# Refractory Materials Repairers, Except Brickmasons

> Build or repair equipment such as furnaces, kilns, cupolas, boilers, converters, ladles, soaking pits, and ovens, using refractory materials.

- **SOC code:** 49-9045.00
- **Canonical URL:** https://singulariki.com/roles/role-49-9045-00
- **Also known as:** Cupola Repairer, Ladle Liner, Refractory Bricklayer, Refractory Technician, Cell Reliner, Furnace Repairer, Hot Repairman, Ladle Repairman
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Measure furnace walls to determine dimensions and cut required number of sheets from plastic block, using saws.
- Reline or repair ladles and pouring spouts with refractory clay, using trowels.
- Dry and bake new linings by placing inverted linings over burners, building fires in ladles, or by using blowtorches.
- Remove worn or damaged plastic block refractory linings of furnaces, using hand tools.
- Chip slag from linings of ladles or remove linings when beyond repair, using hammers and chisels.
- Climb scaffolding, carrying hoses, and spray surfaces of cupolas with refractory mixtures, using spray equipment.
- Mix specified amounts of sand, clay, mortar powder, and water to form refractory clay or mortar, using shovels or mixing machines.
- Spread mortar on stopper heads and rods, using trowels, and slide brick sleeves over rods to form refractory jackets.
- Dump and tamp clay in molds, using tamping tools.
- Transfer clay structures to curing ovens, melting tanks, and drawing kilns, using forklifts.

**Emerging tasks** (O*NET):
- Reline furnaces using ramming material.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Arm-Hand Steadiness _(ability)_
- Mechanical _(knowledge)_
- Extent Flexibility _(ability)_
- Near Vision _(ability)_
- Oral Comprehension _(ability)_
- Manual Dexterity _(ability)_
- Control Precision _(ability)_
- Multilimb Coordination _(ability)_
- Operations Monitoring _(transferable_skill)_
- Trunk Strength _(ability)_
- Gross Body Equilibrium _(ability)_
- Oral Expression _(ability)_

**Skills in demand:**
- Speech Recognition _(Specialized Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft PowerPoint _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Microsoft Access _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- Finger Dexterity _(Common Skill)_
- Equipment Maintenance _(Specialized Skill)_
- Deductive Reasoning _(Common Skill)_
- Active Listening _(Common Skill)_
- Visualization _(Specialized Skill)_

**Tools & technology:**
- Microsoft Access _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Word _(hot technology)_
- Maintenance management software
- Time tracking software

## AI exposure & outlook

- **AI task-overlap index:** 9th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 9th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 3rd percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 27th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 66th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -16.9% growth (Declining); 0.1k annual openings; 1.1k → 0.9k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $58,540; 1,100 employed.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-49-9045-00_