# Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic

> Set up, operate, or tend grinding and related tools that remove excess material or burrs from surfaces, sharpen edges or corners, or buff, hone, or polish metal or plastic work pieces.

- **SOC code:** 51-4033.00
- **Canonical URL:** https://singulariki.com/roles/role-51-4033-00
- **Also known as:** Centerless Grinder Operator, Grinder, Grinder Operator, Grinding Machine Operator, Cell Operator, Deburrer, Die Maintenance Technician, Finisher
- **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):
- Inspect or measure finished workpieces to determine conformance to specifications, using measuring instruments, such as gauges or micrometers.
- Measure workpieces and lay out work, using precision measuring devices.
- Observe machine operations to detect any problems, making necessary adjustments to correct problems.
- Move machine controls to index workpieces, and to adjust machines for pre-selected operational settings.
- Study blueprints, work orders, or machining instructions to determine product specifications, tool requirements, and operational sequences.
- Select machine tooling to be used, using knowledge of machine and production requirements.
- Compute machine indexings and settings for specified dimensions and base reference points.
- Mount and position tools in machine chucks, spindles, or other tool holding devices, using hand tools.
- Set up, operate, or tend grinding and related tools that remove excess material or burrs from surfaces, sharpen edges or corners, or buff, hone, or polish metal or plastic workpieces.
- Set and adjust machine controls according to product specifications, using knowledge of machine operation.
- Activate machine start-up switches to grind, lap, hone, debar, shear, or cut workpieces, according to specifications.
- Brush or spray lubricating compounds on workpieces, or turn valve handles and direct flow of coolant against tools and workpieces.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Operations Monitoring _(transferable_skill)_
- Operation and Control _(transferable_skill)_
- Control Precision _(ability)_
- Manual Dexterity _(ability)_
- Near Vision _(ability)_
- Problem Sensitivity _(ability)_
- Reaction Time _(ability)_
- Quality Control Analysis _(transferable_skill)_
- Arm-Hand Steadiness _(ability)_
- Multilimb Coordination _(ability)_
- Production and Processing _(knowledge)_
- Perceptual Speed _(ability)_

**Skills in demand:**
- Visualization _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Finger Dexterity _(Common Skill)_
- Depth Perception _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Microsoft Windows _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Mathematics _(Common Skill)_
- Complex Problem Solving _(Common Skill)_

**Tools & technology:**
- Autodesk AutoCAD _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Windows _(hot technology)_
- SAP software _(hot technology)_
- Manufacturing reporting system
- Mazak Mazatrol SMART CNC

## 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.):** 18th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 14th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 32nd percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 89th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -12.0% growth (Declining); 5.5k annual openings; 70.1k → 61.7k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $45,190; 70,110 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-51-4033-00_