Wearable Medical Sensors worked example

Capacity Gap at 65% expected equipment uptime: a worked example in wearable medical sensors

This worked example runs the capacity gap numbers for a tougher week than the baseline: 65% expected equipment uptime instead of the typical 90%. Estimate capacity gap for wearable medical sensors using production-ready inputs so teams can confirm whether capacity can cover demand before committing the schedule.

The inputs for this scenario

  • Sensor units built per cycle: 4 units / cycle (held at the documented default)
  • Available production cycles in the window: 480 cycles (held at the documented default)
  • Expected equipment uptime: 65 % (the input this scenario stresses; the baseline uses 90)
  • Expected first-pass yield: 97 % (held at the documented default)

Working through the calculation

  • The calculation starts from the formula this tool documents: Gross capacity gap capacity = capacity gap output per cycle × available capacity gap cycles.
  • Good capacity gap capacity works out to 1,211 units at these inputs, and this is the headline figure for the scenario.
  • Gross capacity gap capacity works out to 1,920 units at these inputs.
  • Capacity gap downtime loss works out to 672 units at these inputs.
  • Capacity gap yield loss works out to 37.44 units at these inputs.

How this compares with the baseline

  • Against the tool's baseline example, where expected equipment uptime sits at 90% and the headline result is 1,676 units, this scenario comes in 27.78% below the baseline at 1,211 units.
  • Use it during capacity planning, order acceptance, or line balancing to check whether real deliverable output covers a demand commitment. A result at this level usually justifies acting on the stressed input before touching anything else, because every other figure in the table is downstream of it.

Results at a glance

  • Good capacity gap capacity: 1,211 units (headline result)
  • Gross capacity gap capacity: 1,920 units
  • Capacity gap downtime loss: 672 units
  • Capacity gap yield loss: 37.44 units

Run it with your numbers

  • To rerun this with your own numbers, open the live Capacity Gap calculator, set expected equipment uptime to your actual value, and adjust the remaining inputs to match your operation.

Last reviewed 2026-05-12.