Industrial automation

Industrial automation with AI

Production data lives in MES, ERP and PLCs — but not together. We connect your systems, automate quality inspection and maintenance planning, and make production KPIs usable in real time. GDPR-compliant, on-premise possible, ROI typically under 6 months.

The problem

Why classic industrial automation is not 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 the ERP and machine states from the PLC sit in separate systems — manual reconciliation costs hours every day.

Unplanned downtime

Machines fail unannounced because wear patterns are not analysed. Every hour of downtime quickly costs four to five figures.

Manual quality control

Spot checks with callipers, Excel lists 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 and audit risks

Missing batch traceability, incomplete documentation and manual inspection records put ISO audits and customer requirements at risk.

Our solution

The 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-powered 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 analysed for wear patterns. Maintenance is scheduled before failures occur — instead of reacting after the standstill.

Automated production planning

Shift schedules, material requirements and machine allocation are dynamically optimised based on current orders and inventory — including bottleneck detection.

OEE & shift reporting

Asset availability, performance and quality (OEE) are captured automatically and analysed by shift, machine and order — without manual Excel work.

Batch tracking & traceability

End-to-end linking of raw material, batch, machine and finished product. On complaints, the affected batch is identified in seconds.

Measurable results

The ROI of industrial automation

Typical orders of magnitude from automation projects in mid-sized manufacturing — we calculate your concrete potential in the free AI audit.

up to
50%
fewer unplanned stops
through predictive maintenance
up to
70%
less scrap
through AI quality inspection
up to
+15%
higher OEE
through real-time planning
typical
< 6 mo.
return on investment
typical payback period
Example scenarios

How manufacturers automate maintenance, quality and planning

Three illustrative scenarios of how AI-powered industrial automation works in practice — as example calculations with typical orders of magnitude.

Example scenario · Metalworking

Predictive maintenance — downtime halved

Problem

A metalworking shop with 12 CNC machines loses around 40 hours per month to unplanned failures. Maintenance runs on fixed intervals, regardless of actual machine condition.

Solution

Vibration, current and temperature data from the spindles is analysed in real time. An AI model detects wear patterns days before failure and schedules maintenance into the next planned stop.

Result

Roughly half as many stopsMarkedly lower maintenance costsROI within a few months
Example scenario · Plastic parts production

AI visual inspection — scrap rate markedly reduced

Problem

Injection-moulded parts are inspected manually for surface defects. The sample rate is low, defective parts reach customers, the complaint rate rises.

Solution

A camera at the end of the line inspects every part with AI vision. Defective parts are rejected automatically, defect types are tracked statistically and fed back to the machine control.

Result

Scrap rate markedly reducedFewer complaints100% instead of sample-based inspection rate
Example scenario · Food manufacturer

Production planning & batch traceability — audit-ready

Problem

Shift plans and material requirements are kept in Excel. On a complaint, tracing the affected batch takes 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 become reproducible at the press of a button.

Result

Batch trace in seconds instead of daysAudit-ready documentationSeveral hours of planning time saved per week

Illustrative example calculations with typical orders of magnitude — not measured values from individual clients.

FAQ

Frequently asked questions about industrial automation

Answers to the most important questions about AI- and IT-driven production automation.

Classic industrial automation controls individual machines — PLCs, robots, drives. AI-powered 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 that were previously made manually — maintenance planning, quality release, production planning. It does not replace the machine, but the manual process around it.

Free AI audit

Ready to automate your production?

In the free AI audit, we analyse your production processes and show you where the biggest lever lies — with concrete figures from your plant.

30 minutes · no obligation · reply within 24 h