Most robotics business cases are written to pass the approval. Few are written to hold.
The standard calculation compares a robot against a shift of labour and stops there. It leaves out the gripper development, the fixtures, the safety assessment, the weeks of commissioning during which the line runs worse, and the changeover time that eats into the gain at small batch sizes.
We put those in the model before you decide, because a cell that pays back on paper and never on the shop floor damages the case for the next one too.
From feasibility to a cell that still runs in year three.
Feasibility and simulation
We simulate the cell against your real part mix and cycle times before anyone quotes hardware. Digital twins are cheap; discovering that the gripper cannot handle variant seven is not.
Vision and bin picking
Machine vision for quality inspection and for picking parts out of unstructured bins. This is where AI has changed what is possible, and where many new cases come from.
Cobots and safe collaboration
Where the cell shares space with people, the safety assessment shapes the layout from the first sketch. Speed and separation monitoring done properly is what keeps the cycle time you budgeted for.
Retrofit before replacement
Older machines can often be instrumented, integrated and kept. Sensors, an edge box and a connection into the planning system frequently deliver more per euro than a new asset does.
Foundation models moved the line between programmed and taught.
Classic industrial robotics needs the world to hold still: fixed positions, fixed parts, fixed lighting. Every deviation is a programming task. Vision models trained on physical interaction shift part of that burden from programming to demonstration, which is what makes small batch sizes viable at all.
This is genuinely new and it is also over-promised. Humanoids are not going to run your line next year. Bin picking on an unsorted tote, quality inspection with a part mix that changes weekly, and a cell that recovers from a fault without an engineer walking over: those work now, and they are worth building.
Questions
What batch size does a robot start making sense at?
There is no single number, which is why we simulate. Roughly: at low volumes per variant, changeover dominates and the case depends on how much of it can be automated. Above that, the classic calculations start to hold.
Buy or lease?
Lease or robotics-as-a-service is usually right for a first cell, because it converts a capital decision into an operating one and the internal argument is easier. Buying wins once you are on your third cell and the team can maintain them.
Do you supply the hardware?
We are vendor-neutral and integrate what fits the case. We have no reseller margin to protect, which is the reason we can tell you a cell does not pay off.
Can you work on a site outside Germany?
For robotics, physical proximity matters more than it does for software. We take UK and Benelux sites; further afield we work with a local integrator and own the AI and simulation side.
Bring us the part and the volume.
With a drawing, a part mix and a cycle time we can tell you within a call whether this is a cell, a retrofit, or a case to revisit later.
From bottleneck to a measured number, on your own data.
Tell us the process that eats your time. We build on your real data, measure with the method agreed before the start, and if the numbers do not carry it, we say so.
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