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Manufacturing & Production · Updated Aug 2026

Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders

Operate or tend heating equipment other than basic metal, plastic, or food processing equipment. Includes activities such as annealing glass, drying lumber, curing rubber, removing moisture from materials, or boiling soap.

JVS 2.0.0-phase4b
AI Exposure
53/100
Moderate

How much of this occupation’s work can be materially affected by current AI systems.

Replacement Risk
46/100
Moderate

How likely exposure is to translate into reduced human demand.

Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured

Evidence quality
Confidence83/100
Task coverage89%

Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.

Task-level evidence

What is driving the score?

Occupation scores are built from the task mix—not a single prediction about a job title.

JVS 2.0.0-phase4b
TaskImportanceAI impactExposure
Press and adjust controls to activate, set, and regulate equipment according to specifications.High
68
Record gauge readings, test results, and shift production in log books.High
70
Calculate amounts of materials to be loaded into furnaces, adjusting amounts as necessary for specific conditions.High
69
Read and interpret work orders and instructions to determine work assignments, process specifications, and production schedules.High
68
Stop equipment and clear blockages or jams, using fingers, wire, or hand tools.High
65
Direct crane operators and crew members to load vessels with materials to be processed.Medium
70
Confer with supervisors or other equipment operators to report equipment malfunctions or to resolve production problems.High
68
Load equipment receptacles or conveyors with material to be processed, by hand or using hoists.High
67
Weigh or measure specified amounts of ingredients or materials for processing, using devices such as scales and calipers.Medium
69
Monitor equipment operation, gauges, and panel lights to detect deviations from standards.High
32
Melt or refine metal before casting, calculating required temperatures, and observe metal color, adjusting controls as necessary to maintain required temperatures.Medium
36
Examine or test samples of processed substances, or collect samples for laboratory testing, to ensure conformance to specifications.High
31
Remove products from equipment, manually or using hoists, and prepare them for storage, shipment, or additional processing.High
23
Transport materials and products to and from work areas, manually or using carts, handtrucks, or hoists.Medium
17
Most exposed

Where AI can do more

Routine, digitized, and highly repeatable tasks face the greatest pressure.

  1. Record gauge readings, test results, and shift production in log books.70
  2. Direct crane operators and crew members to load vessels with materials to be processed.70
  3. Calculate amounts of materials to be loaded into furnaces, adjusting amounts as necessary for specific conditions.69
  4. Weigh or measure specified amounts of ingredients or materials for processing, using devices such as scales and calipers.69
Hardest to automate

Where people still matter

These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.

  1. Transport materials and products to and from work areas, manually or using carts, handtrucks, or hoists.01
  2. Remove products from equipment, manually or using hoists, and prepare them for storage, shipment, or additional processing.02
  3. Monitor equipment operation, gauges, and panel lights to detect deviations from standards.03
  4. Examine or test samples of processed substances, or collect samples for laboratory testing, to ensure conformance to specifications.04
  5. Melt or refine metal before casting, calculating required temperatures, and observe metal color, adjusting controls as necessary to maintain required temperatures.05
Where else this work leads

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Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.

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Beyond AI capability

Adoption and labour-market outlook

Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.

Human dependency50
Physical dependency68
Adoption pressure51
Labour-market resilience60
Methodology & sources

O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.

Confidence83/100
CalculatedAug 21, 2026
Read methodology →