Procurement Glossary
First Pass Yield (FPY): Quality indicator for error-free production processes
November 19, 2025
First Pass Yield (FPY) is a key quality indicator that measures the proportion of fault-free products or processes on the first pass. In Procurement , this metric plays a crucial role in supplier evaluation and quality assurance. Find out below how FPY is calculated, what significance this key figure has for procurement and how you can use it to optimize your supplier performance.
Key Facts
- FPY measures the percentage of error-free units on the first production run
- Calculation: (number of fault-free units / total number of units produced) × 100
- High FPY values (>95%) indicate stable production processes and reliable suppliers
- Low FPY values lead to rework, higher costs and delivery delays
- Important key figure for supplier selection and continuous improvement processes
Contents
Definition and meaning of First Pass Yield (FPY)
First pass yield refers to the quality indicator that measures how many products or process steps are successfully completed on the first pass without errors or rework.
Basic aspects of FPY
FPY measures the efficiency of production processes by measuring error-free outputs. The key figure is expressed as a percentage and shows the stability and reliability of production processes.
- Direct measurement of process quality without taking rework into account
- Indicator for the predictability of production results
- Basis for cost calculations and capacity planning
FPY vs. other quality indicators
In contrast to parts per million (PPM), FPY focuses on the first pass quality. While PPM measures defect rates across all production steps, FPY shows the immediate process performance.
Importance of FPY in Procurement
FPY is a decisive indicator for buyers when evaluating suppliers. High FPY values signal stable supply chains and reduce the risk of quality problems and delivery delays.
Measurement and calculation of first pass yield (FPY)
FPY is calculated using a simple formula, but requires precise data collection and clear error definitions.
Basic formula and calculation method
FPY is calculated using the following formula: (number of defect-free units / total number of units produced) × 100. This calculation is made for a defined period or production batch.
- Recording of all units produced in a time window
- Identification and documentation of all errors during the first run
- Exclusion of reworked or repaired units
Data collection and quality criteria
Successful FPY measurement requires clear quality criteria and systematic data collection. The quality standards must be defined and communicated before the start of production.
Implementation in supplier evaluation
Buyers integrate FPY measurements into their supplier scorecards and use this data for contract negotiations and supplier development. Regular FPY reviews enable proactive quality control.
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Interpretation and target values for FPY
The correct interpretation of FPY values requires industry-specific benchmarks and contextual evaluation of the results.
Sector-specific target values
FPY target values vary considerably between different industries. While FPY values of over 99% are expected in the automotive industry, in other sectors 95% can already be considered excellent.
- Automotive industry: >99% for critical components
- Electronics production: 95-98% depending on complexity
- Pharmaceutical production: >99.5% due to regulatory requirements
Trend analysis and development assessment
The development of FPY values over time is often more meaningful than individual measurements. Continuous improvement or deterioration shows the stability and learning ability of suppliers.
Integration in supplier scorecards
FPY should be combined with other key figures such as on-time delivery and cost development. A weighted assessment of various performance indicators enables a holistic supplier evaluation.
Measurement risks and bias with FPY
Various distortions and risks can occur during FPY measurement, leading to incorrect conclusions.
Definition blurring and measurement distortions
Unclear defect definitions lead to inconsistent FPY measurements. Different inspectors can apply different standards, which impairs comparability between suppliers.
- Subjective assessment of borderline cases during quality inspection
- Different interpretations of quality standards
- Temporal fluctuations in the valuation rigor
Gaming and manipulation
Suppliers may be tempted to manipulate FPY values through selective reporting or pre-selection. The complaint rate can serve as a control mechanism to identify such distortions.
Overemphasis on short-term results
Focusing solely on FPY can lead to short-term thinking and neglect long-term improvement investments. A balanced assessment should also consider other metrics such as on-time delivery and innovation capability.
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Practical example
An automotive supplier produces 10,000 brake disks per week. During the final inspection, 150 parts are identified as defective and rejected. The FPY is therefore (9,850 / 10,000) × 100 = 98.5%. This value is below the industry target of 99%, which makes improvement measures necessary.
- Carry out root cause analysis of the 150 defective parts
- Process optimization based on identified weaknesses
- Establish monthly FPY reviews with the supplier
Current developments and effects
Digitalization and the use of artificial intelligence are changing the way FPY is measured and optimized.
Digital transformation of FPY measurement
Modern production systems record FPY data in real time and enable immediate reactions to quality deviations. IoT sensors and automated inspection systems significantly increase measurement accuracy.
- Continuous data acquisition without manual intervention
- Automatic notifications for FPY deviations
- Integration into ERP systems for holistic visibility
AI-supported prediction models
Artificial intelligence analyzes historical FPY data and identifies patterns that lead to quality problems. Predictive analytics enable preventive measures to be taken before faults occur.
Sustainability and FPY optimization
High FPY values reduce material waste and energy consumption due to less rework. Companies use FPY improvements to contribute to their sustainability goals and reduce costs.
Conclusion
First Pass Yield is an indispensable key figure for evaluating production quality and supplier performance. The systematic measurement and analysis of FPY enables proactive quality control and cost optimization. Modern technologies such as AI and IoT significantly expand the possibilities of FPY optimization. Buyers should establish FPY as a central component of their supplier evaluation and continuously develop it further.
FAQ
What is the difference between FPY and Overall Equipment Effectiveness (OEE)?
FPY focuses exclusively on first pass quality, while OEE combines availability, performance and quality. FPY is a component of OEE, but not identical to it.
How often should FPY be measured?
FPY should be measured continuously or at least daily to enable quick reactions to quality problems. Weekly or monthly evaluations are sufficient for strategic decisions.
Can FPY also be used for services?
Yes, FPY can be applied to service processes by measuring error-free service delivery at first contact. Examples include correct invoicing or complete order processing without follow-up questions.
Which measures improve FPY values sustainably?
Sustainable FPY improvement requires systematic root cause analysis, employee training, process standardization and continuous monitoring. Investments in quality assurance systems pay off in the long term.
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