# Extruding and Drawing Machine Setters, Operators, and Tenders, Metal and Plastic

> Set up, operate, or tend machines to extrude or draw thermoplastic or metal materials into tubes, rods, hoses, wire, bars, or structural shapes.

- **SOC code:** 51-4021.00
- **Canonical URL:** https://singulariki.com/roles/role-51-4021-00
- **Also known as:** Equipment Technician, Extruder Operator, Extrusion Press Operator, Machine Operator, Extrusion Operator, Metal Inspector, Setup Operator, Wire Mill Operator
- **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 and examine extruded products to locate defects and to check for conformance to specifications, adjusting controls as necessary to alter products.
- Determine setup procedures and select machine dies and parts, according to specifications.
- Start machines and set controls to regulate vacuum, air pressure, sizing rings, and temperature, and to synchronize speed of extrusion.
- Reel extruded products into rolls of specified lengths and weights.
- Install dies, machine screws, and sizing rings on machines that extrude thermoplastic or metal materials.
- Change dies on extruding machines, according to production line changes.
- Clean work areas.
- Weigh and mix pelletized, granular, or powdered thermoplastic materials and coloring pigments.
- Test physical properties of products with testing devices such as acid-bath testers, burst testers, and impact testers.
- Load machine hoppers with mixed materials, using augers, or stuff rolls of plastic dough into machine cylinders.
- Troubleshoot, maintain, and make minor repairs to equipment.
- Maintain an inventory of materials.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Production and Processing _(knowledge)_
- Control Precision _(ability)_
- Manual Dexterity _(ability)_
- Multilimb Coordination _(ability)_
- Reaction Time _(ability)_
- Operations Monitoring _(transferable_skill)_
- Mathematics _(knowledge)_
- English Language _(knowledge)_
- Operation and Control _(transferable_skill)_
- Problem Sensitivity _(ability)_
- Rate Control _(ability)_
- Near Vision _(ability)_

**Skills in demand:**
- Mathematics _(Common Skill)_
- English Language _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Critical Thinking _(Common Skill)_
- Visualization _(Specialized Skill)_
- Speech Recognition _(Specialized Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft PowerPoint _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Finger Dexterity _(Common Skill)_
- Deductive Reasoning _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Word _(hot technology)_
- SAP software _(hot technology)_
- Enterprise application integration EAI software
- Operational databases

## AI exposure & outlook

- **AI task-overlap index:** 18th 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):** 7th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 48th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 81st percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 1.2% growth (About average); 6.5k annual openings; 66k → 66.8k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $46,980; 65,700 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/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **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-51-4021-00_