← Risk register SOC 51-6064 · reviewed 2026-08-11

Textile Winding, Twisting, and Drawing Out Machine Setters, Operators, and Tenders

22,020 US workers · median $38,670/yr · Production

COOKED

The work is threading yarn, splicing broken ends, doffing full bobbins, and watching machines for defects inside a controlled, repeatable mill environment — exactly the profile modern automatic winders, robotic doffers, and machine-vision defect detection are built to eliminate. Language AI is not the threat here; capital equipment is, and the industry has been shedding these jobs for decades through consolidation and offshoring. The hands are still needed for splicing, jam clearing, and maintenance today, which is the only real buffer.

10-year outlook: Employment keeps shrinking as remaining US mills invest in automatic winding and robotic doffing; the survivors are setters and machine mechanics, not tenders.

US employment, 2019–2025-29.4%
31,19022,020 workers

This fall is concentrated in 2020 and has not recovered since.

Median pay $29,790 → $38,670 +3.8% in real terms (nominal +29.8%, less ~25% US inflation over the period)

The job count is not the verdict

This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.

So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.

BLS projection, 2024–2034

-9% 21,700 → 19,800 on the projections basis

Exposed, and shrinking

Both signals point the same way: the tasks are largely automatable and the BLS projects -9% by 2034. This is the case where the score and the forecast agree, and it is the one worth taking seriously.

Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.

~2,500 openings a year on average, including replacing people who leave.

One email if this score changes. Watch as many occupations as you like from the same address — no account, and nothing is sent on a schedule, only when a verdict actually moves.

Also known as — 24 job titles this covers

Titles reported by people doing this work, from the US Department of Labor's O*NET survey. If your job title is here, this page is about your work even though the name doesn't match.

ConerBallerBeamerCoilerComberCopperDrawerFramerHankerReelerWarperWinderBlockerCreelerQuillerSkeinerSlubberSpinnerSpoolerThrowerTwisterRebeamerRedrawerRewinder

Score — 28/100 resistance

Holding it up: embodiment (11/20). Weakest point: liability shield (1/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 10 + 11 + 1 + 2 + 4 = 28. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 10/20

Mixed — a routine tier and a judgment tier Automatic winders with electronic yarn clearers and splicers already do the core end-joining and package-building unattended, and robotic doffers handle bobbin change on new lines — what keeps this at 10 rather than 4 is that a tender still creels heavy roving, clears wrapped-around-roller jams by hand, sets tension and traverse for an unfamiliar count, and catches slubs the clearer's settings were never tuned for.

Embodiment 11/20

Some physical or field component You are on your feet the whole shift walking a machine alley in lint, noise, and heat, reaching into moving frames to piece up ends — real physical work, but it is one fixed building, known machine geometry, and a floor plan that never changes, which is why this sits at 11 and not with linemen and roofers at 17.

Liability shield 1/20

No licence, no signature requirement There is no state licence, no board, no certificate that legally has to exist before you touch a twister — the mill's OSHA lockout/tagout and machine-guard training is a condition of employment, not a credential you own or that anyone would have to replace.

Trust premium 2/20

Anonymous artifact production The customer buys yarn by count, twist, and defect rate off a lab test; nobody downstream in the knitting or weaving plant knows or asks which operator built the package, so no relationship survives past the shipping dock.

Judgment & accountability 4/20

Executes defined procedures on defined inputs Speed, tension, twist multiplier, and package density come off a style card set by the process engineer, and the decision that is actually yours is when to stop the frame and call maintenance — a real call with waste consequences, but bounded by written procedure, which is what puts it at 4 rather than in the discretion band.

This occupation has already been through one. Headcount fell 28.8% between 2017 and 2025 — 30,940 to 22,020 — while the median wage held roughly flat in real terms (+ 4.9% after inflation). A job being commoditised usually loses pay along with headcount. One that shrinks by half while pay holds is leaving a specialist core behind, and the score above was assigned from the occupation title without sight of that history — so it may be describing the job this used to be rather than the people still doing it. Why this is a known limit.

Confidence: high · reviewed 2026-08-11 · how scoring works

What this job involves — and which parts are yours

The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.

AI already does these at usable quality

These still need a person

Active moats on the surviving side: embodiment

How to future-proof this job

Training paths for your skill gaps: MIT OpenCourseWare — full course materials across every department, free free · Coursera — negotiation, influence and persuasion courses free to audit · CS50x, Harvard — how software is actually built free · Coursera — work planning and personal productivity free to audit · Coursera — customer service and client-facing skill courses free to audit

All 35 skills ranked by how many jobs they open →

Where this experience transfers — occupations you could move toward

Computed from U.S. Dept. of Labor O*NET skill and knowledge profiles: high overlap with what you already do, a materially higher resistance score, no large jump in required training, and no licence you would have to start a new pipeline to get. Targets that pay meaningfully less, that are themselves COOKED, or whose own headcount is falling are excluded — a move into a shrinking trade is not an escape.

