# Textile Bleaching and Dyeing Machine Operators and Tenders

> Operate or tend machines to bleach, shrink, wash, dye, or finish textiles or synthetic or glass fibers.

- **SOC code:** 51-6061.00
- **Canonical URL:** https://singulariki.com/roles/role-51-6061-00
- **Also known as:** Dye Machine Operator, Dye Operator, Dyer, Machine Operator (Machine Op), Beck Operator, Dye House Worker, Dye Line Operator, Dye Tub Operator
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Weigh ingredients, such as dye, to be mixed together for use in textile processing.
- Start and control machines and equipment to wash, bleach, dye, or otherwise process and finish fabric, yarn, thread, or other textile goods.
- Observe display screens, control panels, equipment, and cloth entering or exiting processes to determine if equipment is operating correctly.
- Notify supervisors or mechanics of equipment malfunctions.
- Monitor factors such as temperatures and dye flow rates to ensure that they are within specified ranges.
- Sew ends of cloth together, by hand or using machines, to form endless lengths of cloth to facilitate processing.
- Add dyes, water, detergents, or chemicals to tanks to dilute or strengthen solutions, according to established formulas and solution test results.
- Ravel seams that connect cloth ends when processing is completed.
- Remove dyed articles from tanks and machines for drying and further processing.
- Adjust equipment controls to maintain specified heat, tension, and speed.
- Examine and feel products to identify defects and variations from coloring and other processing standards.
- Soak specified textile products for designated times.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Operations Monitoring _(transferable_skill)_
- Arm-Hand Steadiness _(ability)_
- Control Precision _(ability)_
- Operation and Control _(transferable_skill)_
- Near Vision _(ability)_
- Production and Processing _(knowledge)_
- Manual Dexterity _(ability)_
- Visual Color Discrimination _(ability)_
- Oral Comprehension _(ability)_
- Deductive Reasoning _(ability)_
- Information Ordering _(ability)_
- Perceptual Speed _(ability)_

**Skills in demand:**
- Information Ordering _(Specialized Skill)_
- Finger Dexterity _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Visualization _(Specialized Skill)_
- Time Management _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft PowerPoint _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Linux _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_

**Tools & technology:**
- Linux _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Word _(hot technology)_
- SAP software _(hot technology)_
- Hewlett-Packard HP OpenVMS

## AI exposure & outlook

- **AI task-overlap index:** 24th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 23rd percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 23rd percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 31st percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 94th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -10.1% growth (Declining); 0.7k annual openings; 6.2k → 5.5k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $37,320; 5,820 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 40% automation, 24% augmentation (usage-weighted).
- **Autonomy median:** 3.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** none.

**Tasks most handed to AI here:**
- Key in processing instructions to program electronic equipment. _(1.5% of measured AI use; none)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me key in processing instructions to program electronic equipment.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-51-6061-00_