cloud mandate, no hidden costs.

🏭
Industry knowledge + data science
We understand maintenance, scrap and shift operation. Our models solve real manufacturing problems – GDPR-compliant and on your infrastructure.
⚡
Results before perfection
We deliver a pilot dashboard with real numbers from your data. No 6-month concept - you see the ROI before you invest.
🔒
Your data, your systems
MES, ERP/SAP, sensor & SCADA data, PPS, quality and inspection data – we connect what already arises in your plant. No new system, no external data.
Note on the context of this portfolio

The following six modules use a fictitious mid-sized manufacturer (48 machines, 3-shift operation, €85M revenue) to show how data science can be applied across production – from predictive maintenance to on-time delivery.

All euro figures are model calculations. They are derived transparently from clearly named assumptions (assumption baseline → lever → result) and serve only to illustrate the order of magnitude of the achievable impact – no promises.

In a real project, the domain expertise of your plant is the decisive factor: How are your machines connected? What data sits in MES, ERP and the control system? Where do the biggest losses occur – downtime, scrap or energy? On that basis we build models that fit your reality.

This portfolio shows which questions data science can answer in manufacturing – the concrete answers emerge only with your data.

Ready to put your data to work?

We work with the data you already have. No vendor lock-in, no cloud mandate, no hidden costs.

Schedule a data workshop →