Rivetira
Book a line assessment

Three deployments, measured against signed baselines

Each of these started as a line assessment on one station. Each has a baseline that was agreed in writing before a single agent ran, measured from the same telemetry the agents use.

0%25%50%75%100%Shim hours per join64.0%Delivered rate38.0%Escapes to next station71.0%Join cycle time47.0%Takt adherence gain11.4%FOD events84.0%Magnitude of change (%)
Headline movements across the three case studiesMagnitudes shown as absolute values; direction of improvement differs per metric and is stated in each case study.
Headline movements across the three case studies
MetricMagnitude of change (%)
Shim hours per join64.0%
Delivered rate38.0%
Escapes to next station71.0%
Join cycle time47.0%
Takt adherence gain11.4%
FOD events84.0%

Airframes assembled on Rivetira across commercial, defense, business-jet, eVTOL and space-structure programs: 8 factories, 70 assembly stations.

Meridian Aerostructures Calder Aviation Group Northvane Defense Solstice Jets Helion Air Mobility Orbital Frame Systems

Removing hand-fit shimming from a narrowbody wing box

Meridian Aerostructures · Tier-1 aerostructures. Predictive shimming cut fit-up from 3.4 iterations to a single machined pass across 14 stations.

Shim hours per join

34h

▼ -64% decrease from 94 h

Gap prediction MAE

0.031 mm

▼ -58% decrease vs hand measurement

Join cycle time

2.6 d

▼ -47% decrease from 4.9 d

Right-first-time

98.7%

▲ +8.4% increase structural joins

The problem

A narrowbody wing box join was taking 3.4 fit-up iterations. Each iteration meant separating the structure, hand-measuring the gap with feeler gauges, machining or stacking shims, and re-presenting. Fourteen stations, 94 shim hours per join, and a fit that still varied by mechanic.

What we deployed

Metrology & Predictive Shimming ran in shadow for nine weeks across 1,900 joins, learning the relationship between as-built part geometry, fixture state, thermal condition and the resulting gap field. Once gap prediction MAE fell below 0.04 mm it was promoted to advisory, then to closed loop driving the 5-axis shim machining cell directly.

The result

Fit-up became a single machined pass. Shim hours per join fell from 94 to 34, join cycle time from 4.9 days to 2.6, and right-first-time on structural joins reached 98.7%. The wing box stopped being the constraint on the line.

0.000 mm0.030 mm0.050 mm0.080 mm0.100 mm0.130 mmMean absolute errorWk 1Wk 5Wk 9Wk 13Wk 17Wk 21Wk 25Wk 29Gap prediction MAEHand-measurement error
Gap prediction accuracy versus hand measurement, Meridian wing boxHand-measurement error is the measured repeatability of feeler-gauge readings across mechanics on the same join.
Gap prediction accuracy versus hand measurement, Meridian wing box
Week since kickoffGap prediction MAEHand-measurement error
Wk 10.112 mm0.074 mm
Wk 50.089 mm0.076 mm
Wk 90.068 mm0.073 mm
Wk 130.052 mm0.075 mm
Wk 170.043 mm0.072 mm
Wk 210.037 mm0.074 mm
Wk 250.033 mm0.073 mm
Wk 290.031 mm0.074 mm

Meridian Aerostructures: the underlying numbers

0255075100Fit-up iterations (before)3.4Fit-up iterations (after)1.1Shim hours (before)94.0Shim hours (after)34.0Join cycle days (before)4.9Join cycle days (after)2.6Value (mixed units — see table)
Before and after, Meridian wing box joinUnits differ per row; the data table carries each unit explicitly. Bars share one axis for visual comparison only.
Before and after, Meridian wing box join
MeasureValue (mixed units — see table)
Fit-up iterations (before)3.4
Fit-up iterations (after)1.1
Shim hours (before)94.0
Shim hours (after)34.0
Join cycle days (before)4.9
Join cycle days (after)2.6

“We stopped arguing about whether the gap was 0.4 or 0.6 millimetres. The twin predicted it, the shim came off the machine right, and the join closed in one pass.”

Dana WhitlockDirector of Wing Operations, Meridian Aerostructures

−64% shim hours per join

Segment
Tier-1 aerostructures
Stations deployed
14
Program
Narrowbody wing box
Baseline window
90 days pre-deployment
Autonomy level reached
Closed loop

Holding takt through a single-aisle rate ramp

Calder Aviation Group · Commercial OEM. Line-and-takt balancing across 22 stations absorbed a 38% rate increase without adding positions.

