# Lathe and Turning Machine Tool Setters, Operators, and Tenders, Metal and Plastic

> Set up, operate, or tend lathe and turning machines to turn, bore, thread, form, or face metal or plastic materials, such as wire, rod, or bar stock.

- **SOC code:** 51-4034.00
- **Canonical URL:** https://singulariki.com/roles/role-51-4034-00
- **Also known as:** CNC Lathe Operator (Computer Numerical Control Lathe Operator), Lathe Operator, Machine Operator, Setup Operator, CNC Setup Operator (Computer Numerical Control Setup Operator), Numerical Control Operator (NC Operator), Screw Machine Operator, Screw Machine Tool Setter
- **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):
- Adjust machine controls and change tool settings to keep dimensions within specified tolerances.
- Move controls to set cutting speeds and depths and feed rates, and to position tools in relation to workpieces.
- Study blueprints, layouts or charts, and job orders for information on specifications and tooling instructions, and to determine material requirements and operational sequences.
- Inspect sample workpieces to verify conformance with specifications, using instruments such as gauges, micrometers, and dial indicators.
- Replace worn tools, and sharpen dull cutting tools and dies, using bench grinders or cutter-grinding machines.
- Move toolholders manually or by turning handwheels, or engage automatic feeding mechanisms to feed tools to and along workpieces.
- Compute unspecified dimensions and machine settings, using knowledge of metal properties and shop mathematics.
- Crank machines through cycles, stopping to adjust tool positions and machine controls to ensure specified timing, clearances, and tolerances.
- Position, secure, and align cutting tools in toolholders on machines, using hand tools, and verify their positions with measuring instruments.
- Start lathe or turning machines and observe operations to ensure that specifications are met.
- Program computer numerical control machines.
- Refill, change, and monitor the level of fluids, such as oil and coolant, in machines.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Production and Processing _(knowledge)_
- Arm-Hand Steadiness _(ability)_
- Control Precision _(ability)_
- Mechanical _(knowledge)_
- Engineering and Technology _(knowledge)_
- Operations Monitoring _(transferable_skill)_
- Near Vision _(ability)_
- Operation and Control _(transferable_skill)_
- Education and Training _(knowledge)_
- Administration and Management _(knowledge)_
- Customer and Personal Service _(knowledge)_
- Finger Dexterity _(ability)_

**Skills in demand:**
- Finger Dexterity _(Common Skill)_
- English Language _(Common Skill)_
- Mathematics _(Common Skill)_
- Visualization _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Equipment Maintenance _(Specialized Skill)_
- Deductive Reasoning _(Common Skill)_
- Active Listening _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Time Management _(Common Skill)_
- Speech Recognition _(Specialized Skill)_

**Tools & technology:**
- Autodesk HSMWorks
- Computer numerical control CNC editor software
- G-code
- Inventory tracking software
- M-code

## AI exposure & outlook

- **AI task-overlap index:** 28th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 15th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 24th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 49th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 69th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -13.6% growth (Declining); 1.5k annual openings; 18.9k → 16.4k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $48,620; 18,970 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

---
_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-51-4034-00_