# Patternmakers, Wood

> Plan, lay out, and construct wooden unit or sectional patterns used in forming sand molds for castings.

- **SOC code:** 51-7032.00
- **Canonical URL:** https://singulariki.com/roles/role-51-7032-00
- **Also known as:** Mold Maker, Pattern Maker, Patternmaker, Wood Pattern Maker, Pattern Engineer, Wood Patternmaker, Wood Shop Moldmaker, Woodshop Worker
- **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 blueprints, drawings, or written specifications to determine sizes and shapes of patterns and required machine setups.
- Fit, fasten, and assemble wood parts together to form patterns, models, or sections, using glue, nails, dowels, bolts, and screws.
- Lay out patterns on wood stock and draw outlines of units, sectional patterns, or full-scale mock-ups of products, based on blueprint specifications and sketches, and using marking and measuring devices.
- Trim, smooth, and shape surfaces, and plane, shave, file, scrape, and sand models to attain specified shapes, using hand tools.
- Verify dimensions of completed patterns, using templates, straightedges, calipers, or protractors.
- Divide patterns into sections according to shapes of castings to facilitate removal of patterns from molds.
- Correct patterns to compensate for defects in castings.
- Set up, operate, and adjust a variety of woodworking machines such as bandsaws and lathes to cut and shape sections, parts, and patterns, according to specifications.
- Finish completed products or models with shellac, lacquer, wax, or paint.
- Mark identifying information such as colors or codes on patterns, parts, and templates to indicate assembly methods.
- Estimate costs for patternmaking jobs.
- Repair broken or damaged patterns.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Mathematics _(knowledge)_
- Manual Dexterity _(ability)_
- Arm-Hand Steadiness _(ability)_
- Control Precision _(ability)_
- Near Vision _(ability)_
- Design _(knowledge)_
- Engineering and Technology _(knowledge)_
- Mechanical _(knowledge)_
- Reaction Time _(ability)_
- Finger Dexterity _(ability)_
- Building and Construction _(knowledge)_
- Administration and Management _(knowledge)_

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

**Tools & technology:**
- Autodesk AutoCAD _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- 3D Systems Geomagic Design X
- Delcam PowerMILL
- Mastercam computer-aided design and manufacturing software

## 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.):** 16th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 33rd percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 40th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 81st percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -5.0% growth (Declining); 0k annual openings; 0.5k → 0.4k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $52,520; 180 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 62% automation, 30% augmentation (usage-weighted).
- **Autonomy median:** 2.5 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- Compute dimensions, areas, volumes, and weights. _(4.3% of measured AI use; directive)_
- Verify dimensions of completed patterns, using templates, straightedges, calipers, or protractors. _(0.3% of measured AI use; directive)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me compute dimensions, areas, volumes, and weights.
- Help me verify dimensions of completed patterns, using templates, straightedges, calipers, or protractors.

## 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/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **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-51-7032-00_