Industrial Engineering Technologists and Technicians
Architecture and Engineering Occupations- Código O*NET-SOC
- 17-3026.00
Apply engineering theory and principles to problems of industrial layout or manufacturing production, usually under the direction of engineering staff. May perform time and motion studies on worker operations in a variety of industries for purposes such as establishing standard production rates or improving efficiency.
Los nombres de las ocupaciones y las descripciones de tareas se muestran en inglés, tal como se publicaron. Las etiquetas, incluidos los tipos de tarea, están traducidas.
Exposición a la IA
- Fuente de datos: BLSPublicado: 2026-08
Alto· relativa
BajoCuatro bandas relativasMuy altoValor por grupo ocupacional
Escala, base y fuente
Cuatro bandas relativas (Bajo / Moderado / Alto / Muy alto)
831 ocupaciones detalladas de la tabla de proyecciones de empleo de BLS. El valor se asigna por código de la National Employment Matrix (NEM), de modo que las ocupaciones que comparten un código NEM reciben la misma banda
- Fuente de datos: AnthropicPublicado: 2026-03
0.000
0.000Rango de los valores aquí recogidos0.745Valor por grupo ocupacional
Escala, base y fuente
Índice de exposición observada, 0–1 tal como se publica
Mapeado sobre tareas de O*NET
Publicado por ocupación SOC 2018; toda ocupación O*NET con el mismo código SOC 2018 recibe este valor
- Fuente de datos: ILOPublicado: 2025
0.26
0.09Rango de los valores aquí recogidos0.70Valor por grupo ocupacional
Escala, base y fuente
Índice de exposición a la IA generativa, 0–1 tal como se publica
Publicado por grupo primario ISCO-08. Vinculado a esta ocupación, total o parcialmente, aplicando tal como se publicaron las tablas de correspondencia de la U.S. Bureau of Labor Statistics (ISCO-08 a SOC 2010, SOC 2010 a SOC 2018)
Qué tipo de cifra publica esta fuente
La categoría de BLS es un rango relativo, no un nivel absoluto, y tampoco es una medición de primera mano: agrupa en cuatro bandas los rangos percentiles de la ocupación en varios estudios publicados. No es una previsión de empleo ni de salarios, no es una probabilidad de adopción y no distingue entre automatización y aumento.
Exposición a la IA (rúbrica de OpenAI)
30 tareas evaluadas · 24 tareas con β ≥ 0,5 (80.0%)
β = exposición directa (E1) + 0,5 × exposición con herramientas disponibles (E2), según la definición del repositorio de origen.
- Unidad de origen: tareas de O*NET 27.2 → código de ocupación de O*NET 31.0
- Todas las tareas puntuadas figuran en la lista de tareas de O*NET 31.0.
- Fuente
- OpenAI "GPTs are GPTs" exposure rubric
- Versión
- gh-main-0471612
- Licencia
- MIT License, Copyright (c) 2024 OpenAI
Tareas
Descripciones de tareas de la O*NET® 31.0 Database, primero las tareas principales.
| Tarea | Tipo | β (OpenAI) |
|---|---|---|
| Study time, motion, methods, or speed involved in maintenance, production, or other operations to establish standard production rate or improve efficiency. | Principal | 0,5 |
| Read worker logs, product processing sheets, or specification sheets to verify that records adhere to quality assurance specifications. | Principal | 1 |
| Compile and evaluate statistical data to determine and maintain quality and reliability of products. | Principal | 0,5 |
| Test selected products at specified stages in the production process for performance characteristics or adherence to specifications. | Principal | 0 |
| Verify that equipment is being operated and maintained according to quality assurance standards by observing worker performance. | Principal | 0 |
| Adhere to all applicable regulations, policies, and procedures for health, safety, and environmental compliance. | Principal | 0,5 |
| Analyze, estimate, or report production costs. | Principal | 0,5 |
| Assist engineers in developing, building, or testing prototypes or new products, processes, or procedures. | Principal | 0,5 |
| Coordinate equipment purchases, installations, or transfers. | Principal | 0,5 |
| Create or interpret engineering drawings, schematic diagrams, formulas, or blueprints for management or engineering staff. | Principal | 0,5 |
| Develop or implement programs to address problems related to production, materials, safety, or quality. | Principal | 0,5 |
| Identify opportunities for improvements in quality, cost, or efficiency of automation equipment. | Principal | 0,5 |
| Monitor and adjust production processes or equipment for quality and productivity. | Principal | 0,5 |
| Oversee or inspect production processes. | Principal | 0,5 |
| Prepare layouts, drawings, or sketches of machinery or equipment, such as shop tooling, scale layouts, or new equipment design, using drafting equipment or computer-aided design (CAD) software. | Principal | 0,5 |
