Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders
Occupation · SOC 51-9021.00
Set up, operate, or tend machines to crush, grind, or polish materials, such as coal, glass, grain, stone, food, or rubber.
Also called: Grinder · Machine Operator · Miller · Preparation Operator (Prep Operator) · Beveler Operator · Cullet Trucker · Grinder Operator · Machine Tender · Polisher · Pulverizer · Abrasive Grinder · Air Bag Buffer
Job family: Production Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-51-9021-00/context.md directly.
AI work map
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Market signal
Independent published positions, read together — not a forecast.
- Declining employment outlook (-2.5% by 2034)
- 2,700 openings/yr
- Low AI exposure
- Median pay $46,890/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (94th); today's AI task-overlap is comparatively low (10th)
10th-percentile task overlap — yet about 2,700 openings a year (-2.5% projected, BLS) . What exposure means →
AI & job outlook
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Exposure to current AI
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Low | 16th | -1.0 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 15th | 0.1 | |
| AI assistant applicability (Microsoft) Low | 11th | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.1), and including AI-powered software (γ 0.1). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.
Mixed signals. Today's AI/LLM studies show relatively low exposure for this job, but the older (2013) Frey–Osborne work rated it higher for computerization and robotics. Different eras, different technologies — the AI measures above reflect the current state.
Historical automation estimate (2013)
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 1.0 · 94th percentile among occupations · High
How AI is actually used in this job
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Record data from operations, testing, and production on specified forms. | 0.2% |
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Declining · -2.5% by 2034 |
| Projected annual openings | 2,700 |
| Employment 2024 → 2034 | 28,700 → 27,900 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
Where this work sits on the global GenAI gradient
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international 4 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders sits at the 33rd percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure rose from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
20% mean task exposure (2025)
33rd percentile of 427 placed occupations
+1 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Cement, Stone and Other Mineral Products Machine Operators · 8114 | 23% | Not exposed |
| Mineral and Stone Processing Plant Operators · 8112 | 21% | Not exposed |
| Rubber Products Machine Operators · 8141 | 18% | Not exposed |
| Glass and Ceramics Plant Operators · 8181 | 17% | Not exposed |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
Tasks
All 22 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Observe operation of equipment to ensure continuity of flow, safety, and efficient operation, and to detect malfunctions. Core · importance 4.3
- Clean, adjust, and maintain equipment, using hand tools. Core · importance 4.1
- Tend accessory equipment, such as pumps and conveyors, to move materials or ingredients through production processes. Core · importance 4.1
- Move controls to start, stop, or adjust machinery and equipment that crushes, grinds, polishes, or blends materials. Core · importance 4.0
- Notify supervisors of needed repairs. Core · importance 4.0
- Weigh or measure materials, ingredients, or products at specified intervals to ensure conformance to requirements. Core · importance 4.0
- Test samples of materials or products to ensure compliance with specifications, using test equipment. Supplemental · importance 3.9
- Mark bins as to types of mixtures stored. Supplemental · importance 3.9
- Transfer materials, supplies, and products between work areas, using moving equipment and hand tools. Core · importance 3.8
- Add or mix chemicals and ingredients for processing, using hand tools or other devices. Supplemental · importance 3.8
- Collect samples of materials or products for laboratory testing. Supplemental · importance 3.8
- Record data from operations, testing, and production on specified forms. Core · importance 3.8
- Reject defective products and readjust equipment to eliminate problems. Core · importance 3.8
- Clean work areas. Core · importance 3.7
- Inspect chains, belts, or scrolls for signs of wear. Core · importance 3.7
- Load materials into machinery and equipment, using hand tools. Core · importance 3.7
- Turn valves to regulate the moisture contents of materials. Supplemental · importance 3.7
- Examine materials, ingredients, or products, visually or with hands, to ensure conformance to established standards. Core · importance 3.6
- Set mill gauges to specified fineness of grind. Supplemental · importance 3.6
- Read work orders to determine production specifications and information. Core · importance 3.5
- Dislodge and clear jammed materials or other items from machinery and equipment, using hand tools. Core · importance 3.4
- Break mixtures to size, using picks. Supplemental
Work activities
- Read work orders or other instructions to determine product specifications or materials requirements.
