55
/100

SOC 51-4021

Extruding and Drawing Machine Setters, Operators, and Tenders, Metal and Plastic

ElevatedFrey/Osborne: 91.0%

Risk Score

โš ๏ธ

55/100

Elevated

US Employment

๐Ÿ‘ฅ

65,700

Total workers

Median Wage

๐Ÿ’ฐ

$47K

$35K โ€“ $62K

Projected Growth

๐Ÿ“ˆ

+1.2%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

10/100

Low exposure

How we calculate these numbers โ†’

๐Ÿ’ก Extruding and Drawing Machine Setters, Operators, and Tenders, Metal and Plastic face a risk score of 55/100 โ€” 11 points above the national average of 44. With only 10/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $47K ($670 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 55/100, Extruding and Drawing Machine Setters, Operators, and Tenders, Metal and Plastic faces moderate automation pressure. While tasks like industrial robotics replacing manual assembly tasks are increasingly handled by AI, the role retains significant human elements. The 65,700 workers in this occupation should focus on strengthening skills in setup and calibration of custom production runs and coordinating workflow across diverse production teams to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Extruding and Drawing 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

Industrial robotics replacing manual assembly tasks

2

Predictive maintenance reducing manual inspection roles

3

Smart factory scheduling and production optimization

4

Cobots handling repetitive material handling tasks

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Setup and calibration of custom production runs

โœ“

Coordinating workflow across diverse production teams

โœ“

Troubleshooting complex equipment malfunctions

โœ“

Quality judgment requiring tactile and visual inspection

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

Measure and examine extruded products to locate defects and to check for conformance to specifications, adjusting controls as necessary to alter products.

โ€ข

Determine setup procedures and select machine dies and parts, according to specifications.

โ€ข

Start machines and set controls to regulate vacuum, air pressure, sizing rings, and temperature, and to synchronize speed of extrusion.

โ€ข

Reel extruded products into rolls of specified lengths and weights.

โ€ข

Install dies, machine screws, and sizing rings on machines that extrude thermoplastic or metal materials.

๐Ÿ’ป Technology Skills

โ€ข

Enterprise application integration software

โ€ข

Spreadsheet software

โ€ข

Office suite software

โ€ข

Electronic mail software

โ€ข

Presentation software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Production and Processing

โ€ข

Mathematics

โ€ข

English Language

โ€ข

Administration and Management

โ€ข

Computers and Electronics

๐Ÿ“Š vs National Average

Median Wage$47K
+$670

National avg: $46K

Risk Score55/100
+11

National avg: 44/100

GenAI Exposure10/100
-28

National avg: 38/100

Projected Growth1.2%
-2.5%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

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