Will AI replace Textile Winding, Twisting, and Drawing Out Machine Setters, Operators, and Tenders?
AI reaches little of this job’s work.
8/100
Low exposure
More exposed to AI than 15% of US workers.
- AI already used in
- 0% of the work
- As AI tools mature: up to
- 15% of the work
What the job involves
Set up, operate, or tend machines that wind or twist textiles; or draw out and combine sliver, such as wool, hemp, or synthetic fibers. Includes slubber machine and drawing frame operators.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Within reach(3)
- Notify supervisors or mechanics of equipment malfunctions.
- Record production data such as numbers and types of bobbins wound.
- Study guides, samples, charts, and specification sheets, or confer with supervisors or engineering staff to determine setup requirements.
Out of reach(20)
- Start machines, monitor operation, and make adjustments as needed.
- Stop machines when specified amount of products has been produced.
- Tend machines that twist together two or more strands of yarn or insert additional twists into single strands of yarn to increase strength, smoothness, or uniformity of yarn.
- Inspect machinery to determine whether repairs are needed.
- Thread yarn, thread, or fabric through guides, needles, and rollers of machines.
and 15 more
Also called
Twister · Spinner · Twister Operator · Winder Operator · Twister Tender · Warper · Winder · Yarn Winder
Related jobs
- Extruding and Forming Machine Setters, Operators, and Tenders, Synthetic and Glass Fibers10/100
- Machine Feeders and Offbearers9/100
- Textile Knitting and Weaving Machine Setters, Operators, and Tenders12/100
- Paper Goods Machine Setters, Operators, and Tenders3/100
- Cutting and Slicing Machine Setters, Operators, and Tenders8/100
What these numbers mean
The score is the share of this job’s work, weighted by how important and frequent each task is, that AI could do in half the time: tasks an AI model could do alone count in full, tasks that need software built on AI count half.
“AI already used” is the share of the work in tasks where people are recorded using AI today. “As AI tools mature” counts every task AI could halve, with or without extra software.
The percentile compares the score with every job’s, weighted by how many people in the US do each one. Exposure means AI could change how the work is done, not that the job goes away. These are estimates for the typical job, not predictions.
Sources
- O*NET 31.0 Database, U.S. Department of Labor, Employment and Training Administration
- GPTs are GPTs: Labor market impact potential of LLMs (task labels), Eloundou, Manning, Mishkin & Rock (2023), OpenAI and University of Pennsylvania
- Anthropic Economic Index: labor market impacts (task penetration), Anthropic
- Occupational Employment and Wage Statistics, May 2025 (national and metropolitan areas), U.S. Bureau of Labor Statistics