IS WORK OVER?

Automation index

How much of a Materials engineer’s job can AI already do?

A tensile curve comes earlier. Picking the alloy so it does not fail in service do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Materials engineer

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Tests, metallography and the spec.
Estimate

No public source provides a precise figure. This is our estimate.

18%48%+8.6
Shop, heat treatment and the part that fails spec.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Material choice, corrosion and fatigue.
Estimate

No public source provides a precise figure. This is our estimate.

16%36%+5.8
Supplier, certificates and the doubtful batch.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The field failure and the root cause.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
That it does not fail, and not swapping the material blind.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%27%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • materials tests
  • metallography
  • choose alloys
  • corrosion
  • fatigue
  • heat treatment
  • failure analysis
  • batch certificates

Sources for this job· O*NET 17-2131.00· ESCO/ISCO 2149

Station master

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Graph, orders and the station log.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
Platforms, the crossing and the late train.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
Staff, shifts and the ticket-office gap.
Estimate

No public source provides a precise figure. This is our estimate.

16%32%+5.1
Incident, passengers and the PA.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Works, closures and leaving nobody on the platform.
Estimate

No public source provides a precise figure. This is our estimate.

18%18%+3.2
That they do not meet, and signing the graph.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%23%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • train graph
  • orders
  • platforms
  • ticket office
  • PA
  • line crossings
  • station shifts
  • station logs

Sources for this job· O*NET 53-4031.00· ESCO/ISCO 4323

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