Delivered rate

41/mo

▲ +38% increase from 30/mo

Takt adherence

96.8%

▲ +11% increase rolling 90 d

Travelled work

−44%

▼ -44% decrease jobs moved downstream

Overtime hours

−29%

▼ -29% decrease assembly mechanics

The problem

A single-aisle final assembly line was committed to a 38% rate increase. The plan on the table was four additional positions and a building extension. Takt adherence was 85.4% and travelled work was rising every month as jobs slipped downstream.

What we deployed

Line & Takt Optimisation ingested station cycle data from the MES across 22 stations and rebalanced work content every shift against actual, not planned, cycle times. Where a station drifted, work was re-sequenced ahead of the drift rather than after it. Robotic handling supervision removed the crane-wait time that had been absorbing float.

The result

Delivered rate went from 30 to 41 aircraft per month inside the existing footprint. Takt adherence reached 96.8%, travelled work fell 44%, and overtime for assembly mechanics fell 29%. The building extension was cancelled.

30 /mo33 /mo35 /mo38 /mo40 /mo43 /moAircraft per monthJanFebMarAprMayJunJulAugSepOctDelivered ratePlanned rate
Delivered rate against the committed ramp plan, Calder final assemblyThe value axis is truncated to resolve the difference between plan and actual; full range in the data table.
Delivered rate against the committed ramp plan, Calder final assembly
MonthDelivered ratePlanned rate
Jan30 /mo30 /mo
Feb30 /mo31 /mo
Mar31 /mo32 /mo
Apr33 /mo33 /mo
May34 /mo35 /mo
Jun36 /mo36 /mo
Jul37 /mo38 /mo
Aug39 /mo39 /mo
Sep40 /mo40 /mo
Oct41 /mo41 /mo

Calder Aviation Group: the underlying numbers

0%20%40%60%80%100%Share of station timePre-deploymentMonth 3Month 6Month 9Month 12
Composition of station time through the deploymentShares sum to 100% in each period. Measured from MES station cycle data across 22 stations.
Composition of station time through the deployment
PeriodValue-added timeWait for parts / craneRework & travelled workInspection waitTotal
Pre-deployment58%21%14%7%100%
Month 363%17%12%8%100%
Month 669%13%10%8%100%
Month 974%10%8%8%100%
Month 1278%8%8%6%100%

“The rate ramp was going to cost us four more positions. Instead the line rebalanced itself every shift and we found the capacity inside the stations we already had.”

Marcus AdeyemiPlant Director, Final Assembly, Calder Aviation Group

+38% delivered rate

Segment
Commercial OEM
Stations deployed
22
Program
Single-aisle final assembly
Baseline window
90 days pre-deployment
Autonomy level reached
Closed loop

Driving airworthiness escapes toward zero on a tactical airlifter

Northvane Defense · Defense prime. Hole-and-fastener inspection caught 412 conditions before the structure left the station.

Escapes to next station

−71%

▼ -71% decrease vs spot inspection

FOD events

2/mo

▼ -84% decrease from 12/mo

NCR cycle time

−52%

▼ -52% decrease raise to disposition

Inspection coverage

100%

▲ +71% increase from 29% sampled

The problem

A tactical airlifter program inspected 29% of holes by sample. Escapes were reaching the next station, and each one meant disassembly, disposition and a nonconformance record. FOD events were running at twelve a month. The program office wanted an audit trail nobody could produce in under two weeks.

What we deployed

Hole & Fastener Inspection deployed air-gapped across nine stations. Every drilled hole was measured for diameter, countersink depth, perpendicularity, burr and surface condition; every fastener was checked for seating, flushness and grip length. FOD sensing ran continuously on the same imagery. Nothing left the enclave.

The result

Inspection coverage went from 29% sampled to 100%. Escapes to the next station fell 71%, FOD events from twelve a month to two, and NCR cycle time from raise to disposition fell 52%. A complete airframe trace is now produced in ninety seconds.

0255075100125Count per quarterQ1Q2Q3Q4Q5Q6
Escapes versus conditions caught in station, Northvane tactical airlifterConditions caught in station rise first — the same defects, found earlier — then fall as the drilling process itself is corrected upstream.
Escapes versus conditions caught in station, Northvane tactical airlifter
Quarter since go-liveEscapes to next stationConditions caught in station
Q18431
Q27168
Q35294
Q441112
Q531106
Q62498

Northvane Defense: the underlying numbers

The 412 conditions caught before the structure left the stationEvery one of these would previously have had a 71% chance of reaching the next station undetected.
The 412 conditions caught before the structure left the station
SegmentShare
Countersink depth118
Hole diameter94
Perpendicularity71
Burr / surface condition58
Fastener seating41
FOD in structure30

“Every hole is now inspected, not one in four. My airworthiness record writes itself, and I can hand an auditor a complete trace in ninety seconds.”

