# Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic

> Set up, operate, or tend milling or planing machines to mill, plane, shape, groove, or profile metal or plastic work pieces.

- **SOC code:** 51-4035.00
- **Canonical URL:** https://singulariki.com/roles/role-51-4035-00
- **Also known as:** CNC Licensed Mill Operator (Computer Numerical Control Licensed Mill Operator), CNC Mill Operator (Computerized Numerical Control Mill Operator), Machine Operator, Mill Operator, CNC Mill Operator (Computer Numerical Control Mill Operator), CNC Mill Set Up Operator (Computerized Numerical Control Mill Set Up Operator), Machine Set Up Operator, Miller
- **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):
- Remove workpieces from machines, and check to ensure that they conform to specifications, using measuring instruments such as microscopes, gauges, calipers, and micrometers.
- Verify alignment of workpieces on machines, using measuring instruments such as rules, gauges, or calipers.
- Move controls to set cutting specifications, to position cutting tools and workpieces in relation to each other, and to start machines.
- Observe milling or planing machine operation, and adjust controls to ensure conformance with specified tolerances.
- Select and install cutting tools and other accessories according to specifications, using hand tools or power tools.
- Position and secure workpieces on machines, using holding devices, measuring instruments, hand tools, and hoists.
- Study blueprints, layouts, sketches, or work orders to assess workpiece specifications and to determine tooling instructions, tools and materials needed, and sequences of operations.
- Replace worn tools, using hand tools, and sharpen dull tools, using bench grinders.
- Compute dimensions, tolerances, and angles of workpieces or machines according to specifications and knowledge of metal properties and shop mathematics.
- Move cutters or material manually or by turning handwheels, or engage automatic feeding mechanisms to mill workpieces to specifications.
- Mount attachments and tools, such as pantographs, engravers, or routers, to perform other operations, such as drilling or boring.
- Select cutting speeds, feed rates, and depths of cuts, applying knowledge of metal properties and shop mathematics.

## Skills, tools, capabilities

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

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

**Tools & technology:**
- Autodesk AutoCAD _(hot technology)_
- Extensible markup language XML _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Word _(hot technology)_
- EditCNC
- G-code
- Kentech machine shop software
- M-code
- Mastercam computer-aided design and manufacturing software
- Siemens Solid Edge

## AI exposure & outlook

- **AI task-overlap index:** 29th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 23rd percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 30th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 41st percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 97th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -14.4% growth (Declining); 1.1k annual openings; 13.8k → 11.8k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $48,310; 13,810 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-51-4035-00_