Additive Manufacturing worked example

Powder Usage at 63% powder recovery efficiency: a worked example

Suppose powder recovery efficiency falls to 63%. This page works the full calculation at that level so you can see exactly which result moves and by how much. Estimate powder required for SLS, MJF, binder jet, or metal powder bed builds from build quantity, powder per part, and recovery efficiency.

The inputs for this scenario

  • Build quantity: 120 parts (held at the documented default)
  • Powder required per part: 0.06 kg / part (held at the documented default)
  • Powder recovery efficiency: 63 % (the input this scenario stresses; the baseline uses 88)

Working through the calculation

  • The calculation starts from the formula this tool documents: Theoretical powder = build quantity × powder required per part.
  • Powder required works out to 10.48 kg at these inputs, and this is the headline figure for the scenario.
  • Net fused/cake powder works out to 6.6 kg at these inputs.
  • Recovery and handling loss works out to 3.88 kg at these inputs.
  • Powder recovery efficiency works out to 63 % at these inputs.

How this compares with the baseline

  • Against the tool's baseline example, where powder recovery efficiency sits at 88% and the headline result is 7.5 kg, this scenario comes in 39.68% above the baseline at 10.48 kg.
  • It computes theoretical powder (parts times powder per part), then divides by recovery efficiency to give the larger required powder you must actually stage, and splits out net usable mass versus loss. When the numbers land here, the stressed input is the lever to work; the walkthrough above shows exactly how much each output recovers as it climbs back toward the baseline.

Results at a glance

  • Powder required: 10.48 kg (headline result)
  • Net fused/cake powder: 6.6 kg
  • Recovery and handling loss: 3.88 kg
  • Powder recovery efficiency: 63 %

Run it with your numbers

  • To rerun this with your own numbers, open the live Powder Usage calculator, set powder recovery efficiency to your actual value, and adjust the remaining inputs to match your operation.

Last reviewed 2026-05-12.