Priya RaghunathanChief Quality & Airworthiness Engineer, Northvane Defense

100% inspection coverage

Segment
Defense prime
Stations deployed
9
Program
Tactical airlifter
Baseline window
90 days pre-deployment
Autonomy level reached
Supervised (air-gapped)

What the three deployments have in common

A signed baseline first

Every deployment locked its baseline in writing before a single agent ran. Without that, a result is an anecdote.

90-day pre-deployment window

Shadow mode before advisory

Agents predicted for weeks while humans worked normally. Promotion only followed measured accuracy against physical reality.

6–11 weeks in shadow

One station, then the line

None of these started as a factory rollout. Each proved a single cell first, then expanded on the strength of the number.

1 cell → 4–22 stations

Where the money actually comes back

Rivetira is priced on the metric it moves. This is the value stack from a representative 14-station wing-box deployment.

$0M$2M$4M$6MShim labour removed$4.9MRework hours avoided$3.6MRate capacity unlocked$3.1MScrap & escapes avoided$2.2MOvertime reduction$1.4MInspection labour$0.9MAnnualised value (USD)
Annualised value by source, 14-station wing-box deploymentAgainst $2.7M annual platform cost at Cell pricing across 14 stations. Illustrative model — your line assessment produces your numbers.
Annualised value by source, 14-station wing-box deployment
Value sourceAnnualised value (USD)
Shim labour removed$4.9M
Rework hours avoided$3.6M
Rate capacity unlocked$3.1M
Scrap & escapes avoided$2.2M
Overtime reduction$1.4M
Inspection labour$0.9M

Annualised value

$16.1M

14 stations

Platform cost

$2.7M

Cell pricing, annual prepay

Payback period

2.4 mo

from first closed-loop station

Net revenue retention

136%

▲ +36% increase expansion by station and module

Shadow first. Autonomy is earned, not switched on.

Every agent starts by watching. It is promoted only when its measured accuracy clears the mechanic-plus-metrology baseline and the twin agrees.

  1. Weeks 1–4

    Shadow

    Agent observes the station, predicts every outcome, actuates nothing. Accuracy measured against what the mechanics actually do.

  2. Weeks 4–10

    Advisory

    Agent recommends feed, shim geometry and sequence. A human accepts or rejects; every rejection becomes training data.

  3. Weeks 10–20

    Supervised

    Agent actuates with a human in the loop and a live fail-safe stop. Airworthiness-critical dispositions still require sign-off.

  4. Week 20+

    Closed loop

    Agent runs the step. Humans handle exceptions and the twin gates any change to the control policy.

87.5%90.0%92.5%95.0%97.5%100.0%Prediction accuracyWk 2Wk 4Wk 6Wk 8Wk 10Wk 12Wk 16Wk 20Wk 24promotion gateAgent accuracyMechanic + metrology baseline
Agent accuracy against the human baseline during shadow and advisory phasesPromotion to supervised autonomy requires four consecutive weeks above baseline plus twin agreement. The value axis is truncated to resolve the crossover.
Agent accuracy against the human baseline during shadow and advisory phases
WeekAgent accuracyMechanic + metrology baseline
Wk 288.2%94.1%
Wk 491.4%94.0%
Wk 693.6%94.2%
Wk 895.2%94.1%
Wk 1096.4%94.3%
Wk 1297.1%94.2%
Wk 1697.8%94.1%
Wk 2098.3%94.2%
Wk 2498.6%94.3%

Assembly autonomy, measured on the line

Every figure below is produced by the same telemetry the agents act on — station cycle, hole quality, gap field, fastener state and conformance. Pilot and design-partner aggregate, trailing 12 months.

Holes drilled under agent control

41.6M

▲ +32% increase cumulative, all lines

Right-first-time, structural joins

97.9%

▲ +9.1% increase vs 88.8% baseline

Shim hours removed per join

68%

▼ -68% decrease 96 h → 31 h

Assembly-line uptime

99.94%

▲ +0.3% increase edge runtime, trailing 90 d

Aggregate across design-partner lines. Baselines are the same stations before Rivetira, measured over an equivalent period.

Questions engineers actually ask

Anything else goes to the people who build it. Ask an assembly engineer or read the full FAQ.

The deployments, structures and results are representative of Rivetira engagements; company names are anonymised at customer request as is standard on aerospace programs. Named references are available under NDA after a line assessment.

Because the constraints differ. A commercial ramp is throughput-constrained, a defense program is escape-constrained, an eVTOL program is industrialisation-constrained. The line assessment identifies which one you are before anyone quotes a number.

Shadow mode produces measurable prediction accuracy inside six weeks. Operational results follow the first closed-loop promotion, which has ranged from four to eleven months depending on structure complexity and accreditation requirements.

Build your own case study

A line assessment maps one station, quantifies the rework, shim and rate opportunity, and returns a modelled ROI in three weeks. No production disruption.