Should FPY be based on samples or full counts?

Prefer full counts from MES/WMS. If sampling is necessary, use governed plans and account for sampling error in interpretation.

Can yield improve without new equipment?

Yes. Address top defect modes, stabilize variation with SPC, improve incoming quality, and add mistake-proofing to lift FPY and free capacity.

How do laboratories affect yield?

Lab pass/fail decisions can be bottlenecks and error sources. Validate methods (TMV), assure gage fidelity (MSA), and integrate results for timely disposition.

Is scrap allowed to re-enter production?

Only via an approved, controlled rework route authorized by MRB; otherwise scrap must be blocked from re-entry and tracked to disposition.

Yield – First-Pass & Final YieldGlossary

Yield – First‑Pass & Final Yield

Q: What’s the difference between FPY and Final Yield?

FPY counts first-time goods only, with no rework; Final Yield includes successful reworked units. Tracking both avoids masking waste.

Q: How is RTY calculated?

Rolled Throughput Yield is the product of step-level FPYs across the route: RTY = Π(FPY_step). It reflects the chance of passing end-to-end with no rework.

This topic is part of the SG Systems Global regulatory & operations glossary.

Updated October 2025 • Throughput, FPY/RTY & Scrap • Quality, Manufacturing, Finance

Yield expresses how much product emerges conforming versus what entered the process. First‑Pass Yield (FPY) is the fraction that meets requirements without any rework. Final Yield (sometimes called “throughput yield”) counts conforming units after permitted rework is applied. For multi‑step flows, Rolled Throughput Yield (RTY) multiplies step‑level FPYs to reveal the hidden factory cost of small losses at each stage. Clear counting rules, trustworthy measurement, and governed records are essential so yield drives improvement rather than becoming an accounting artifact.

“If FPY shows how clean your process is today, RTY shows how expensive yesterday’s dirt has become.”

TL;DR: Define yield consistently: FPY = first‑time good ÷ total processed; Final Yield = good after rework ÷ total started; RTY = Π(FPY_step). Track rework and scrap explicitly in MES, gate nonconforming material through MRB, and stabilize variation with SPC and capable processes (Cpk). Reconcile to Yield Variance (Plan vs Actual) for financial impact.

1) What Yield Covers—and What It Does Not

Covers: proportions of conforming output at defined boundaries (operation, line, or value stream); effects of rework loops and scrap; cumulative loss across stages (RTY). Yield is a process measure that ties to quality cost and capacity.

Does not cover: speed or uptime (that’s OEE), product mix economics, or tolerance to spec drift. A high final yield can hide excessive rework; FPY and RTY expose it.

2) System & Data Integrity Anchors

Counting must be governed under Document Control: define the unit of measure, step boundaries, good/nonconforming states, and rework allowances. Measurements and results flow through validated systems (CSV), with attributable users and immutable audit trails. If lab results gate yield, ensure method capability via TMV and MSA.

3) The Evidence Pack for Yield Reporting

Maintain a reconstructable trail: production orders and quantities started, scrap by reason code, rework tickets with pass/fail outcomes, inspection/test records, MRB/NCMR decisions, disposition in Lot Release, and inventory movements in WMS. Calculations (FPY, Final Yield, RTY) should be parameterized and version‑controlled so a past month can be re‑computed identically.

4) From Data Capture to Improvement—A Standard Path

Capture pass/fail at each key operation; segment defects by code; send nonconforming units to NCMR/MRB; execute approved rework in controlled routes; compute FPY per step and RTY across the flow; correlate losses with PFMEA and the Control Plan; fix causes with RCA/CAPA; then verify gains with stabilized SPC baselines.

5) Interpreting FPY, Final Yield & RTY

FPY reflects process cleanliness and operator/machine capability without fixes. Final Yield reflects the net that ships after allowed rework; it’s appropriate for promise‑to‑ship but can mask waste. RTY exposes cumulative loss: even modest step FPY (e.g., 0.95 across 6 steps) yields 0.95⁶ ≈ 74%—a powerful case for preventing defects near the source.

6) Counting Rules That Avoid Confusion

Define the denominator (“started” vs “processed”), count each physical unit once per step, and treat a unit that loops through rework as one unit with a rework event—not multiple new units. Do not include reworked failures in FPY numerators; include successful reworks in Final Yield. Align sampling inspection with accepted plans (Sampling) and ensure the lab’s pass/fail criteria are version‑locked in SOPs.

7) Rework, Scrap & Hidden Factory

Rework consumes capacity and introduces risk. Track rework rate, time, and yield of rework itself; route recurring rework through RCA/CAPA; escalate suppliers via SCAR if incoming defects drive losses. Scrap must be physically and system‑blocked from re‑entry and dispositioned under MRB rules.

