Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders
In short: today's best AI models could do about 5% 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 conversations, in-person and hands-on work, about 95% of the time, stays with people.
Set up, operate, or tend continuous flow or vat-type equipment; filter presses; shaker screens; centrifuges; condenser tubes; precipitating, fermenting, or evaporating tanks; scrubbing towers; or batch stills. These machines extract, sort, or separate liquids, gases, or solids from other materials to recover a refined product. Includes dairy processing equipment operators.
60,100 people do this job in the US. $51,610 a year.
Reviewed on October 3, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on0 h
- A person checks AI's work2 h
- Desk work AI can't do yet0 h
- Stays with people38 h
Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders, now: of a 40-hour week, AI could take on 0 hours, 2 hours become checking its work, 0 hours are desk work it can't do yet, and 38 hours stay with people.
The largest pieces: Log readings and production (about 2 h, a person checks); Monitor flow and gauges (under an hour, a person checks).
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.
- 0%
- 5%
- 0%
- 2%
- 93%
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.
What handing it over would take, now
The 5% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
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, 1%. With Claude Mythos Preview (early), measured in April 2026, 5%. Today's estimate: 5%.
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 20 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 76% of this job's working time as physical work. For 73% of the working time, a robot has been shown doing most of the task somewhere: 51% in a purpose-built cell, 21% in a structured facility. 0.94 of 3, the 155th highest of the 923 jobs.
- Not physical 24%
- No robot shown 4%
- In a purpose-built cell 51%
- In a structured facility 21%
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.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
94% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Operate processing machines, the hands-on work, 29%
- Clean and sterilize equipment, the hands-on work, 8%
- Set machine controls, the hands-on work, 6%
- Maintain hoses, pumps and filters, the hands-on work, 6%
- Connect pipes, the hands-on work, 5%
- Assemble equipment parts, the hands-on work, 4%
What becomes checking the machine
5% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it.
- Log readings and production, costly if wrong, 4%
- Monitor flow and gauges, costly if wrong, 1%
What to learn
- The hands-on craft. About 93% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check: spotting what a draft gets wrong is a skill of its own.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 20 tasks from .
| Task | ||||
|---|---|---|---|---|
| Operate machines to process materials in compliance with applicable safety, energy, or environmental regulations.Machines run to the safety, energy and environmental rules.Done several times a day by most who do it. Robots: in a purpose-built cell, Automated milk powder processing plant (PLC/SCADA process control, automated CIP, electronic compliance records) (Malisko Engineering (integrator) for a national dairy producer) (deployed). Anthropic's rating. | 29% | 1.7 h25 min to 3.3 h | Hands-on 100% | Stays with people |
| Clean or sterilize tanks, screens, inflow pipes, production areas, or equipment, using hoses, brushes, scrapers, or chemical solutions.Tanks, screens, pipes and areas cleaned with hoses, brushes and chemicals.Done several times a day by most who do it. Robots: in a structured facility, Tetra Pak CIP unit P (deployed). Anthropic's rating. | 8% | 50 min17 min to 2.5 h | Hands-on 100% | Stays with people |
| Set up or adjust machine controls to regulate conditions such as material flow, temperature, or pressure.Flow, temperature and pressure set and adjusted at the machine.Done hourly or more by most who do it. Robots: in a structured facility, Tetra Pak Pasteurizer D / D Base automation (sold). Anthropic's rating. | 6% | 21 min8 min to 50 min | Hands-on 100% | Stays with people |
| Install, maintain, or repair hoses, pumps, filters, or screens to maintain processing equipment, using hand tools.Hoses, pumps, filters and screens installed, maintained and repaired with hand tools.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 6% | 1.3 h25 min to 2.5 h | Hands-on 100% | Stays with people |
| Connect pipes between vats and processing equipment.Pipes connected between vats and equipment.Done daily by most who do it. Robots: in a purpose-built cell, Robofuel autonomous refuelling system (Scott Automation) (sold). Anthropic's rating. | 5% | 38 min13 min to 1.3 h | Hands-on 100% | Stays with people |
