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First Pass Yield Vs Scrap Rate Calculator

FPY and Scrap Rate Formulas:

\[ FPY = \left( \frac{Good}{Total} \right) \times 100 \] \[ Scrap\ Rate = \left( \frac{Scrap}{Total} \right) \times 100 \]

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1. What is First Pass Yield (FPY)?

First Pass Yield (FPY) is a quality metric that measures the percentage of products manufactured correctly without any rework or scrap the first time through the process. It's a key indicator of manufacturing efficiency and process quality.

2. What is Scrap Rate?

Scrap Rate represents the percentage of manufactured items that cannot be reworked or repaired and must be discarded. It's the inverse of FPY and indicates waste in the production process.

3. How These Metrics Are Calculated

The calculator uses these equations:

\[ FPY = \left( \frac{Good}{Total} \right) \times 100 \] \[ Scrap\ Rate = \left( \frac{Scrap}{Total} \right) \times 100 \]

Where:

Note: FPY + Scrap Rate = 100% when there's no rework. If rework exists, you'll need a separate rework percentage calculation.

4. Using the Calculator

Instructions: Enter the number of good units (passed first inspection) and scrap units (discarded). The calculator will automatically compute FPY, Scrap Rate, and Total Units.

5. Frequently Asked Questions (FAQ)

Q1: What is a good FPY percentage?
A: In most manufacturing, FPY > 95% is good, >98% is excellent. The target varies by industry and product complexity.

Q2: How does FPY differ from traditional yield?
A: Traditional yield includes reworked units, while FPY only counts units that pass inspection the first time.

Q3: Why track both FPY and Scrap Rate?
A: FPY shows process efficiency, while Scrap Rate shows material waste. Together they give a complete picture of quality performance.

Q4: How can we improve FPY?
A: Common strategies include process optimization, better training, improved materials, and mistake-proofing (poka-yoke) techniques.

Q5: Does this calculator account for rework?
A: No, this simple version assumes all non-good units are scrap. For rework calculations, you'd need a more complex formula.

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