Real capacity per machine
What each machine actually produces, in its conditions, with its people and its product — not the theoretical estimate nobody has revisited.
“I plan blind.”
The capacity you plan and the capacity your machines deliver are almost never the same. Planning closes that gap using the real times you're already measuring, run after run.
What each machine actually produces, in its conditions, with its people and its product — not the theoretical estimate nobody has revisited.
The setup that 'takes half an hour' gets timed by the machine. Scheduling with the real number changes how many runs fit in a shift.
The deviation shows up during the shift, not in tomorrow's report. There's still something you can do about it.
When sales asks whether an order fits, the answer comes from demonstrated capacity. You promise less and deliver more.
Planning feeds on the times measured by OEE and DAQ. Without that history it would plan on estimates again, which is exactly the problem it comes to solve.
The usual path is to switch it on once the line has been measuring for weeks: by then real capacity, changeover times and stop causes are data, not perception.
They all run on the same data and the same hardware. Turn on one, turn on six — the bill grows per machine, not per module.
15–20% more productivity
Lines measuring their real capacity before committing it to a customer.
It doesn't compete with it: it feeds it. The MRP plans with standard times someone loaded at some point; Planning contributes the time the machine is demonstrating today, which is usually the outdated input.
You can, but it pays off little at first. Without history it would plan on estimates, which is exactly what it comes to correct. The recommendation is to let the line accumulate weeks of measurement first.
That's where it contributes most. When every product runs at a different rate, the catalogue average lies on every run; the per-product history doesn't.
We install on 1–2 machines, measure your real baseline and present the findings with your own data. Success criteria agreed from day one.