| Monitor material flow or instruments, such as temperature or pressure gauges, indicators, or meters, to ensure optimal processing conditions.Gauges and meters watched at the equipment and the panel.Done hourly or more by most who do it. | 5% | 13 min4 min to 25 min | Hands-on 70%, systems 30% | 30%Desk part half by now |
| Assemble fittings, valves, bowls, plates, disks, impeller shafts, or other parts to prepare equipment for operation.Fittings, valves, bowls, plates and shafts assembled for the run.Done daily by most who do it. Robots: in a purpose-built cell, RND Automation valve assembly cell (Epson robots, SCHUNK grippers, ATI compliance) (sold). Anthropic's rating. | 4% | 38 min17 min to 1.3 h | Hands-on 100% | Stays with people |
| Maintain logs of instrument readings, test results, or shift production for entry in computer databases.Readings, test results and shift output entered in the log.Done hourly or more by most who do it. | 4% | 13 min4 min to 25 min | Systems 100% | 100%Half by now |
| Test samples to determine viscosity, acidity, specific gravity, or degree of concentration, using test equipment such as viscometers, pH meters, or hydrometers.Viscosity, acidity, gravity and concentration tested with the instruments.Done several times a day by most who do it. Robots: in a purpose-built cell, FOSS CombiFoss / MilkoScan analysers with robot pipette systems and conveyor sample handling at Qlip (deployed). Anthropic's rating. | 4% | 17 min8 min to 38 min | Hands-on 100% | Stays with people |
| Inspect machines or equipment for hazards, operating efficiency, malfunctions, wear, or leaks.Machines looked over for hazards, wear, leaks and faults.Done daily by most who do it. Robots: in a structured facility, Boston Dynamics Spot with Spot CAM+IR and acoustic payload, Orbit software (deployed). Anthropic's rating. | 4% | 17 min8 min to 38 min | Hands-on 100% | Stays with people |
| Collect samples of materials or products for laboratory analysis.Samples drawn for the laboratory.Done several times a day by most who do it. Robots: in a purpose-built cell, iAM SAMPLE automatic milk sampler (ACRAM Flowing Technologies) (sold). Anthropic's rating. | 4% | 13 min4 min to 25 min | Hands-on 100% | Stays with people |
| Remove clogs, defects, or impurities from machines, tanks, conveyors, screens, or other processing equipment.Clogs and defects removed from tanks, screens and conveyors.Done daily by most who do it. Robots: in a purpose-built cell, BOLLFILTER automatic backwash filters; Eaton Automatic Self-Cleaning Filters and Strainers (sold). Anthropic's rating. | 4% | 38 min13 min to 1.7 h | Hands-on 100% | 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. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% 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.
- Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders5% now, 5% by 2028
- Mixing and Blending Machine Setters, Operators, and Tenders3% now, 3% by 2028
- Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders10% now, 10% by 2028
- Chemical Equipment Operators and Tenders22% now, 22% by 2028
- Chemical Plant and System Operators22% now, 22% 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).
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 Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders is within reach of AI now?
- An estimated 5% of the working time is within reach of AI models now and 5% 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 Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, 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: Log readings and production (100% of the task's time now); and Monitor flow and gauges (30% of the task's time now).
- Which tasks of Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, 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: Operate processing machines; Clean and sterilize equipment; and Set machine controls. Together such tasks are about 91% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are the hands-on craft; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 94% of the working time stays with people, 5% becomes checking a model's work and 0% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, 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 Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders?
- Anthropic's robot exposure rating (September 2026) finds 76% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 73% of the working time, 21% in a structured facility. Its index is 0.94 of 3. One example: Tetra Pak CIP unit P for "clean and sterilize equipment". 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 20 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on October 3, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), 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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