Skip to content
man bot

Plant and machine operators, and assemblers · code 8154

Bleaching, dyeing and fabric cleaning machine operators

Bleaching, dyeing and fabric cleaning machine operators operate and monitor machines that bleach, shrink, dye and otherwise treat fibres, yarn or cloth. Tasks include - (a) starting and controlling machines and equipment to bleach, dye or otherwise process and finish fabric, yarn, thread and/or other textile goods; (b) tending machines that shrink woven or knitted cloth to predetermined size or strengthen the weave by interlocking the fibres; (c) tending a variety of automatic machines that comb and polish furs; (d) operating and monitoring machines that treat silk to give it body and weight; (e) operating and monitoring machines that impregnate textiles with chemicals to render them waterproof; (f) dyeing articles to change or restore their colours; (g) operating and monitoring machines that stretch or impart lustre or other type of finish to textiles; (h) tending and regulating equipment that fumigates and removes foreign matter from furs; (i) operating machines that comb, dry and polish furs, and clean, sterilize and fluff feathers and blankets; (j) keying in processing instructions to programme electronic equipment; (k) observing display screens, control panels, equipment and cloth entering or exiting processes to determine if equipment is operating correctly; (l) cleaning machine filters and lubricating equipment. Examples of the occupations classified here: - Fabric bleaching machine operator - Textile dyeing machine operator Some related occupations classified elsewhere: - Textile printer - 7322 - Laundry machine operator - 8157 - Hand launderer - 9121 - Hand presser - 9121

None of this job's tasks scored high enough to count. It ranks 157 of 427 for holding up against AI.

Also known as

  • textile dyer
  • finishing textile technician
  • textile finishing machine operator
  • textile dyeing technician

Job titles from the EU's ESCO list. Search for any of them on the jobs page and you'll end up here.

79
Holds up
against AI Not Exposed

AI could take on 21 of 100, on average
so it holds up at 100 − 21 = 79

That's the whole sum, and you can check it against the ILO's study.

64.8
How hands-on
out of 100

From O*NET, matched to one US job

40.1
How fiddly
and cramped

finger skill 42.9 · hand skill 44.6 · cramped spaces 32.8 · averaged

Kind of hands-on work · hands-on 50+ · fiddly 39.4+ Hands-on, fiddly work in tight spaces

More fine handwork, and more time in cramped or awkward spots, than a typical hands-on job. That is exactly what machines find hardest: they do best in tidy, predictable places.

estimated O*NET 31.0 BLS occupational crosswalk chain ISCO-08 to 2010 SOC (Aug 2012, rev. Jun 2015); 2010 to 2018 SOC (Nov 2017); O*NET-SOC 2019 taxonomy data 0.7-work-setting measures chosen by Frey & Osborne (2017) · the grouping is a sorting, not a measurement

This number is probably too high

This score only looks at AI tools like chatbots. It doesn't look at robots at all — and this job rates 64.8 out of 100 for how hands-on it is, which is exactly where robots come in.

Have a look at the tasks below and judge for yourself. The ILO scored them low because a chatbot can't do them. Whether a machine with hands could is a different question, and we can't answer it yet.

The tasks behind the score

The score is the average of these. A job is really a bundle of tasks, and an average can hide how uneven that bundle is.

The task AI could do most of scores 65, while the average is 21. A big gap means some of this job is wide open to AI and some of it barely at all. That's quite different from a job where everything sits somewhere in the middle, even when the averages match.

  1. 65

    Keying in processing instructions to programme electronic equipment

    Medium
  2. 28.3

    Observing display screens, control panels, equipment, and cloth entering or exiting processes to determine if equipment is operating correctly

    Low
  3. 19

    Operating and monitoring machines that treat silk to give it body and weight

    Very Low
  4. 19

    Operating and monitoring machines that stretch or impart lustre or other type of finish to textiles

    Very Low
  5. 18.5

    Operating and monitoring machines that impregnate textiles with chemicals to render them waterproof

    Very Low
  6. 18

    Starting and controlling machines and equipment to bleach, dye or otherwise process and finish fabric, yarn, thread and/or other textile goods

    Very Low
  7. 17

    Operating machines that comb, dry and polish furs, and clean, sterilize and fluff feathers and blankets

    Very Low
  8. 15.8

    Tending machines that shrink woven or knitted cloth to predetermined size or strengthen the weave by interlocking the fibres

    Very Low
  9. 14.8

    Dyeing articles to change or restore their colours

    Very Low
  10. 13.5

    Tending a variety of automatic machines that comb and polish furs

    Very Low
  11. 11.5

    Tending and regulating equipment that fumigates and removes foreign matter from furs

    Very Low
  12. 11.5

    Cleaning machine filters and lubricating equipment.

    Very Low

12 tasks · the High to Very Low labels are the ILO's

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.7-work-setting

Helped, or replaced?

The score above can't tell a tool that makes you faster from one that does the task instead of you. Jobs and Skills Australia looked at those two things separately, and this is their result, matched to this job.

One Australian job matches this one closely, so this is about as reliable as it gets here.

AI helps you
56
AI does it for you
24

Helping wins by 32 points.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.7-work-setting matched to Australian jobs 7117

Compared with similar jobs

There are 39 jobs in the “Plant and machine operators, and assemblers” group, averaging 80.2. This one is below that.