Robot cell risk assessment
Each robot application is assessed for hazards from motion, tools and maintenance, and safeguards are chosen and verified against robot safety standards before operation.
GCRI · Advanced Industry and Robotics
Robotics in industry
Robotics and automation is the technology this platform stewards for the network. It covers the design, control, safety and integration of robots in production, logistics and inspection, and how they work alongside people.
01Contents
Robotics in industry in five parts.
02Application
What robotics and automation does here.
Robotics and automation design machines that sense, decide and act in physical environments. They are used in manufacturing, logistics, inspection and disaster response, and change patterns of operational risk and labour. In industry and robotics, work and skills and trade, resources and supply chains, automation can reduce human exposure to hazardous tasks and speed recovery operations. It also concentrates dependence on software, sensors and supply chains. The canonical description is on the STEM Commons.
Vision-guided handling
Machine vision lets robots handle variable parts. Performance is tested across part variations, lighting and wear, with failure modes documented.
Collaborative workstation design
Shared workstations are designed with force, speed and separation limits and ergonomic layouts, and validated with the workers who use them.
03Monitor
Verification and test.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Verification and test
Industry and robotics · Robotics in industry · Run R-3272
Test campaignGCRI · Advanced Industry and Robotics
Requirements coverage
| REQ-01 safe stop | 33 | 33 | Covered |
| REQ-07 fault detection | 6 | 9 | Gaps |
| REQ-12 timing | 26 | 18 | Covered |
Method card
- Method
- Robotics and automation
- Standard
- traceability matrix
- Reviewer
- independent
- Label
- MODELLED
Findings by severity
04Data
What the method consumes.
Datasets and records used by robotics and automation on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| Robot specifications | Capabilities | DECLARED |
| Safety validation records | Verification | OBSERVED |
| Incident reports | Failure modes | REPORTED |
05Simulator
A shock through an input-output economy.
A loss of output in one sector propagates through the technical coefficients to its suppliers and customers, and recovers at the rate you set; the coefficients are teaching values, not national accounts. Teaching model with stated illustrative values, not a prediction.
Controls
- Sector hit first (position in the list)
- 0
- Size of the shock
- 30% of its output
- Duration of the shock
- 30 days
- Recovery rate
- 0.08 per day
- Days simulated
- 180 days
Readouts
- Output lost over the run
- 0.92% of a year’s output
- Total over direct (multiplier)
- 1.59 times
- Most affected other sector
- Trade
- Its peak inoperability
- 3.9%
Numbers, methods and sources
| Sector | Peak inoperability (%) | Output weight (%) |
|---|---|---|
| Agriculture | 29.88 | 27.3 |
| Energy | 0.23 | 15.2 |
| Manufacturing | 0.53 | 17.0 |
| Transport and ports | 3.68 | 17.1 |
| Trade | 3.89 | 10.7 |
| Services | 0.48 | 12.7 |
Methods
- Input-output analysis Leontief (1936); Miller and Blair (2009), Input-Output Analysis, Cambridge University Press
- Inoperability input-output model Haimes and Jiang (2001), Journal of Infrastructure Systems 7
- Dynamic inoperability and recovery Lian and Haimes (2006), Systems Engineering 9
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
- Seaports Natural Earth
- Maritime chokepoints Nexus (named straits and canals at their published coordinates)
- Railways Natural Earth
- Major roads Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Advanced Industry and Robotics in Foundry
- Tested at Advanced Industry and Robotics in Universe
- Codified in Industry, Trade and Supply Chains in Standards
- Published in Advanced Industry and Robotics in Reports
- Taught in Faculty of Technology and Digital Systems in Academy
06Validation
How results are checked.
Systems are validated through simulation, staged field trials and conformance to functional safety standards. Operational monitoring checks performance after deployment.
| Check | How it is done |
|---|---|
| Standards verification | Safety functions are verified against applicable standards |
| Field performance | Vision and handling are tested under production conditions |
| Worker feedback | Collaborative designs are reviewed with users |
Robots may behave unpredictably in unstructured environments not covered by testing. Interaction with people raises safety and liability questions.
07Methods and evidence
How robotics in industry 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 robotics in industry: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
08Connections
Topics that rely on this method.
09Stewardship
Who maintains the method.
Advanced Industry and Robotics stewards robotics and automation for the Consortium and reviews how it is applied across platforms.
10Questions
Questions and answers.
What are the limits of robotics and automation in this field?
Robots may behave unpredictably in unstructured environments not covered by testing. Interaction with people raises safety and liability questions.
How are results checked?
Systems are validated through simulation, staged field trials and conformance to functional safety standards. Operational monitoring checks performance after deployment.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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GCRIAdvanced Industry and RoboticsExponential TechnologyGlobal Sector Risk and Resilience
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