Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic
In short: today's best AI models could do about 20% 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 80% of the time, stays with people.
Set up, operate, or tend heating equipment, such as heat-treating furnaces, flame-hardening machines, induction machines, soaking pits, or vacuum equipment to temper, harden, anneal, or heat treat metal or plastic objects.
14,000 people do this job in the US. $48,750 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on8 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people32 h
Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic, now: of a 40-hour week, AI could take on 8 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 32 hours stay with people.
The largest pieces: Determine types and temperatures of baths and quenching media needed to attain specified part hardness, toughness, and ductility, using heat-treating charts and knowledge of methods, equipment, and metals (about 3 h); Read production schedules and work orders to determine processing sequences, furnace temperatures, and heat cycle requirements for objects to be heat-treated (about 2 h); Determine flame temperatures, current frequencies, heating cycles, and induction heating coils needed, based on degree of hardness required and properties of stock to be treated (about 2 h).
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.
- 20%
- 0%
- 80%
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, 19%. Today's estimate: 20%.
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
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 23 tasks showed up. Within each of Anthropic's methods, never across a change: none to 0.0018% (released February and March 2025); none to 0.0017% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | none | n/a | 0 of 23 |
| Released March 2025 | 0.0018% | 677 of 703 | 1 of 23 |
| The week of Aug 4, 2025 (released September 2025) | none | n/a | 0 of 23 |
| The week of Nov 13, 2025 (released January 2026) | none | n/a | 0 of 23 |
| The week of Feb 5, 2026 (released March 2026) | 0.0017% | 664 of 677 | 1 of 23 |
| April 2026 (released June 2026) | none | n/a | 0 of 23 |
| May 2026 (released June 2026) | none | n/a | 0 of 23 |
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 84% of this job's working time as physical work. For 80% of the working time, a robot has been shown doing most of the task somewhere: 76% in a purpose-built cell, 4% in a structured facility. 0.84 of 3, the 211th highest of the 923 jobs.
- Not physical 16%
- No robot shown 4%
- In a purpose-built cell 76%
- In a structured facility 4%
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 . 23 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Set up and operate or tend machines, such as furnaces, baths, flame-hardening machines, and electronic induction machines, that harden, anneal, and heat-treat metal.Done daily by most who do it. Robots: in a purpose-built cell, Can-Eng continuous mesh belt heat-treatment furnace line with PET Level 2 SCADA (installed at Gallos Metal Solutions, Milwaukee, WI) (deployed). Anthropic's rating. | 16% | 50 min17 min to 1.7 h | Stays with people | |
| Adjust controls to maintain temperatures and heating times, using thermal instruments and charts, dials and gauges of furnaces, and color of stock in furnaces to make setting determinations.Done hourly or more by most who do it. Robots: in a purpose-built cell, Eurotherm E+PLC400 heat treatment furnace control (deployed). Anthropic's rating. | 9% | 25 min8 min to 50 min | Stays with people | |
| Load parts into containers and place containers on conveyors to be inserted into furnaces, or insert parts into furnaces.Done hourly or more by most who do it.Robots: in a purpose-built cell, MWES robotic heat-treat load/unload cell (FANUC M-900iA/260L with vision and custom EOAT) (Midwest Engineered Systems (MWES) / FANUC) (deployed). Anthropic's rating. | 9% | 25 min8 min to 50 min | Stays with people | |
| Determine types and temperatures of baths and quenching media needed to attain specified part hardness, toughness, and ductility, using heat-treating charts and knowledge of methods, equipment, and metals.Done daily by most who do it. | 8% | 38 min13 min to 1.3 h | 100%Half by now | |
| Remove parts from furnaces after specified times, and air dry or cool parts in water, oil brine, or other baths.Done hourly or more by most who do it. Robots: in a purpose-built cell, DentonTSI integrated heat treat and quenching cell (FANUC R-2000iB/210F) (deployed). Anthropic's rating. | 7% | 21 min8 min to 50 min | Stays with people | |
| Instruct new workers in machine operation.Done yearly or less by most who do it. | 6% | 1.3 h25 min to 2.5 h | Stays with people | |
| Read production schedules and work orders to determine processing sequences, furnace temperatures, and heat cycle requirements for objects to be heat-treated.Done hourly or more by most who do it. | 6% | 13 min4 min to 33 min | 100%Half by now | |
