Fiber Optic Cable & Photonic Interconnects worked example

Fiber Draw Yield at 99% target fiber draw yield: a worked example

This scenario runs the fiber draw yield calculation on the strong side: 99% target fiber draw yield, with every other input held at its documented default. Use it when a fiber draw tower, proof-test line, or cable preform run needs a clear yield number for scrap, capacity, or cost review.

The inputs for this scenario

  • Accepted drawn fiber length: 238,000 m, km, or ft (unchanged)
  • Started draw length: 250,000 m, km, or ft (unchanged)
  • Target fiber draw yield: 99 % (raised for this scenario; the documented default is 96)

Working through the calculation

  • Applying the documented formula (Fiber draw yield = accepted drawn fiber length รท started draw length) to the inputs above produces each figure below.
  • At this operating point the engine returns 95.2 % for fiber draw yield, the number this scenario is built around.
  • At this operating point the engine returns 3.8 points for gap to draw-yield target.
  • At this operating point the engine returns 238,000 m, km, or ft for accepted drawn fiber length.
  • At this operating point the engine returns 250,000 m, km, or ft for started draw length.

How this compares with the baseline

  • Against the tool's baseline example, where target fiber draw yield sits at 96% and the headline result is 95.2 %, this scenario lands almost exactly on the baseline at 95.2 %.
  • Use it after each draw campaign or shift to reconcile proof-tested good length against the length actually pulled from the preform. Treat this as a target state: the delta against the baseline quantifies what the improvement is worth before you commit to chasing it.

Results at a glance

  • Fiber draw yield: 95.2 % (headline result)
  • Gap to draw-yield target: 3.8 points
  • Accepted drawn fiber length: 238,000 m, km, or ft
  • Started draw length: 250,000 m, km, or ft

Run it with your numbers

  • Every input above is editable in the live Fiber Draw Yield calculator, which recalculates instantly and can be shared with the inputs intact.

Last reviewed 2026-05-12.