GCRI · Advanced Industry and Robotics
Human machine work
Automation and robots change what industrial workers do: fewer repetitive and heavy tasks, more monitoring, programming, maintenance and problem-solving. They can improve safety and job quality or intensify work and deskill it, depending on how they are designed and introduced. This page sets out how human-machine work is changing, how job quality and safety are measured, and what evidence serves employers, workers and their representatives.
How the work runs.
Plant operations and safety
Human machine work · Plant 3 · Shift 3
- OEE, % of planned644Watch
- Safety-critical alarms active2Alert
- Robot cell stops this shift5
- Energy per unit2.4kWhNormal
Barriers
layers of protection
| High-pressure trip | SIS | Q2 | Healthy |
| Relief valve RV-12 | Mechanical | Q4 | Healthy |
| Gas detection zone 4 | Detection | Q4 | Bypassed |
| Robot cell light curtain | Safeguard | Q1 | Healthy |
Reactor pressure
Fig.Plant operations and safety: example names and illustrative values, not a record or a live system.
Human machine work: how the risk develops.
Ergonomics, labour and training. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Tasks shift, roles remain
Automation usually takes over specific tasks, leaving workers to supervise, adjust and repair systems. New skills are needed and old ones lose value.
Monitoring changes workload
Supervising automated systems can be monotonous until something fails, when operators must act quickly with incomplete information.
Safety risks change
Robots remove some physical hazards and introduce others, such as unexpected motion, maintenance hazards and new ergonomic strains.
Participation shapes outcomes
Where workers and their representatives are involved in introducing technology, outcomes for job quality and acceptance tend to be better.
People and exposure in Germany.
Population density, night lights and daytime surface heat over Germany, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
People and exposure, for this page
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
- Provider
- NASA LAADS DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite radiance, corrected for moonlight and atmosphere
- Newest at build
- 2026-10-12
- Resolution
- about 500 m grid
- Uncertainty
- Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (persistent cloud still leaves gaps)
- Source
- VIIRS NOAA-20 Level 3, 8-day (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- 8-day; Satellite 8-day composite; persistent cloud still leaves gaps
- Newest at build
- 2026-09-14
- Resolution
- about 1 km grid
- Uncertainty
- Satellite skin temperature of the ground over the 8 days ending on the date shown, a heat exposure indicator; not air temperature, heat index or a heat warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- OMI Aura (NASA GES DISC)
- Provider
- NASA GES DISC
- Licence
- NASA open data
- Vintage
- daily; Satellite retrieval; clouds leave gaps
- Newest at build
- 2026-10-10
- Resolution
- about 2 km grid
- Uncertainty
- Satellite column of nitrogen dioxide in the lower atmosphere on the day shown, mostly from combustion; not a ground-level concentration or a health warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
People and exposure, framed on Germany.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA JPL OPERA DIST-ALERTSources and licences
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- OMI nitrogen dioxide (Aura) and OMPS aerosol index (Suomi NPP), NASA; distributed by the NASA GES DISC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Air quality forecast, 5 days, PM2.5 (CAMS via Open-Meteo): Contains modified Copernicus Atmosphere Monitoring Service information 2026.
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- Optional layers (9 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Nitrogen dioxide, lower atmosphere column: OMI Aura, NASA GES DISC · 10 Oct 2026
Human-machine work changes safety and skills in every sector.
Studies are designed for the Exponential Technology series. Collaborative robot safety follows ISO/TS 15066; social partners decide work organisation.
- Worker accounts with consent.
- Ergonomic evaluations.
Model human machine work as a system. Run the cascade.
