70
/100

SOC 51-4023

Rolling Machine Setters, Operators, and Tenders, Metal and Plastic

High RiskFrey/Osborne: 83.0%

Risk Score

โš ๏ธ

70/100

High Risk

US Employment

๐Ÿ‘ฅ

22,350

Total workers

Median Wage

๐Ÿ’ฐ

$49K

$37K โ€“ $68K

Projected Growth

๐Ÿ“ˆ

-8.3%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

53/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Rolling Machine Setters, Operators, and Tenders, Metal and Plastic face a risk score of 70/100 โ€” 26 points above the national average of 44. With 53/100 GenAI exposure, this occupation faces significant pressure from AI tools despite weak projected growth. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $49K ($2K above the national median). The 3 recommended career transitions all maintain competitive wages while reducing automation exposure. Explore transition paths โ†’

๐Ÿ” AI Impact Analysis

With a risk score of 70/100, Rolling Machine Setters, Operators, and Tenders, Metal and Plastic faces significant automation pressure. Key threats include smart factory scheduling and production optimization and automated cnc programming and machine operation. The 22,350 Americans in this role should actively develop skills in troubleshooting complex equipment malfunctions and setup and calibration of custom production runs to remain competitive. Workers who proactively adapt will find new opportunities even as traditional tasks are automated.

Will AI Replace Rolling Machine Setters, Operators, and Tenders, Metal and Plastic?

Read our full analysis with verdict, risk factors, safe tasks, and career transition paths โ†’

โš ๏ธ Top Risk Factors

1

Smart factory scheduling and production optimization

2

Automated CNC programming and machine operation

3

Industrial robotics replacing manual assembly tasks

4

AI quality inspection via computer vision systems

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Troubleshooting complex equipment malfunctions

โœ“

Setup and calibration of custom production runs

โœ“

Coordinating workflow across diverse production teams

๐Ÿ“Š Task Automation Breakdown

Based on O*NET task analysis and GenAI exposure scoring. Shows the estimated proportion of this occupation's core tasks that are automatable by current AI, augmented by AI tools, or require essential human skills.

๐Ÿ“‹ O*NET Task Profile

โ€ข

Monitor machine cycles and mill operation to detect jamming and to ensure that products conform to specifications.

โ€ข

Adjust and correct machine set-ups to reduce thicknesses, reshape products, and eliminate product defects.

โ€ข

Start operation of rolling and milling machines to flatten, temper, form, and reduce sheet metal sections and to produce steel strips.

โ€ข

Examine, inspect, and measure raw materials and finished products to verify conformance to specifications.

โ€ข

Read rolling orders, blueprints, and mill schedules to determine setup specifications, work sequences, product dimensions, and installation procedures.

๐Ÿ’ป Technology Skills

โ€ข

Electronic mail software

โ€ข

Internet browser software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Mechanical

โ€ข

Production and Processing

โ€ข

English Language

โ€ข

Education and Training

โ€ข

Administration and Management

๐Ÿ“Š vs National Average

Median Wage$49K
+$2K

National avg: $46K

Risk Score70/100
+26

National avg: 44/100

GenAI Exposure53/100
+15

National avg: 38/100

Projected Growth-8.3%
-12.0%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Engineers20$106K65%
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors25$62K55%
Fabric and Apparel Patternmakers33$68K74%