- Monitor equipment operation to ensure proper functioning.
- Operate grinding equipment.
- Record operational or production data.
- Test chemical or physical characteristics of materials or products.
- Measure ingredients or substances to be used in production processes.
- Weigh finished products.
- Measure dimensions of completed products or workpieces to verify conformance to specifications.
- Clean production equipment.
- Maintain production or processing equipment.
- Notify others of equipment repair or maintenance needs.
- Evaluate quality of materials or products.
- Clean work areas.
- Move products, materials, or equipment between work areas.
- Clear equipment jams.
- Inspect production equipment.
- Operate pumping systems or equipment.
- Collect samples of materials or products for testing.
- Mark products, workpieces, or equipment with identifying information.
- Adjust equipment controls to regulate flow of water, cleaning solutions, or other liquids.
- Load materials into production equipment.
- Mix substances to create chemical solutions.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Transferable skills
| Operations Monitoring | 3.9 | |
| Operation and Control | 3.9 | |
| Quality Control Analysis | 3.1 | |
| Coordination | 3.0 | |
| Judgment and Decision Making | 3.0 | |
| Time Management | 3.0 |
Abilities
| Manual Dexterity | 3.6 | |
| Control Precision | 3.6 | |
| Arm-Hand Steadiness | 3.5 | |
| Multilimb Coordination | 3.5 | |
| Rate Control | 3.5 | |
| Reaction Time | 3.5 | |
| Near Vision | 3.5 | |
| Problem Sensitivity | 3.3 | |
| Flexibility of Closure | 3.1 | |
| Perceptual Speed | 3.1 | |
| Finger Dexterity | 3.1 | |
| Static Strength | 3.1 | |
| Trunk Strength | 3.1 | |
| Auditory Attention | 3.1 | |
| Oral Comprehension | 3.0 | |
| Written Comprehension | 3.0 | |
| Oral Expression | 3.0 | |
| Deductive Reasoning | 3.0 | |
| Inductive Reasoning | 3.0 | |
| Category Flexibility | 3.0 | |
| Visualization | 3.0 | |
| Selective Attention | 3.0 | |
| Response Orientation | 3.0 | |
| Extent Flexibility | 3.0 | |
| Visual Color Discrimination | 3.0 |
Knowledge
| Administration and Management | 3.5 | |
| Production and Processing | 3.4 | |
| English Language | 3.2 | |
| Education and Training | 3.2 | |
| Public Safety and Security | 3.0 |
Essential skills
| Monitoring | 3.1 | |
| Reading Comprehension | 3.0 | |
| Active Listening | 3.0 | |
| Speaking | 3.0 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Tools & technology
| Example | Category | |
|---|---|---|
| Microsoft Excel | Spreadsheet software | Hot technology |
| Microsoft Office software | Office suite software | Hot technology |
| Microsoft Word | Word processing software | Hot technology |
| SAP software | Enterprise resource planning ERP software | Hot technology |
| Email software | Electronic mail software |
Work context
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
How to get in
- Job zone
- Zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed
- Education
- Usually requires a high school diploma or GED, though some occupations may not.
- Typical entry-level education
- High school diploma or equivalent · BLS, the typical path — not a requirement
- Related experience
- Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
- Preparation level
- SVP (Below 6.0) — total schooling plus on-the-job experience.