Assembled from the Nexus Standards area profile Industry and manufacturing: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
- Natech event
- Dam failure
- River flood (set off downstream)
- Flash flood (set off downstream)
- Mass displacement (set off downstream)
- Chemical spill or leak (set off downstream)
- Emergency-response overload (set off downstream)
- Widespread power outage (set off downstream)
- Water supply shortfall (set off downstream)
- Toxic gas release (set off downstream)
- Industrial fire (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-12Software, model and AI/ML artefacts (supply chain, model cards, dataset sheets)NRS-H60Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)NRS-H50Hazard family: Industrial and process accidents (NHS-1 infra.industrial)NRS-H109Hazard family: Energy-transition technology failures (NHS-1 tech.energy-transition)NRS-X10Chemical, industrial, nuclear and radiological safetyNRS-H54Hazard family: Signal and platform disruption (NHS-1 cyber.platform)NRS-K14Domain pack profile: Manufacturing industrial (DOMAIN-014)
Observation
- eMARS Major Accident Reporting System (listed for reference)
- World Development Indicators (listed for reference)
- ILOSTAT (listed for reference)
- Manufacturing value added as a proportion of GDP and per capita
- CO2 emission per unit of value added
- Manufacturing, value added (% of GDP)
- Direct economic loss to all other damaged or destroyed productive assets attributed to disasters
Example geography
- The Strait of Malacca: 227 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface soil moisture (SMAP), NASA GIBS
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Workers using robots or automated systems | percent of workers | per survey | Working conditions surveys | REPORTED |
| Workplace injuries in manufacturing | injuries per hundred thousand workers | annual | Occupational injury statistics | Published statistics |
| Workers receiving training on new technology | percent | per survey | Training surveys | REPORTED |
| Work intensity | share reporting high speed or tight deadlines | per survey | Working conditions surveys | REPORTED |
| Collective agreements covering technology change | count | per assessment | Labour relations records | REPORTED |
| Manufacturing employment | persons employed | quarterly | Labour force surveys | Published statistics |
How human machine work is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
System model
The couplings between the systems in human machine work: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| Eurofound European Working Conditions Survey | Job quality, technology use and intensity | Public, Eurofound terms |
| ILOSTAT | Employment and occupational injury statistics | Open, CC BY 4.0 |
| EU-OSHA reports on digitalisation and occupational safety | Evidence on new technology and worker safety | Public, EU terms |
| OECD Employment Outlook and automation studies | Labour effects of automation | Public, OECD terms |
| National labour force surveys | Employment by sector and occupation | Public records, licence per government |
Who decides, and what the evidence serves.
Advanced Industry and Robotics prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Employers | How to design jobs and introduce technology | Job quality and safety evidence |
| Trade unions and works councils | What to negotiate on technology change | Agreement and outcome evidence |
| Labour and safety regulators | Which guidance and rules to issue | Injury and working conditions data |
Outputs this topic produces
- Job quality analyses in automated workplaces
- Safety reviews of human-robot interaction
- Training needs assessments
- Evidence notes for social dialogue
What experts ask.
- 01
How is work redesigned?
Which tasks move to machines, which remain with people and how the remaining work is organised.
- 02
What are the health effects?
Physical strain, cognitive load, monotony, isolation and the pace set by machines.
- 03
What skills are needed?
How training keeps pace with new systems and preserves manual skills for abnormal situations.
- 04
Who has a say?
How workers and their representatives take part in introducing technology.
What drives the risk.
Automation often removes heavy and repetitive physical tasks, reducing some injuries, while increasing monitoring and cognitive demands. Supervising automated systems can combine long periods of low activity with sudden high-stakes intervention.
Machine pacing and algorithmic management can intensify work, reduce autonomy and increase stress. Ergonomic risks shift rather than disappear, for example to maintenance tasks in awkward spaces.
Skills decay when they are not used. Operators who rarely run a process manually may struggle when automation fails. Training in simulators and structured practice help maintain competence.
Participation affects outcomes. Research on technology introduction finds that involving workers early tends to improve both safety and acceptance, and surfaces practical knowledge designers lack.
Demographics add pressure. Ageing workforces in many industrial economies raise both the value of assistive technology and the importance of designing work that older workers can sustain.
How evidence is gathered, and where it stops.
| Method or data | What it shows | Its limit |
|---|---|---|
| Ergonomic assessment | Physical and cognitive load | Snapshots may miss variation |
| Workforce surveys | Job quality and wellbeing | Self-report and response bias |
| Task analysis | Division of work between people and machines | Formal tasks differ from actual practice |
| Training evaluation | Competence after training | Short-term tests may not predict performance |
How it is studied, and what the methods cannot say.
- 01Robotics and automationRobot cell risk assessment · Vision-guided handling · Collaborative workstation designApplied here
- 02Systems engineeringIntegrated safety and security requirements · Factory and site acceptance testingApplied here
- 03Sensors, IoT and observation networksCondition monitoring · In-line quality inspection · Securing connected sensorsApplied here
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
How does automation change factory jobs?
Do robots make work safer?
What is social dialogue on technology?
Does automation reduce workplace injuries?
Does the platform take positions on labour disputes?
What is algorithmic management?
Contribute evidence from this page.
Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
- EmailGateway GW-GCRISend it from this pageEvidence, a correction, a case, a method, a review, a translation or profile input. It arrives tagged with this page, so the editor who owns it receives it.
- ZenodoOpen depositDeposit it and submit to the communityPublish your own record on Zenodo with your ORCID iD, then submit it to the Reports community there. Curators review it; the DOI stays yours.
- ReportsGCRISee every way to contributeThe contribution types, how each is reviewed, what credit you receive, the licence and what is never accepted.
Never send personal data, sensitive infrastructure detail or anything you have no right to share. A contribution is reviewed before use; sending it confers no authorship or editorial rights, and sponsorship never buys a finding.
Bring a method, a dataset or a question.
Information and enquiries are open today. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.
Legal documents.
Maps, data and figures on this site are shown for context and general information. They are not advice, forecasts or warnings; the limits of the information are set out in the Disclaimers and Data Notices.