# Electromechanical Equipment Assemblers

> Assemble or modify electromechanical equipment or devices, such as servomechanisms, gyros, dynamometers, magnetic drums, tape drives, brakes, control linkage, actuators, and appliances.

- **SOC code:** 51-2023.00
- **Canonical URL:** https://singulariki.com/roles/role-51-2023-00
- **Also known as:** Assembler, Electronic Assembler, Electronic Technician, Mechanical Assembler, Electrical Assembler, Electromechanical Assembler, Electromechanical Equipment Assembler, Electronics Assembler
- **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, test, and adjust completed units to ensure that units meet specifications, tolerances, and customer order requirements.
- Position, align, and adjust parts for proper fit and assembly.
- Assemble parts or units, and position, align, and fasten units to assemblies, subassemblies, or frames, using hand tools and power tools.
- Connect cables, tubes, and wiring, according to specifications.
- Measure parts to determine tolerances, using precision measuring instruments such as micrometers, calipers, and verniers.
- Read blueprints and specifications to determine component parts and assembly sequences of electromechanical units.
- Attach name plates and mark identifying information on parts.
- File, lap, and buff parts to fit, using hand and power tools.
- Disassemble units to replace parts or to crate them for shipping.
- Clean and lubricate parts and subassemblies, using grease paddles or oilcans.
- Drill, tap, ream, countersink, and spot-face bolt holes in parts, using drill presses and portable power drills.
- Operate or tend automated assembling equipment, such as robotics and fixed automation equipment.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Arm-Hand Steadiness _(ability)_
- Finger Dexterity _(ability)_
- Near Vision _(ability)_
- Manual Dexterity _(ability)_
- Production and Processing _(knowledge)_
- Operations Monitoring _(transferable_skill)_
- Quality Control Analysis _(transferable_skill)_
- Problem Sensitivity _(ability)_
- Information Ordering _(ability)_
- Control Precision _(ability)_
- Mechanical _(knowledge)_
- Deductive Reasoning _(ability)_

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

**Tools & technology:**
- Autodesk AutoCAD _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Word _(hot technology)_
- SAP software _(hot technology)_
- Blueprint display software
- Timekeeping 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.):** 35th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 13th percentile (Low) — source: eloundou_gamma.
- **Frey–Osborne (2013, historical computerization estimate):** 94th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.

## How people actually use AI here

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

- **Automation vs augmentation:** 46% automation, 24% augmentation (usage-weighted).
- **Autonomy median:** 3.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- Measure parts to determine tolerances, using precision measuring instruments such as micrometers, calipers, and verniers. _(0.7% of measured AI use; directive)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me measure parts to determine tolerances, using precision measuring instruments such as micrometers, calipers, and verniers.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **“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-51-2023-00_