Electronics Repair Depot KPIs: Benchmark Ranges for Yield, NFF, Turnaround and More

An electronics repair depot runs on a handful of linked KPIs, and a gain in one can quietly cost another. Use the ranges below as reference points for spotting a gap worth investigating, not as targets, and compare against your own trend first.

Every figure here shows its basis. A superscript number links to a public source in the Sources list at the end, and the sentence states which returns that source studied. A figure marked no cited source is kept exactly as originally published because no public source stating it has been found, so treat it as illustrative.

At a glance

First-pass repair yield

First-pass repair yield is the headline KPI: the share of units repaired correctly on the first bench visit. Typical depots run 78 to 86 percent no cited source, competent operations hit 88 to 92 percent no cited source, and world-class board-level shops reach 93 to 96 percent no cited source.

Below 80 percent, second passes eat capacity and every other metric degrades no cited source. A single low-yield model can hide inside a healthy average, so never read the blended figure alone.

How to measure

• Divide units that pass verification after one bench visit by units repaired.
• Report it weekly per product family, not blended.
• Compare each week against a rolling four-week baseline.

What moves it

• Diagnostic accuracy, so more failures reach the correct root cause on the first visit.
• Splitting results by product family, so a weak model gets attention early.

Track it with the First-Pass Repair Yield calculator, and price the bench time behind it with the Diagnostic Labor Cost calculator.

No-fault-found rate

No-fault-found (NFF) rate is the KPI most operations underestimate: the share of returned units in which no reproducible defect is found. Typical NFF sits at 8 to 15 percent no cited source, good depots hold 5 to 8 percent no cited source, and best-in-class screening keeps it under 5 percent no cited source.

Published studies of particular return streams report far higher rates. An IPC technical paper by Louis Ungar cites a 2005 UK survey in which 63 percent of returned mobile phones had no fault¹, and a study of automotive cruise-control modules returned on customer complaints in which 96 percent operated properly and passed the bench test².

False alarms are one driver. The same paper reports that on F/A-18 A/B/C/D aircraft, 75 percent of cannot-duplicate events resulted from false alarms, and its modeled example shows that with 3 percent of units truly faulty, 95 percent detection and a 10 percent false-call rate, 77 percent of units sent to the depot are fault-free³.

High NFF means diagnostic labor is going to units with no reproducible defect, often because test coverage or soak duration is too shallow. Watch for NFF that spikes right after a new product launch, a classic sign of premature returns.

How to measure

• Divide units closed as no fault found by units received for repair.
• Split it by product, by customer and by return reason.
• Mark product launches on the trend so a spike after a launch stands out.

What moves it

• A standardized, time-boxed screen with enough test coverage and soak time.
• Better field return criteria upstream.
• Fewer false alarms from built-in test in the field.

Put a cost on the diagnostic hours NFF consumes with the Diagnostic Labor Cost calculator.

Turnaround time and queue

Turnaround time (TAT) is what customers actually feel. Consumer electronics depots target 3 to 5 business days end to end no cited source, and industrial and medical work often allows 7 to 15 days given burn-in requirements no cited source. World-class flow keeps queue wait under one day no cited source.

Most of that time is waiting: 50 to 70 percent of TAT is usually idle queue, not touch time no cited source. Little's Law rewards lower queue over faster hands, because average time in the depot equals units on the floor divided by throughput.

How to measure

• Measure TAT from receipt to shipment in business days.
• Split each unit's time into queue time and touch time.
• Count units in work in progress on the floor every day.

What moves it

• A cap on units in work in progress, which cuts TAT without adding a technician.
• Fewer second passes, since each one sends a unit back through the queue.

See how queue depth turns into wait with the RMA Queue Lead Time calculator.

Repeat repair rate

Repeat repair rate, sometimes called re-return or bounce rate, measures durable quality. Typical is 6 to 10 percent within 90 days no cited source, strong depots hold 3 to 5 percent no cited source, and world-class stays under 3 percent no cited source.

Every repeat is a full second repair cost with lost customer trust attached. One avoided bounce pays for many extra soak hours, so extra verification is worth a small throughput cost.

How to measure

• Count units that come back within 90 days of shipment.
• Group them by ship-date cohort, not calendar month, so a bad batch shows cleanly.

What moves it

• Longer burn-in dwell on high-bounce models.
• Added functional test coverage on high-bounce models.

Check what longer dwell costs in chamber capacity with the Burn-In Test Capacity calculator.

Burn-in chamber utilization

Burn-in utilization tells you whether expensive chambers earn their keep. Typical utilization runs 45 to 65 percent no cited source, well-run depots hit 70 to 85 percent no cited source, and pushing past 90 percent risks queue backup ahead of the chamber no cited source.

Low utilization usually means load and unload scheduling, not slot count, is the constraint. A chamber that runs half empty overnight doubles its fixed cost per unit for that run.

How to measure

• Divide occupied slot-hours by available slot-hours.
• Report it per chamber, including nights and weekends.

What moves it

• Staggered load windows across the day.
• Batching units by dwell time so chambers are rarely half empty overnight.

Benchmark slot capacity with the Burn-In Test Capacity calculator.

Technician productivity

Technician output ties labor to output. A benchmark board tech completes 12 to 20 repaired units per 8-hour shift on mixed work, or 30 to 50 on simple reseat and reflash tasks no cited source.

World-class operations track productive touch time above 75 percent of paid time no cited source, versus a typical 55 to 65 percent no cited source, with the rest lost to material chasing and documentation.

Kitting and staging are the lever. Pre-picked parts and a clean return merchandise authorization (RMA) record can add 10 to 15 productive points per technician no cited source without any change to repair skill or headcount.

How to measure

• Count repaired units per technician per shift, split by type of work.
• Divide hands-on repair time by paid time.

What moves it

• Kitted, pre-picked parts waiting at the bench.
• A complete return record before the unit reaches the technician.

Estimate hands-on time per board with the Board Rework Time calculator.

Cost per repaired unit

Cost per repaired unit aggregates the rest, and it should be trended, not just quoted. Product mix makes cross-company comparison unreliable, so the real benchmark is your own trend line bending down while yield and TAT hold or improve.

As an improvement scenario, a depot moving first-pass yield from 84 to 90 percent, NFF from 12 to 7 percent and burn-in utilization from 55 to 78 percent will typically cut cost per repaired unit by 12 to 20 percent without touching wage rates no cited source.

How to measure

• Divide the month's total depot cost by units repaired and shipped.
• Trend it monthly against your own baseline, not an external number.

What moves it

• Every KPI above: yield, NFF, queue, repeat rate and chamber use.
• Value recovered from parts that cannot be repaired.

Offset part of the cost with the Parts Salvage Value calculator.

How to build your own baseline

• Rank levers by leverage, not by ease, starting with a cap on work in progress in the queue to fix TAT.
• Next, tighten the diagnostic screen to fix NFF and first-pass yield together.
• Then extend verification to fix repeat rate, and schedule chambers to lift utilization.
• Set one north-star target per quarter and hold the other KPIs as guardrails.
• Keep a balanced scorecard of five metrics rather than chasing any one number.

For example, a quarter's north-star target could be first-pass yield above 90 percent no cited source, with NFF, TAT, repeat rate and utilization held where they are.