# Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic

> Set up, operate, or tend metal or plastic molding, casting, or coremaking machines to mold or cast metal or thermoplastic parts or products.

- **SOC code:** 51-4072.00
- **Canonical URL:** https://singulariki.com/roles/role-51-4072-00
- **Also known as:** Machine Operator, Molder, Process Technician, Production Technician, Core Machine Operator, Die Cast Technician, Diecast Machine Operator, Mold 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):
- Measure and visually inspect products for surface and dimension defects to ensure conformance to specifications, using precision measuring instruments.
- Observe continuous operation of automatic machines to ensure that products meet specifications and to detect jams or malfunctions, making adjustments as necessary.
- Set up, operate, or tend metal or plastic molding, casting, or coremaking machines to mold or cast metal or thermoplastic parts or products.
- Turn valves and dials of machines to regulate pressure, temperature, and speed and feed rates, and to set cycle times.
- Read specifications, blueprints, and work orders to determine setups, temperatures, and time settings required to mold, form, or cast plastic materials, as well as to plan production sequences.
- Observe meters and gauges to verify and record temperatures, pressures, and press-cycle times.
- Connect water hoses to cooling systems of dies, using hand tools.
- Cool products after processing to prevent distortion.
- Remove parts, such as dies, from machines after production runs are finished.
- Operate hoists to position dies or patterns on foundry floors.
- Install dies onto machines or presses and coat dies with parting agents, according to work order specifications.
- Unload finished products from conveyor belts, pack them in containers, and place containers in warehouses.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Arm-Hand Steadiness _(ability)_
- Manual Dexterity _(ability)_
- Production and Processing _(knowledge)_
- Mechanical _(knowledge)_
- Operations Monitoring _(transferable_skill)_
- Control Precision _(ability)_
- Multilimb Coordination _(ability)_
- Active Listening _(essential_skill)_
- Deductive Reasoning _(ability)_
- Information Ordering _(ability)_
- Perceptual Speed _(ability)_
- Near Vision _(ability)_

**Skills in demand:**
- Information Ordering _(Specialized Skill)_
- Deductive Reasoning _(Common Skill)_
- Active Listening _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Finger Dexterity _(Common Skill)_
- Mathematics _(Common Skill)_
- Visualization _(Specialized Skill)_
- Time Management _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft Word _(hot technology)_
- SAP software _(hot technology)_
- FANUC Robotics iRVision
- HotFlo! Die-Shot Monitor
- Intera Systems Hawk-i
- RobotWare DieCast
- Visi-Trak True-Trak 20/20

## AI exposure & outlook

- **AI task-overlap index:** 14th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 13th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 19th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 18th 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):** -3.8% growth (Declining); 15.9k annual openings; 154.6k → 148.8k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $41,230; 154,820 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-51-4072-00_