# Forging Machine Setters, Operators, and Tenders, Metal and Plastic

> Set up, operate, or tend forging machines to taper, shape, or form metal or plastic parts.

- **SOC code:** 51-4022.00
- **Canonical URL:** https://singulariki.com/roles/role-51-4022-00
- **Also known as:** Blacksmith, Forge Operator, Hammer Operator, Machine Operator, Cold Header Operator, Forge Press Operator, Forger, Header Set-Up 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):
- Read work orders or blueprints to determine specified tolerances and sequences of operations for machine setup.
- Position and move metal wires or workpieces through a series of dies that compress and shape stock to form die impressions.
- Measure and inspect machined parts to ensure conformance to product specifications.
- Set up, operate, or tend presses and forging machines to perform hot or cold forging by flattening, straightening, bending, cutting, piercing, or other operations to taper, shape, or form metal.
- Turn handles or knobs to set pressures and depths of ram strokes and to synchronize machine operations.
- Install, adjust, and remove dies, synchronizing cams, forging hammers, and stop guides, using overhead cranes or other hoisting devices, and hand tools.
- Start machines to produce sample workpieces, and observe operations to detect machine malfunctions and to verify that machine setups conform to specifications.
- Confer with other workers about machine setups and operational specifications.
- Trim and compress finished forgings to specified tolerances.
- Remove dies from machines when production runs are finished.
- Repair, maintain, and replace parts on dies.
- Select, align, and bolt positioning fixtures, stops, and specified dies to rams and anvils, forging rolls, or presses and hammers.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Production and Processing _(knowledge)_
- Mathematics _(knowledge)_
- Education and Training _(knowledge)_
- Near Vision _(ability)_
- Mechanical _(knowledge)_
- Oral Comprehension _(ability)_
- Operations Monitoring _(transferable_skill)_
- Written Comprehension _(ability)_
- Oral Expression _(ability)_
- Problem Sensitivity _(ability)_
- Information Ordering _(ability)_
- Arm-Hand Steadiness _(ability)_

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

**Tools & technology:**
- Email software
- Inventory tracking software
- Machine control software

## AI exposure & outlook

- **AI task-overlap index:** 22nd percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 25th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 12th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 36th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 84th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -18.9% growth (Declining); 0.6k annual openings; 8.8k → 7.2k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $49,240; 8,760 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-51-4022-00_