IS WORK OVER?

Automation index

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

A dye recipe comes earlier. Getting the colour the same over ten thousand metres do not.

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

Task comparison

Textile 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
Recipes, weaves and piece QC.
Estimate

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

18%48%+8.6
Shop, looms and the warp break.
Estimate

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

16%22%+3.5
Supplier, cotton and the sustainability card.
Estimate

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

16%36%+5.8
Finishes, shrinkage and fastness tests.
Estimate

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

16%28%+4.5
The brand, the deadline and the colour that misses.
Estimate

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

18%14%+2.5
Ten thousand metres the same, and not hiding the bad yardage.
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

  • dye recipes
  • weaves
  • looms
  • colour fastness
  • shrinkage
  • piece card
  • warp
  • textile finishes

Sources for this job· O*NET 17-2199.00· ESCO/ISCO 2141

Olive-oil miller

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
Intake, yield and the mill log.
Estimate

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

16%40%+6.4
Crush, malaxate and the decanter.
Estimate

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

18%12%+2.2
Temperature, time and the fruitiness.
Estimate

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

16%28%+4.5
Cellar, the batch and the one that goes rancid.
Estimate

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

16%22%+3.5
The campaign, the tractor queue and not heating.
Estimate

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

18%18%+3.2
Cold for real, and not painting the yield.
Estimate

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

16%12%+1.9
Total100%22%

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

Skills and activities

  • crush olives
  • malaxation
  • decanter
  • fruitiness
  • the campaign
  • mill yield
  • oil cellar
  • extraction temperature

Sources for this job· O*NET 51-3092.00· ESCO/ISCO 7514

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