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 →Metal-Refining Furnace Operators and Tenders
Occupation · SOC 51-4051.00
Operate or tend furnaces, such as gas, oil, coal, electric-arc or electric induction, open-hearth, or oxygen furnaces, to melt and refine metal before casting or to produce specified types of steel.
Also called: Central Melt Specialist · Furnace Operator · Melter · Vacuum Melter · Arc and Argon Oxygen Decarburization Melter (ARC and AOD Melter) · Automatic Furnace Operator · Control Room Operator · Electric Melt Operator · Melt Room Operator · Vessel Operator · Backbreaker · Bessemer Converter Blower
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-51-4051-00/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 (-2.3% by 2034)
- 2,000 openings/yr
- Low AI exposure
- Median pay $55,770/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (75th); today's AI task-overlap is comparatively low (13th)
13th-percentile task overlap — yet about 2,000 openings a year (-2.3% 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 | 12th | -1.2 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 17th | 0.1 | |
| AI assistant applicability (Microsoft) Low | 20th | 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 0.9 · 75th percentile among occupations · High
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 · -2.3% by 2034 |
| Projected annual openings | 2,000 |
| Employment 2024 → 2034 | 20,800 → 20,300 |
“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 2 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.
Metal-Refining Furnace Operators and Tenders sits at the 54th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure eased from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
28% mean task exposure (2025)
54th percentile of 427 placed occupations
−3 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Metal Production Process Controllers · 3135 | 31% | Minimal |
| Metal Processing Plant Operators · 8121 | 27% | 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 15 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Regulate supplies of fuel and air, or control flow of electric current and water coolant to heat furnaces and adjust temperatures. Core · importance 4.6
- Draw smelted metal samples from furnaces or kettles for analysis, and calculate types and amounts of materials needed to ensure that materials meet specifications. Core · importance 4.6
- Prepare material to load into furnaces, including cleaning, crushing, or applying chemicals, by using crushing machines, shovels, rakes, or sprayers. Supplemental · importance 4.5
- Weigh materials to be charged into furnaces, using scales. Core · importance 4.5
- Record production data, and maintain production logs. Core · importance 4.5
- Observe air and temperature gauges or metal color and fluidity, and turn fuel valves or adjust controls to maintain required temperatures. Core · importance 4.5
- Operate controls to move or discharge metal workpieces from furnaces. Core · importance 4.5
- Inspect furnaces and equipment to locate defects and wear. Core · importance 4.4
- Drain, transfer, or remove molten metal from furnaces, and place it into molds, using hoists, pumps, or ladles. Core · importance 4.4
- Remove impurities from the surface of molten metal, using strainers. Supplemental · importance 4.3
- Kindle fires, and shovel fuel and other materials into furnaces or onto conveyors by hand, with hoists, or by directing crane operators. Core · importance 4.3
- Observe operations inside furnaces, using television screens, to ensure that problems do not occur. Supplemental · importance 4.3
- Sprinkle chemicals over molten metal to bring impurities to the surface. Supplemental · importance 4.2
- Direct work crews in the cleaning and repair of furnace walls and flooring. Supplemental · importance 4.0
- Scrape accumulations of metal oxides from floors, molds, and crucibles, and sift and store them for reclamation. Supplemental · importance 3.7
Work activities
- Calculate specific material, equipment, or labor requirements for production.
- Collect samples of materials or products for testing.
- Place materials into molds.
- Record operational or production data.
- Operate cranes, hoists, or other moving or lifting equipment.
- Measure ingredients or substances to be used in production processes.
- Adjust equipment controls to regulate gas flow.
- Adjust equipment controls to regulate coolant flow.
- Adjust flow of electricity to tools or production equipment.
- Inspect production equipment.
- Monitor instruments to ensure proper production conditions.
- Adjust temperature controls of ovens or other heating equipment.
- Watch operating equipment to detect malfunctions.
- Skim impurities from molten metal.
- Load materials into production equipment.
- Ignite fuel to activate heating equipment.
- Signal others to coordinate work activities.
- Direct operational or production activities.
- Clean materials to prepare them for production.