Education of current workers
Share of people in this occupation at each level of education.
| High School Diploma | 61.7% | |
| Less than a High School Diploma | 19.4% | |
| Post-Secondary Certificate | 1.2% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 6.8 | |
| Conventional | 4.6 | |
| Investigative | 2.1 | |
| Enterprising | 1.4 |
Interest areas
| Physical/Manual Labor | 4.9 | |
| Mechanics/Electronics | 2.9 | |
| Transportation/Machine Operation | 2.3 | |
| Engineering | 1.9 | |
| Construction/Woodwork | 1.8 | |
| Management/Administration | 1.4 | |
| Agriculture | 1.3 | |
| Physical Science | 1.3 | |
| Accounting | 1.2 |
Work styles
| Dependability | 3.0 | |
| Cautiousness | 2.1 | |
| Attention to Detail | 2.0 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $35,380 |
| 25th percentile | $38,990 |
| Median (50th) | $46,890 |
| 75th percentile | $58,440 |
| 90th percentile | $65,980 |
| People employed | 28,550 |
Industries that employ this occupation
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Manufacturing · Sector | 19,280 | $46,110 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 3,420 | $58,340 |
| Wholesale Trade · Sector | 2,390 | $42,490 |
| Construction · Sector | 1,230 | $49,450 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 820 | $41,450 |
| Temporary Help Services · National industry | 430 | $37,060 |
| Other Services (except Public Administration) · Sector | 240 | $46,150 |
| Machine Shops · National industry | 170 | $37,980 |
| Transportation and Warehousing · Sector | 170 | $37,630 |
| Agriculture, Forestry, Fishing and Hunting · Sector | 160 | $45,760 |
| Professional, Scientific, and Technical Services · Sector | 80 | $50,530 |
| Jewelry and Silverware Manufacturing · National industry | — | $60,990 |
Where this work is most concentrated
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 32.21× | 3,420 |
| Manufacturing · Sector | 8.16× | 19,280 |
| Machine Shops · National industry | 3.53× | 170 |
| Wholesale Trade · Sector | 2.14× | 2,390 |
| Agriculture, Forestry, Fishing and Hunting · Sector | 2.04× | 160 |
| Temporary Help Services · National industry | 0.88× | 430 |
| Construction · Sector | 0.82× | 1,230 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 0.49× | 820 |
Related occupations
Part of the Advanced Manufacturing career cluster.
- Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic · 51-4033.00 Compare →
- Grinding and Polishing Workers, Hand · 51-9022.00 Compare →
- Machine Feeders and Offbearers · 53-7063.00 Compare →
- Cutting and Slicing Machine Setters, Operators, and Tenders · 51-9032.00 Compare →
- Tool Grinders, Filers, and Sharpeners · 51-4194.00 Compare →
- Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders · 51-9041.00 Compare →
- Woodworking Machine Setters, Operators, and Tenders, Except Sawing · 51-7042.00 Compare →
- Mixing and Blending Machine Setters, Operators, and Tenders · 51-9023.00 Compare →
- Rolling Machine Setters, Operators, and Tenders, Metal and Plastic · 51-4023.00 Compare →
- Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders · 51-9012.00 Compare →
- Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic · 51-4035.00 Compare →
- Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders · 51-9051.00 Compare →
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
What you can do with this
Options the data surfaces for Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Skills that travel
Capabilities this work builds that are used across many other occupations.
Adjacent roles
Occupations O*NET rates as related — the nearby moves on the map.
- Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic Compare →
- Grinding and Polishing Workers, Hand Compare →
- Machine Feeders and Offbearers Compare →
- Cutting and Slicing Machine Setters, Operators, and Tenders Compare →
- Tool Grinders, Filers, and Sharpeners Compare →
Paths in
How people typically prepare for this work.
- High school diploma or equivalent · typical entry level
- Job zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed · preparation tier
Zoom out
On the global GenAI exposure gradient this work sits around the 33rd percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders show 10th-percentile AI task overlap — and about 2,700 annual U.S. openings
- Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders rank in the 10th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
- The occupation is projected to see about 2,700 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
- BLS projects employment to be declining (-2.5%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $46,890, across about 28,550 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders show 10th-percentile AI task overlap — and about 2,700 annual U.S. openings • Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders rank in the 10th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 2,700 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be declining (-2.5%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $46,890, across about 28,550 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders". https://singulariki.com/roles/role-51-9021-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-51-9021-00
APA
Singulariki. (2026). Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-51-9021-00
BibTeX
@misc{singulariki-role-51-9021-00,
title = {Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-51-9021-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.