Industrial Automation with AI
Production data lives in MES, ERP and PLCs — but never together. We connect your systems, automate quality inspection and maintenance planning, and make production KPIs usable in real time. GDPR-compliant, on-premise possible, typical ROI under 6 months.
Why Classic Industrial Automation Isn't Enough
Machines are automated. But the processes around them — quality, maintenance, planning — still run on Excel, paper and gut feeling.
Data Silos Between MES, ERP & PLC
Production data from the shop floor, orders from ERP and PLC machine states sit in separate systems — manual reconciliation costs hours every day.
Unplanned Downtime
Machines fail unannounced because wear patterns are not analyzed. Every hour of downtime costs four to five figures.
Manual Quality Control
Spot checks with calipers, Excel sheets for SPC and after-the-fact complaints — no continuous quality flow from goods-in to delivery.
Production Planning in Excel
Shift schedules, material requirements and machine allocation are maintained manually. Changes take hours, bottlenecks are spotted too late.
Compliance & Audit Risks
Missing batch traceability, incomplete documentation and manual inspection records put ISO audits and customer requirements at risk.
Industrial Processes We Automate
From machine data capture to predictive maintenance — we connect your systems and apply AI where it delivers measurable ROI.
MES & ERP Integration
Machine data, orders, master data and inventory flow automatically between MES, ERP and SCADA. One data foundation, no more double entry.
AI-Based Quality Inspection
Computer vision detects surface defects, dimensional deviations and assembly errors in real time. Complaint rate drops, rework disappears.
Predictive Maintenance
Machine data is analyzed for wear patterns. Maintenance is scheduled before failures occur — downtime is cut by up to 50%.
Automated Production Planning
Shift schedules, material requirements and machine allocation are dynamically optimized based on current orders and inventory — including bottleneck detection.
OEE & Shift Reporting
Asset availability, performance and quality (OEE) are captured automatically and analyzed by shift, machine and order — without manual Excel work.
Batch Traceability
End-to-end linking of raw material, batch, machine and finished product. On complaints, the affected batch is identified in seconds.
The ROI of Industrial Automation
Concrete numbers from projects with mid-sized production companies in the DACH region.
How Our Clients Automate Their Production
Predictive Maintenance — Downtime Halved
Problem
A metalworking shop with 12 CNC machines was losing roughly 40 hours per month to unplanned failures. Maintenance ran on fixed intervals, regardless of actual machine condition.
Solution
Vibration, current and temperature data from the spindles is analyzed in real time. An AI model detects wear patterns 5–14 days before failure and schedules maintenance into the next planned stop.
AI Visual Inspection — Scrap Rate From 4.8% to 1.3%
Problem
Injection-molded parts were inspected manually for surface defects. Sample rate was low, defective parts reached customers, complaint rate 2.1%.
Solution
A camera at the end of the line inspects every part with AI vision. Defective parts are auto-rejected, defect types are tracked statistically and fed back into machine control.
Production Planning & Batch Traceability — Audit-Ready
Problem
Shift plans and material requirements lived in Excel. On a complaint, tracing the affected batch took up to two days — a risk in IFS audits.
Solution
Order, material and machine data are merged into one planning system. Every batch is linked from raw material to finished product, audits are reproducible at the press of a button.
Frequently Asked Questions About Industrial Automation
Answers to the most common questions about AI- and IT-driven production automation.
What's the difference between classic industrial automation and AI-driven automation?
Classic industrial automation controls individual machines — PLCs, robots, drives. AI-driven industrial automation sits on top: it connects data from MES, ERP, SCADA and PLCs, detects patterns (e.g. wear signals, quality deviations) and automates decisions previously made manually — maintenance planning, quality release, production planning. It does not replace the machine, but the manual process around it.
What prerequisites do I need for AI-driven industrial automation?
At minimum: digitally captured machine data (OPC UA, Modbus, MQTT or comparable interfaces) and an ERP or MES system reachable via API. Where interfaces are missing, we retrofit sensors or edge gateways. A complete Industry 4.0 landscape is not required — we start with the process with the highest ROI and expand step by step.
Is this GDPR-compliant and can it run on-premise?
Yes. Production data often contains trade secrets or personal data (e.g. shift assignments). On request, the AI models run entirely on-premise or in a private cloud with German server location. Data flows are documented, access is role-based, GoBD and ISO 27001 requirements are met.
How long does implementation take?
A first productive process (e.g. AI quality inspection on one line or predictive maintenance on one machine group) is typically live in 8–12 weeks. Full integration of MES, ERP and multiple assets takes 4–9 months depending on scope. We always start with the highest-leverage process — no big-bang project.
What does AI-driven industrial automation cost?
Entry projects (e.g. predictive maintenance for one machine group or vision inspection on one line) start at €12,000–25,000 one-off plus ongoing operations. Larger integration projects range from €3,500–8,000/month. In a free AI audit, we analyze your production and show concrete savings potential — including ROI based on your downtime cost and scrap rate.
Ready to Automate Your Production?
In a free AI audit, we analyze your production processes and show you where the biggest leverage lies — with concrete numbers from your plant.
Book Free AI Audit