Inspectors, Testers, Sorters, Samplers, and Weighers

Production Occupations
رمز O*NET-SOC
51-9061.00

Inspect, test, sort, sample, or weigh nonagricultural raw materials or processed, machined, fabricated, or assembled parts or products for defects, wear, and deviations from specifications. May use precision measuring instruments and complex test equipment.

تُعرض أسماء المهن وأوصاف المهام بالإنجليزية كما نُشرت. أما التسميات، ومنها أنواع المهام، فمترجمة.

التعرّض للذكاء الاصطناعي

  • مصدر البيانات: BLSتاريخ النشر: 2026-08

    متوسط· نسبي

    منخفضأربع فئات نسبيةمرتفع جدًا

    قيمة على مستوى المجموعة المهنية

    المقياس والأساس والمصدر

    أربع فئات نسبية (منخفض / متوسط / مرتفع / مرتفع جدًا)

    831 مهنة تفصيلية في جدول توقعات التوظيف لدى BLS. وتُسند القيمة على مستوى رمز مصفوفة التوظيف الوطنية (NEM)، فالمهن التي تشترك في الرمز نفسه تأخذ النطاق نفسه

    مجموعة البيانات المصدر (تنزيل ملف XLSX)

  • مصدر البيانات: Anthropicتاريخ النشر: 2026-03

    0.032

    0.000نطاق القيم المعروضة هنا0.745
    المقياس والأساس والمصدر

    مؤشر التعرّض المرصود، 0–1 كما نُشر

    مربوط بمهام O*NET

    منشورة لكل مهنة في SOC 2018؛ وكل مهنة في O*NET تحمل رمز SOC 2018 نفسه تأخذ هذه القيمة

    مجموعة البيانات المصدر (تنزيل ملف CSV)

  • مصدر البيانات: ILOتاريخ النشر: 2025

    0.31

    0.09نطاق القيم المعروضة هنا0.70

    قيمة على مستوى المجموعة المهنية

    المقياس والأساس والمصدر

    مؤشر التعرّض للذكاء الاصطناعي التوليدي، 0–1 كما نُشر

    قيمة منشورة على مستوى مجموعة الوحدة في ISCO-08. رُبطت بهذه المهنة بتطبيق جداول التناظر الرسمية لمكتب إحصاءات العمل الأمريكي (BLS) (من ISCO-08 إلى SOC 2010، ومن SOC 2010 إلى SOC 2018) كما نُشرت، والتناظر كلي أو جزئي

    مجموعة البيانات المصدر (تنزيل ملف PDF)

ما نوع القيمة التي ينشرها هذا المصدر

فئة BLS رتبة نسبية لا مستوى مطلق، وليست قياسًا مباشرًا: فهي تجمع الرتب المئينية للمهنة في عدة دراسات منشورة في أربع فئات. وهي ليست توقّعًا للتوظيف أو الأجور، ولا احتمالًا للتبني، ولا تفرّق بين الأتمتة والتعزيز.

التعرض للذكاء الاصطناعي (معيار OpenAI)

32 مهمة مقيَّمة · 18 مهمة بقيمة β ≥ 0.5 (56.3%)

β = التعرّض المباشر (E1) + 0.5 × التعرّض عند توفر الأدوات (E2)، وفق تعريف المستودع المصدري.

  • وحدة المصدر: مهام O*NET 27.2 ← رمز المهنة في O*NET 31.0
  • عدد المهام المقيَّمة غير الموجودة في قائمة مهام O*NET 31.0: 1؛ وتبقى درجاتها كما نُشرت وفق O*NET 27.2.
المصدر
OpenAI "GPTs are GPTs" exposure rubric
الإصدار
gh-main-0471612
الترخيص
MIT License, Copyright (c) 2024 OpenAI

المهام

أوصاف المهام من O*NET® 31.0 Database، والمهام الأساسية أولًا.

المهمةالنوعβ (OpenAI)
Discard or reject products, materials, or equipment not meeting specifications.أساسية0
Inspect, test, or measure materials, products, installations, or work for conformance to specifications.أساسية0.5
Record inspection or test data, such as weights, temperatures, grades, or moisture content, and quantities inspected or graded.أساسية1
Mark items with details, such as grade or acceptance-rejection status.أساسية1
Measure dimensions of products to verify conformance to specifications, using measuring instruments, such as rulers, calipers, gauges, or micrometers.أساسية0
Collect or select samples for testing or for use as models.أساسية0
Write test or inspection reports describing results, recommendations, or needed repairs.أساسية1
Read dials or meters to verify that equipment is functioning at specified levels.أساسية0.5
Remove defects, such as chips, burrs, or lap corroded or pitted surfaces.أساسية0
Make minor adjustments to equipment, such as turning setscrews to calibrate instruments to required tolerances.أساسية0
Read blueprints, data, manuals, or other materials to determine specifications, inspection and testing procedures, adjustment methods, certification processes, formulas, or measuring instruments required.أساسية1
Notify supervisors or other personnel of production problems.أساسية1
Recommend necessary corrective actions, based on inspection results.أساسية0.5
Position products, components, or parts for testing.أساسية0
Stack or arrange tested products for further processing, shipping, or packaging.أساسية0
Monitor production operations or equipment to ensure conformance to specifications, making necessary process or assembly adjustments.أساسية0.5
Analyze test data, making computations as necessary, to determine test results.تكميلية1
Compare colors, shapes, textures, or grades of products or materials with color charts, templates, or samples to verify conformance to standards.تكميلية0.5
Adjust, clean, or repair products or processing equipment to correct defects found during inspections.تكميلية0
Fabricate, install, position, or connect components, parts, finished products, or instruments for testing or operational purposes.تكميلية0
Grade, classify, or sort products according to sizes, weights, colors, or other specifications.تكميلية0.5
Interpret legal requirements, provide safety information, or recommend compliance procedures to contractors, craft workers, engineers, or property owners.تكميلية0.5
Inspect or test raw materials, parts, or products to determine compliance with environmental standards.تكميلية0
Clean, maintain, calibrate, or repair measuring instruments or test equipment, such as dial indicators, fixed gauges, or height gauges.تكميلية0
Check arriving materials to ensure that they match purchase orders, submitting discrepancy reports as necessary.تكميلية0.5
Compute defect percentages or averages, using formulas and calculators.تكميلية1
Monitor machines that automatically measure, sort, or inspect products.تكميلية0.5
Compute usable amounts of items in shipments.تكميلية1
Weigh materials, products, containers, or samples to verify packaging weights or ingredient quantities.تكميلية0
Disassemble defective parts or components, such as inaccurate or worn gauges or measuring instruments.تكميلية0
Administer tests to assess whether engineers or operators are qualified to use equipment.تكميلية0.5

معلومات مهنية

المصادر والإسناد

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: 51-9061.00 Inspectors, Testers, Sorters, Samplers, and Weighers

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.

الإسناد والتراخيص كاملة