Laborers and Freight, Stock, and Material Movers, Hand EXPOSED · 39/100 · you already have ~81% of the skill profile

Paper Goods Machine Setters, Operators, and Tenders EXPOSED · 38/100 · you already have ~78% of the skill profile

Skills to close: Active Learning, Persuasion, Technology Design, Time Management

Tire Repairers and Changers EXPOSED · 49/100 · you already have ~76% of the skill profile

Skills to close: Service Orientation, Time Management

What would move this back up — beyond any one person

The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 37/100 — EXPOSED.

3 specific changes that would raise this score
  • already happening task resistance +3

    Task-mix shift within the mill: as automatic winders with splicers and robotic doffers take the routine tending tier, the surviving headcount is the person who sets up and changes over machines for new yarn counts, diagnoses recurring end-breaks to a specific traveler/tension/humidity cause, and clears novel jams. This is already visible in US mills where 'operator' postings have become 'setter/technician' postings requiring PLC and mechanical troubleshooting. Raises task_resistance only for the remaining fraction of the workforce, not the count of jobs.

  • plausible embodiment +3

    Product-mix shift toward high-value technical and specialty yarns — aramid, carbon, glass, conductive filament for defense and aerospace textiles — run in short lots on older or modified machines where automatic splicing is unreliable and changeovers are frequent. Berry Amendment and DFARS domestic-sourcing demand for US-made technical textiles is the visible driver.

  • plausible judgment accountability +3

    If reshored technical-textile plants push lot-level quality accountability down to the machine setter — signed setup sheets and first-article yarn checks tied to AS9100/ISO 9001 traceability for aerospace or ballistic end use — the role owns a consequential call (release or scrap a lot) rather than just tending. Watch for mills adopting operator-signed first-piece inspection under customer source-inspection requirements.

The limit. No plausible route to liability_shield or trust_premium: no license attaches to yarn winding and no buyer of yarn pays a premium for human-tended winding. Even with every lever above, the realistic ceiling is roughly the high 30s, and it applies to a smaller surviving workforce — the levers raise the resistance of the remaining job, not the number of jobs. Capital equipment cost, not AI capability, sets the pace.

These are conditions, not forecasts — what would have to happen, not what will. Specific rules, cases and bills are named so you can go and check whether they exist and where they stand; verify before relying on any of them. Nothing here is legal or financial advice.

Where this work is, and what it pays there

BLS metro figures for 20 areas. The verdict above does not change by city — the rubric judges what the work involves, not where it happens — but pay and headcount do, and the national median hides a very wide range.

Most of these jobs

Dalton, GA 3,370 $38,670 +0%
Charlotte-Concord-Gastonia, NC-SC 1,270 $36,800 -5%
Atlanta-Sandy Springs-Roswell, GA 1,110 $43,870 +13%
Winston-Salem, NC 780 $37,070 -4%
Greensboro-High Point, NC 620 $37,290 -4%
Chattanooga, TN-GA 510 $40,140 +4%
Greenville-Anderson-Greer, SC 430 $38,280 -1%
Providence-Warwick, RI-MA 320 $38,350 -1%

Best paid

Cincinnati, OH-KY-IN 60 $54,350 +41%
Kingsport-Bristol, TN-VA 250 $47,750 +23%
New York-Newark-Jersey City, NY-NJ 100 $47,230 +22%

Percentages are against this occupation's national median of $38,670. Counts are jobs in that metro, not vacancies. Metros where the BLS suppressed the cell are absent rather than shown as zero.

Who is actually doing this — nobody, on the record

We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.

That is worth saying out loud next to a score of 28. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.

Read that as a gap in the reporting we can see, not proof of absence — the dispatch runs on English-language feeds and misses plenty. If you know of a case, tell us, or add a field report from inside the job.

Quick take — do you do this job?

Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.

Self-reported and unverified — a sentiment signal, not a survey. One response per person per occupation; you can change your answer.

Field reports — what people say has changed

No field reports yet. A written account takes a paragraph rather than a tap, goes to an editor before it appears, and is the one thing on this page the rubric cannot produce on its own.

File a field report

Concrete beats general: a tool that arrived, a task that moved, a headcount decision you watched happen. Don't include anything that identifies you or your employer if that would put you at risk.

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Kept current

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