78
/100

SOC 51-4035

Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic

High RiskFrey/Osborne: 98.0%

Risk Score

โš ๏ธ

78/100

High Risk

US Employment

๐Ÿ‘ฅ

13,810

Total workers

Median Wage

๐Ÿ’ฐ

$48K

$37K โ€“ $75K

Projected Growth

๐Ÿ“ˆ

-14.4%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

44/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic face a risk score of 78/100 โ€” 34 points above the national average of 44. With only 44/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $48K ($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 78/100, Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic faces significant automation pressure. Key threats include industrial robotics replacing manual assembly tasks and predictive maintenance reducing manual inspection roles. The 13,810 Americans in this role should actively develop skills in troubleshooting complex equipment malfunctions and quality judgment requiring tactile and visual inspection to remain competitive. Workers who proactively adapt will find new opportunities even as traditional tasks are automated.

Will AI Replace Milling and Planing 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

AI quality inspection via computer vision systems

4

Smart factory scheduling and production optimization

5

Cobots handling repetitive material handling tasks

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Troubleshooting complex equipment malfunctions

โœ“

Quality judgment requiring tactile and visual inspection

โœ“

Setup and calibration of custom production runs

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

Remove workpieces from machines, and check to ensure that they conform to specifications, using measuring instruments such as microscopes, gauges, calipers, and micrometers.

โ€ข

Verify alignment of workpieces on machines, using measuring instruments such as rules, gauges, or calipers.

โ€ข

Move controls to set cutting specifications, to position cutting tools and workpieces in relation to each other, and to start machines.

โ€ข

Observe milling or planing machine operation, and adjust controls to ensure conformance with specified tolerances.

โ€ข

Select and install cutting tools and other accessories according to specifications, using hand tools or power tools.

๐Ÿ’ป Technology Skills

โ€ข

Computer aided design CAD software

โ€ข

Industrial control software

โ€ข

Enterprise application integration software

โ€ข

Object or component oriented development software

โ€ข

Analytical or scientific software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Mechanical

โ€ข

Production and Processing

โ€ข

Mathematics

โ€ข

English Language

โ€ข

Computers and Electronics

๐Ÿ“Š vs National Average

Median Wage$48K
+$2K

National avg: $46K

Risk Score78/100
+34

National avg: 44/100

GenAI Exposure44/100
+6

National avg: 38/100

Projected Growth-14.4%
-18.1%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Engineers20$106K61%
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors25$62K51%
Fabric and Apparel Patternmakers33$68K75%