The Continuous Process Yield Loss Estimator measures the share of continuous-process output that is not accepted as good product during a reporting window. It calculates lost quantity, loss percentage, and good yield from total and accepted output.
The estimator works with any consistent quantity unit, including pieces, kilograms, liters, or meters. It is useful for comparing waste or off-spec loss between shifts, recipes, operating conditions, or time periods. Keep the total-output and good-output boundaries aligned; otherwise the calculated loss may reflect inventory timing or measurement differences rather than true process yield.
1. Select one reporting window
Use a shift, run, day, or other clearly defined period.
2. Enter total output
Use all measured output generated within that boundary.
3. Enter accepted output
Use the portion of that same output that meets your quality definition.
4. Check loss and yield
The tool reports loss percentage and its complement, good yield.
5. Compare like-for-like periods
Use consistent units and acceptance rules when trending the metric over time.
Total process output = gross measured output in the reporting window
Good output = accepted output from the same window
Assumption: Inventory accumulation, recycle loops, and delayed quality release can distort the simple difference if the two quantities are not measured on the same basis.
Use the result as an estimate based on the values and boundaries you entered. Compare like-for-like periods and units when tracking changes.
Actual process results can differ because of downtime, product mix, measurement methods, operating conditions, and quality rules.
Given:
Total process output = 84,000 liters
Accepted good output = 81,900 liters
Calculation:
Loss = 84,000 − 81,900 = 2,100 liters; loss rate = 2,100 ÷ 84,000 × 100 = 2.5%; yield = 97.5%.
Result:
2.50% yield loss
The process has 2,100 liters of non-good output in the selected measurement window.
Count output according to your reporting boundary. If recycled material remains inside the process and is not yet accepted product, do not count it as good final output.
Yield loss can include off-spec product, purge, measurement differences, or other gaps between gross and accepted output, while scrap records may cover only specific disposition codes.
Yes, but only if their measurement and acceptance definitions are comparable. Product-specific quality requirements may make a direct comparison inappropriate.
Align the data periods before calculating. A lag between production and quality release can temporarily make loss look too high or too low.
Good yield is the same basic ratio as OEE quality when both use identical total-output and good-output boundaries.