# Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders

> Set up, operate, or tend machines to crush, grind, or polish materials, such as coal, glass, grain, stone, food, or rubber.

- **SOC code:** 51-9021.00
- **Canonical URL:** https://singulariki.com/roles/role-51-9021-00
- **Also known as:** Grinder, Machine Operator, Miller, Preparation Operator (Prep Operator), Beveler Operator, Cullet Trucker, Grinder Operator, Machine Tender
- **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):
- Observe operation of equipment to ensure continuity of flow, safety, and efficient operation, and to detect malfunctions.
- Clean, adjust, and maintain equipment, using hand tools.
- Tend accessory equipment, such as pumps and conveyors, to move materials or ingredients through production processes.
- Move controls to start, stop, or adjust machinery and equipment that crushes, grinds, polishes, or blends materials.
- Notify supervisors of needed repairs.
- Weigh or measure materials, ingredients, or products at specified intervals to ensure conformance to requirements.
- Test samples of materials or products to ensure compliance with specifications, using test equipment.
- Mark bins as to types of mixtures stored.
- Transfer materials, supplies, and products between work areas, using moving equipment and hand tools.
- Add or mix chemicals and ingredients for processing, using hand tools or other devices.
- Record data from operations, testing, and production on specified forms.
- Collect samples of materials or products for laboratory testing.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Operations Monitoring _(transferable_skill)_
- Operation and Control _(transferable_skill)_
- Manual Dexterity _(ability)_
- Control Precision _(ability)_
- Arm-Hand Steadiness _(ability)_
- Multilimb Coordination _(ability)_
- Rate Control _(ability)_
- Reaction Time _(ability)_
- Near Vision _(ability)_
- Administration and Management _(knowledge)_
- Production and Processing _(knowledge)_
- Problem Sensitivity _(ability)_

**Skills in demand:**
- English Language _(Common Skill)_
- Finger Dexterity _(Common Skill)_
- Visualization _(Specialized Skill)_
- Time Management _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Active Listening _(Common Skill)_
- Mathematics _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Word _(hot technology)_
- SAP software _(hot technology)_
- Email software

## AI exposure & outlook

- **AI task-overlap index:** 10th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 16th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 15th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 11th 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):** -2.5% growth (Declining); 2.7k annual openings; 28.7k → 27.9k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $46,890; 28,550 employed.

## 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-51-9021-00_