Introduction
Thomas Heidemann distrusted the first collaborative robot because it moved too smoothly. In the workshop, smoothness can be useful; it can also hide danger. He watched the arm stop beside a workpiece and asked where the person was supposed to stand when something went wrong.
Thomas lives in Essen and trains companies introducing AI-supported robotics into assembly and quality inspection. He brings four decades of workshop knowledge to rooms full of screens.
Story of the Path into AI
When his company introduced a cobot, Thomas saw young engineers understand the machine and miss the rhythm of the shop floor. Colleagues feared job loss; management spoke too optimistically. Thomas started mediating because nobody else had enough trust on both sides.
He learned robot control, safety zones and machine vision by testing them on real workpieces. His first training session had workers provoke robot errors and derive safety rules from them. The exercise was messy. A camera misread a reflection, a tool was placed where the plan said it never would be, and someone asked the question that mattered: who notices first?
Thomas realized that acceptance does not begin with a presentation. It begins when experienced workers are allowed to make the machine fail under controlled conditions.
Current Work
Today Thomas trains teams in assembly halls and smaller factories. In one exercise he shows how lighting can confuse a vision system. Then the group decides which checks can be automatic and which must stay manual.
The practical result is rising acceptance of new systems because workers are not merely instructed; they are involved. Thomas is not against automation. He is against systems introduced as if the old knowledge in the room had already expired.
Personal Advice
“Experience is not an obstacle to AI. It is the test bench,” Thomas says. He advises companies to let skilled workers challenge the system before it reaches production. If the robot cannot survive their questions, it is not ready.
Key Facts
Age and place: 63, Essen.
Background: manual trade, later training, bridge between generations.
Entry into AI: safety training in which workers provoke robot errors.
Focus today: industrial robotics and occupational safety.
Typical tools: collaborative robots, computer vision, safety training.
Werkstattnotiz
Thomas keeps a scratched test piece from a failed demonstration. The mark is small, but it ended a long argument about “unlikely” situations. He now begins sessions by placing it on the table. It saves twenty minutes of theory about edge cases.