| Prepare production documents, such as standard operating procedures, manufacturing batch records, inventory reports, or productivity reports. | Principal | 1 |
| Provide advice or training to other technicians. | Principal | 1 |
| Recommend corrective or preventive actions to assure or improve product quality or reliability. | Principal | 0,5 |
| Select cleaning materials, tools, or equipment. | Principal | 0 |
| Select material quantities or processing methods needed to achieve efficient production. | Principal | 0,5 |
| Aid in planning work assignments in accordance with worker performance, machine capacity, production schedules, or anticipated delays. | Complementaria | 0,5 |
| Evaluate industrial operations for compliance with permits or regulations related to the generation, storage, treatment, transportation, or disposal of hazardous materials or waste. | Complementaria | 0,5 |
| Calibrate or adjust equipment to ensure quality production, using tools such as calipers, micrometers, height gauges, protractors, or ring gauges. | Complementaria | 0 |
| Conduct statistical studies to analyze or compare production costs for sustainable and nonsustainable designs. | Complementaria | 0,5 |
| Design plant layouts or production facilities. | Complementaria | 0,5 |
| Develop manufacturing infrastructure to integrate or deploy new manufacturing processes. | Complementaria | 0,5 |
| Develop production, inventory, or quality assurance programs. | Complementaria | 0,5 |
| Develop sustainable manufacturing technologies to reduce greenhouse gas emissions, minimize raw material use, replace toxic materials with non-toxic materials, replace non-renewable materials with renewable materials, or reduce waste. | Complementaria | 0,5 |
| Oversee equipment start-up, characterization, qualification, or release. | Complementaria | 0 |
| Set up and operate production equipment in accordance with current good manufacturing practices and standard operating procedures. | Complementaria | 0 |
Información ocupacional
Fuentes y atribución
This page includes information from the O*NET® 31.0 Database (https://www.onetcenter.org/database.html) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. AI Changing Work has modified all or some of this information: the O*NET-SOC code, title and task statements are reproduced in English without change; task-type labels are shown in the page's language and tasks are listed core first; any Korean occupation title shown on the Korean-language page is AI Changing Work's translation; any KSCO-8 unit groups linked to this occupation were paired with it by AI Changing Work's judgment, and the relation labels and statuses are AI Changing Work's additions. USDOL/ETA has not approved, endorsed, or tested these modifications.
Any AI exposure figures on this page are published by third parties, not by AI Changing Work, and none is part of the O*NET information. OpenAI publishes task-level scores (MIT License) for O*NET 27.2 task statements; each is shown next to the O*NET 31.0 task statement with the same task ID, whose wording can differ from the 27.2 statement that was scored. OpenAI also publishes occupation-level scores for O*NET-SOC codes in the same release, and any such score is shown on the O*NET occupation with the same code. Anthropic publishes an observed exposure index in the Anthropic Economic Index (CC-BY), and the U.S. Bureau of Labor Statistics publishes relative AI exposure categories (public domain); both are published per SOC code, and each value is shown on every O*NET occupation with that code. The International Labour Organization publishes a generative AI exposure index in ILO Working Paper 140 (CC BY 4.0) for ISCO-08 unit groups; AI Changing Work links those groups to O*NET occupations by applying the U.S. Bureau of Labor Statistics ISCO-08 to 2010 SOC and 2010 SOC to 2018 SOC crosswalks as published, without case-by-case selection, and these crosswalks match many groups only in part. Where several unit groups are linked, each group's published value is listed, and any summary shows only the lowest and highest of those values with the number of groups; no exposure figure is averaged or recalculated. Any employment figures are published by the U.S. Bureau of Labor Statistics for the SOC group containing this occupation. Each source is credited where its figures are shown.
O*NET OnLine: 17-3026.00 Industrial Engineering Technologists and Technicians
KSCO 코드·명칭: 한국표준직업분류(제8차 개정) — 통계청 고시 제2024-328호 (2024-07-01 고시, 2025-01-01 시행). 저작권법 제7조 제2호의 고시 항목이다. 명칭 표기(가운뎃점·띄어쓰기)는 해설서 2차 정오 반영판의 표기를 따랐으며, 고시 항목표와는 18개 명칭에서 가운뎃점 글리프나 띄어쓰기만 다르다. 통계청은 2025년 10월 국가데이터처로 개편되었다. 이 페이지의 KSCO 연결은 통계청·국가데이터처의 공식 연계표가 아니다.