| Determine flame temperatures, current frequencies, heating cycles, and induction heating coils needed, based on degree of hardness required and properties of stock to be treated.Done daily by most who do it. | 5% | 33 min13 min to 1.1 h | 100%Half by now | |
| Heat billets, bars, plates, rods, and other stock to specified temperatures preparatory to forging, rolling, or processing, using oil, gas, or electrical furnaces.Done daily by most who do it.Robots: in a purpose-built cell, InductoForge modular billet heating system (Inductoheat / Inductotherm Group), with Clinton Machine BPS billet pushout (Inductoheat, Inductotherm Group) (sold). Anthropic's rating. | 4% | 38 min13 min to 1.7 h | Stays with people | |
| Examine parts to ensure metal shades and colors conform to specifications, using knowledge of metal heat-treating.Done hourly or more by most who do it.Robots: in a purpose-built cell, KEYENCE machine vision systems (Multi-Spectrum Mode, CV-X / IV series) (sold). Anthropic's rating. | 4% | 13 min4 min to 38 min | Stays with people | |
| Reduce heat when processing is complete to allow parts to cool in furnaces or machinery.Done hourly or more by most who do it.Robots: in a structured facility, Nitrex N-EXT / NX series nitriding systems (NITREG expert control) (sold). Anthropic's rating. | 3% | 13 min4 min to 25 min | Stays with people | |
| Test parts for hardness, using hardness testing equipment, or by examining and feeling samples.Done hourly or more by most who do it.Robots: in a purpose-built cell, INNOVATEST automated hardness testing systems (with Tinius Olsen) (sold). Anthropic's rating. | 3% | 17 min8 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.
- Metal-Refining Furnace Operators and Tenders8% now, 8% by 2028
- Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders10% now, 10% by 2028
- Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic5% now, 5% 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
- Plating Machine Setters, Operators, and Tenders, Metal and Plastic6% now, 6% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
- Coating, Engraving, Heat Treating, and Allied Activities3,220 people
- Fabricated Metal Product Manufacturing (3321, 3322, 3325, 3326, and 3329 only)2,480 people
- Machinery Manufacturing (3331, 3332, 3334, and 3339 only)1,070 people
- Aerospace Product and Parts Manufacturing940 people
- Iron and Steel Mills and Ferroalloy Manufacturing630 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 Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic is within reach of AI now?
- An estimated 20% of the working time is within reach of AI models now and 20% 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 Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic 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: Determine types and temperatures of baths and quenching media needed to attain specified part hardness, toughness, and ductility, using heat-treating charts and knowledge of methods, equipment, and metals (100% of the task's time now); Read production schedules and work orders to determine processing sequences, furnace temperatures, and heat cycle requirements for objects to be heat-treated (100% of the task's time now); and Determine flame temperatures, current frequencies, heating cycles, and induction heating coils needed, based on degree of hardness required and properties of stock to be treated (100% of the task's time now).
- Which tasks of Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Set up and operate or tend machines, such as furnaces, baths, flame-hardening machines, and electronic induction machines, that harden, anneal, and heat-treat metal; Adjust controls to maintain temperatures and heating times, using thermal instruments and charts, dials and gauges of furnaces, and color of stock in furnaces to make setting determinations; and Load parts into containers and place containers on conveyors to be inserted into furnaces, or insert parts into furnaces. Together such tasks are about 80% of the working time.
- Do people already use AI for the work of Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic?
- 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 Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic?
- Anthropic's robot exposure rating (September 2026) finds 84% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 80% of the working time, 4% in a structured facility. Its index is 0.84 of 3. One example: Nitrex N-EXT / NX series nitriding systems (NITREG expert control) for "reduce heat when processing is complete to allow parts to cool in furnaces or machinery". 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 23 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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