Metal-Refining Furnace Operators and Tenders
In short: today's best AI models could do about 8% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about the same by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 92% of the time, stays with people.
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.
16,780 people do this job in the US. $54,430 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on3 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people37 h
Metal-Refining Furnace Operators and Tenders, now: of a 40-hour week, AI could take on 3 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 37 hours stay with people.
The largest pieces: Record production data, and maintain production logs (about 3 h); Observe operations inside furnaces, using television screens, to ensure that problems do not occur (under an hour).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 8%
- 0%
- 92%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 2%. With Claude Mythos Preview (early), measured in April 2026, 8%. Today's estimate: 8%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
None of this job's 15 tasks showed up in the Claude.ai conversations Anthropic sampled in any of its 7 releases, from February 2025 to May 2026.
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 88% of this job's working time as physical work. For 88% of the working time, a robot has been shown doing most of the task somewhere: 39% in a purpose-built cell, 49% in a structured facility. 1.37 of 3, the 32nd highest of the 923 jobs.
- Not physical 12%
- In a purpose-built cell 39%
- In a structured facility 49%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
The tasks
Sorted by . 15 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Drain, transfer, or remove molten metal from furnaces, and place it into molds, using hoists, pumps, or ladles.Done hourly or more by most who do it. Robots: in a purpose-built cell, Danieli Automatic EAF Tapping System (Q-Slag / Ladle Level Detection with AMETEK LAND imagers) (sold). Anthropic's rating. | 15% | 38 min17 min to 1.3 h | Stays with people | |
| Draw smelted metal samples from furnaces or kettles for analysis, and calculate types and amounts of materials needed to ensure that materials meet specifications.Done daily by most who do it. Robots: in a structured facility, ARMS (Automated Robotic Melt Shop) (Inductotherm Corp.) (deployed). Anthropic's rating. | 10% | 33 min17 min to 1.3 h | Stays with people | |
| Regulate supplies of fuel and air, or control flow of electric current and water coolant to heat furnaces and adjust temperatures.Done hourly or more by most who do it. Robots: in a structured facility, Danieli Q-Melt automatic furnace (Q-Reg electrode regulator, LINDARC off-gas analyzer, Melt-Model) (deployed). Anthropic's rating. | 9% | 21 min8 min to 50 min | Stays with people | |
| Prepare material to load into furnaces, including cleaning, crushing, or applying chemicals, by using crushing machines, shovels, rakes, or sprayers.Done daily by most who do it.Robots: in a purpose-built cell, Danieli automatic charging crane (ABS meltshop) (deployed). Anthropic's rating. | 8% | 38 min17 min to 1.3 h | Stays with people | |
| Inspect furnaces and equipment to locate defects and wear.Done daily by most who do it. Robots: in a structured facility, Spot with thermal camera payload + Orbit fleet management (Boston Dynamics) (deployed). Anthropic's rating. | 8% | 38 min17 min to 1.7 h | Stays with people | |
| Kindle fires, and shovel fuel and other materials into furnaces or onto conveyors by hand, with hoists, or by directing crane operators.Done daily by most who do it. Robots: in a purpose-built cell, EAF ChargeOpt (automated EAF charging crane system) (Primetals Technologies) (sold). Anthropic's rating. | 7% | 25 min13 min to 50 min | Stays with people | |
| Record production data, and maintain production logs.Done hourly or more by most who do it. | 7% | 13 min4 min to 25 min | 100%Half by now | |
| Scrape accumulations of metal oxides from floors, molds, and crucibles, and sift and store them for reclamation.Done daily by most who do it.Robots: in a purpose-built cell, ALTEK TARDIS Generation III dross press (dross management line) (deployed). Anthropic's rating. | 7% | 50 min25 min to 1.7 h | Stays with people | |
| Direct work crews in the cleaning and repair of furnace walls and flooring.Done daily by most who do it. | 6% | 1.7 h50 min to 3.3 h | Stays with people | |
| Observe air and temperature gauges or metal color and fluidity, and turn fuel valves or adjust controls to maintain required temperatures.Done hourly or more by most who do it. Robots: in a structured facility, Q-Robot Melt (Sample) (Danieli) (sold). Anthropic's rating. | 6% | 13 min4 min to 33 min | Stays with people | |
| Weigh materials to be charged into furnaces, using scales.Done hourly or more by most who do it. Robots: in a purpose-built cell, Magaldi Superbelt HD scrap infeed / weigh-belt conveyor (deployed). Anthropic's rating. | 5% | 17 min8 min to 38 min | Stays with people | |
| Operate controls to move or discharge metal workpieces from furnaces.Done daily by most who do it. Robots: in a purpose-built cell, Danieli automatic EAF tapping system (Q-ATS with Q-Slag and LLD) (deployed). Anthropic's rating. | 4% | 13 min4 min to 33 min | Stays with people |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic20% now, 20% by 2028
- Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders10% now, 10% by 2028
- Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders5% now, 5% by 2028
- Welding, Soldering, and Brazing Machine Setters, Operators, and Tenders11% now, 11% by 2028
- Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders5% now, 5% by 2028
- Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders13% now, 13% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
- Nonferrous Metal (except Aluminum) Production and Processing3,800 people
- Foundries3,670 people
- Iron and Steel Mills and Ferroalloy Manufacturing3,020 people
- Alumina and Aluminum Production and Processing2,420 people
- Fabricated Metal Product Manufacturing (3321, 3322, 3325, 3326, and 3329 only)610 people
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Metal-Refining Furnace Operators and Tenders is within reach of AI now?
- An estimated 8% of the working time is within reach of AI models now and 8% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Metal-Refining Furnace Operators and Tenders come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Record production data, and maintain production logs (100% of the task's time now); and Observe operations inside furnaces, using television screens, to ensure that problems do not occur (100% of the task's time now).
- Which tasks of Metal-Refining Furnace Operators and Tenders stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Drain, transfer, or remove molten metal from furnaces, and place it into molds, using hoists, pumps, or ladles; Draw smelted metal samples from furnaces or kettles for analysis, and calculate types and amounts of materials needed to ensure that materials meet specifications; and Regulate supplies of fuel and air, or control flow of electric current and water coolant to heat furnaces and adjust temperatures. Together such tasks are about 92% of the working time.
- Do people already use AI for the work of Metal-Refining Furnace Operators and Tenders?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Metal-Refining Furnace Operators and Tenders?
- Anthropic's robot exposure rating (September 2026) finds 88% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 88% of the working time, 49% in a structured facility. Its index is 1.37 of 3. One example: ARMS (Automated Robotic Melt Shop) for "draw smelted metal samples from furnaces or kettles for analysis, and calculate types and amounts of materials needed to ensure that materials meet specifications". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 15 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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