- Clean production equipment.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Production and Processing | 4.0 | |
| Mechanical | 3.7 | |
| Public Safety and Security | 3.2 | |
| Administration and Management | 3.2 | |
| Education and Training | 3.0 |
Transferable skills
| Operations Monitoring | 3.9 | |
| Operation and Control | 3.8 | |
| Complex Problem Solving | 3.0 | |
| Quality Control Analysis | 3.0 |
Abilities
| Control Precision | 3.9 | |
| Problem Sensitivity | 3.8 | |
| Manual Dexterity | 3.8 | |
| Near Vision | 3.8 | |
| Arm-Hand Steadiness | 3.6 | |
| Reaction Time | 3.6 | |
| Selective Attention | 3.4 | |
| Information Ordering | 3.3 | |
| Multilimb Coordination | 3.3 | |
| Deductive Reasoning | 3.1 | |
| Perceptual Speed | 3.1 | |
| Rate Control | 3.1 | |
| Static Strength | 3.1 | |
| Extent Flexibility | 3.1 | |
| Depth Perception | 3.1 | |
| Hearing Sensitivity | 3.1 | |
| Oral Expression | 3.0 | |
| Inductive Reasoning | 3.0 | |
| Flexibility of Closure | 3.0 | |
| Finger Dexterity | 3.0 | |
| Response Orientation | 3.0 | |
| Trunk Strength | 3.0 | |
| Visual Color Discrimination | 3.0 | |
| Glare Sensitivity | 3.0 | |
| Auditory Attention | 3.0 |
Essential skills
| Monitoring | 3.6 | |
| Reading Comprehension | 3.0 | |
| Active Listening | 3.0 | |
| Speaking | 3.0 | |
| Critical Thinking | 3.0 | |
| Active Learning | 2.9 |
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 |
| Process control software | Industrial control software | |
| Process safety management software | Data base user interface and query software | |
| Production tracking system software | Inventory management 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.
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 6.9 | |
| Conventional | 4.0 | |
| Investigative | 2.8 |
Interest areas
| Physical/Manual Labor | 5.2 | |
| Mechanics/Electronics | 3.1 | |
| Engineering | 2.9 | |
| Transportation/Machine Operation | 2.2 | |
| Physical Science | 2.0 | |
| Mathematics/Statistics | 1.6 | |
| Accounting | 1.4 | |
| Management/Administration | 1.4 | |
| Human Resources | 1.2 |
Work styles
| Dependability | 3.0 | |
| Cautiousness | 2.5 | |
| Attention to Detail | 2.2 | |
| Stress Tolerance | 1.6 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $38,760 |
| 25th percentile | $46,550 |
| Median (50th) | $55,770 |
| 75th percentile | $65,070 |
| 90th percentile | $80,280 |
| People employed | 20,330 |
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 | 19,870 | $56,220 |
| Wholesale Trade · Sector | 280 | $42,370 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 110 | $70,440 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 70 | $53,910 |
| Jewelry and Silverware Manufacturing · National industry | 40 | $48,990 |
| Temporary Help Services · National industry | 40 | $53,740 |
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 |
|---|---|---|
| Manufacturing · Sector | 11.81× | 19,870 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 1.45× | 110 |
| Wholesale Trade · Sector | 0.35× | 280 |
Related occupations
Part of the Advanced Manufacturing career cluster.
- Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic · 51-4191.00 Compare →
- Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders · 51-9051.00 Compare →
- Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders · 51-9012.00 Compare →
- Welding, Soldering, and Brazing Machine Setters, Operators, and Tenders · 51-4122.00 Compare →
- Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders · 51-9192.00 Compare →
- Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders · 51-9041.00 Compare →
- Welders, Cutters, Solderers, and Brazers · 51-4121.00 Compare →
- Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic · 51-4072.00 Compare →
- Chemical Equipment Operators and Tenders · 51-9011.00 Compare →
- Stationary Engineers and Boiler Operators · 51-8021.00 Compare →
- Pourers and Casters, Metal · 51-4052.00 Compare →
- Cooling and Freezing Equipment Operators and Tenders · 51-9193.00 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 Metal-Refining Furnace 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.
- Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic Compare →
- Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders Compare →
- Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders Compare →
- Welding, Soldering, and Brazing Machine Setters, Operators, and Tenders Compare →
- Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders 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 54th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Metal-Refining Furnace Operators and Tenders show 13th-percentile AI task overlap — and about 2,000 annual U.S. openings
- Metal-Refining Furnace Operators and Tenders rank in the 13th 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 2,000 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 (-2.3%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $55,770, across about 20,330 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Metal-Refining Furnace Operators and Tenders show 13th-percentile AI task overlap — and about 2,000 annual U.S. openings • Metal-Refining Furnace Operators and Tenders rank in the 13th 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 2,000 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 (-2.3%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $55,770, across about 20,330 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Metal-Refining Furnace Operators and Tenders". https://singulariki.com/roles/role-51-4051-00 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
- 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. "Metal-Refining Furnace 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; 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-51-4051-00
APA
Singulariki. (2026). Metal-Refining Furnace Operators and Tenders. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-51-4051-00
BibTeX
@misc{singulariki-role-51-4051-00,
title = {Metal-Refining Furnace 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; 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-51-4051-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.