8) Yield vs OEE, Throughput & Cost

Yield affects OEE’s “quality” component but is not the same as uptime or rate. Improving FPY/RTY often releases capacity without new equipment and lowers Cost of Poor Quality (COPQ). Link yield deltas to KPIs and to Yield Variance to show financial impact of technical fixes.

9) Stabilizing Yield with SPC & Capability

Use control charts (e.g., X‑bar/R, I‑MR) to detect drift before defects accrue. Target capable processes (Cpk), quantify variation (σ), and use alert/action limits that trigger intervention ahead of spec limits.

10) People, Methods & Equipment

Yield depends on capable methods (validated via TMV), trained people (Training Matrix), mistake‑proofing (poka‑yoke), and fit‑for‑use assets (IQ/OQ/PQ, TPM). Visual inspection benefits from machine vision to cut subjectivity.

11) Supplier & Incoming Quality Effects

Upstream defects depress FPY immediately. Strengthen Supplier Qualification, apply Incoming Inspection based on risk, reconcile CoA, and feed defects to SCARs. Where identity errors drive scrap, enforce label verification and serialization.

12) Deviation Handling Without Diluting Yield

When yield drops or escapes occur, open a Deviation/NC, perform RCA, decide fate at MRB, and implement CAPA. Do not “improve” yield by redefining counts; improve the process and lock changes through MOC.

13) Metrics That Demonstrate Control

FPY by step and RTY across the value stream.
Rework rate and rework FPY (success of rework routes).
Scrap rate by reason code and supplier attribution.
Cpk vs Ppk on yield‑critical characteristics; OOC rate on SPC charts.
Yield variance (plan vs actual) and COPQ trend linked to actions.

Together these show whether improvements are structural (less rework/scrap) or cosmetic (counting changes).

14) Common Pitfalls & How to Avoid Them

Counting reworked units as first‑pass good. Separate FPY from Final Yield; compute RTY.
Shifting boundaries. Lock step definitions and denominators in SOPs.
Weak measurement. Validate methods (TMV) and gages (MSA) to avoid false rejects/accepts.
Overreliance on inspection. Prevent with poka‑yoke and SPC.
Supplier blind spots. Tie incoming defects to SCARs and purchasing leverage.
Spreadsheet drift. Calculate in validated systems with audit trails.

15) What Belongs in the Yield Record

Product/route IDs; step boundaries; quantities started/processed/scrapped; FPY per step, Final Yield for lot, RTY across the route; defect and rework codes; MRB/CAPA links; governing SOP versions; and references to SPC/capability reports. Store under controlled records and tie to traceability so results are reconstructable.

16) How This Fits with V5 by SG Systems Global

Execution & counting discipline. The V5 platform records pass/fail at each operation in the V5 MES, enforces step boundaries and rework permissions via controlled routings, and blocks unauthorized re‑entries. FPY, Final Yield, and RTY are computed from the same source events with effective‑dated logic to preserve history.

Quality workflow integration. Nonconforming units auto‑open V5 QMS records (NCMR/MRB) and, where patterns emerge, escalate to CAPA. Root causes link to PFMEA and update the Control Plan under Document Control.

SPC & capability backbone. V5 charts critical characteristics (SPC, X‑bar/R), computes Cpk, and issues alert/action notifications before yield collapses, tying signals to deviations and containment.

WMS & financial alignment. The V5 WMS governs scrap/quarantine movements and prevents shipment of nonconforming stock. Yield dashboards reconcile to Yield Variance and COPQ, making technical improvements visible to finance and planning.

Bottom line: V5 makes yield trustworthy and actionable—clean counting, integrated quality workflows, real‑time SPC, and inventory control that together move FPY up and rework down.

17) FAQ

Q1. What’s the difference between FPY and Final Yield?
FPY counts only first‑time goods with no rework; Final Yield includes successful reworked units. Track both to avoid hiding waste.

Q2. How is RTY calculated?
Multiply the FPY of each step in the route: RTY = Π(FPY_step). It reflects the chance of a unit passing the entire process without any rework.

Q3. Should I compute FPY on samples or full counts?
Prefer full counts from MES/WMS events. If sampling is used, follow governed plans and account for sampling error in interpretation.

Q4. Can we improve yield without new equipment?
Often yes—fix top defect modes, stabilize variation with SPC, strengthen incoming quality, and deploy poka‑yoke; these usually lift FPY and free capacity.

Q5. How do labs affect yield?
Lab pass/fail can be a bottleneck. Validate methods (TMV), assure gage fidelity (MSA), and integrate LIMS results so disposition is timely and defensible.

Q6. Is scrap ever allowed to re‑enter?
Only via a controlled rework route approved by MRB; otherwise scrap must be system‑blocked from re‑entry and traced to final disposition.