Additive Manufacturing worked example
Build Batch Capacity at 99% equipment uptime: a worked example
What does the result look like when equipment uptime reaches 99%? The full calculation is worked below with real intermediate numbers. a production planner needs expected batch output for a customer order or weekly AM schedule
The inputs for this scenario
- Parts per build cycle: 60 parts / cycle (unchanged)
- Build cycles available: 8 cycles (unchanged)
- Equipment uptime: 99 % (raised for this scenario; the documented default is 90)
- Accepted print yield: 94 % (unchanged)
Working through the calculation
- Applying the documented formula (Gross batch capacity = parts per cycle × build cycles available) to the inputs above produces each figure below.
- At this operating point the engine returns 447 parts for good batch capacity, the number this scenario is built around.
- At this operating point the engine returns 480 parts for gross batch capacity.
- At this operating point the engine returns 4.8 parts for availability loss.
- At this operating point the engine returns 28.51 parts for rejected part loss.
How this compares with the baseline
- Against the tool's baseline example, where equipment uptime sits at 90% and the headline result is 406 parts, this scenario comes in 10% above the baseline at 447 parts.
- A figure at this level is achievable when equipment uptime is genuinely sustained, not just peaked for a shift. It assumes uniform parts per cycle and constant uptime and yield, so it won't reflect ramp-up cycles or batch-specific defect spikes.
Results at a glance
- Good batch capacity: 447 parts (headline result)
- Gross batch capacity: 480 parts
- Availability loss: 4.8 parts
- Rejected part loss: 28.51 parts
Run it with your numbers
- Every input above is editable in the live Build Batch Capacity calculator, which recalculates instantly and can be shared with the inputs intact.
Last reviewed 2026-05-12.