CEN ISO/TR 22100-5:2022 PDF
Safety of machinery - Relationship with ISO 12100 - Part 5: Implications of artificial intelligence machine learning (ISO/TR 22100-5:2021)
Safety of machinery - Relationship with ISO 12100 - Part 5: Implications of artificial intelligence machine learning (ISO/TR 22100-5:2021)
- Статус документа:
- Действующий
- Формат:
- Электронный (PDF)
- Количество страниц:
- 14
- Дата публикации:
- 27 апреля 2022 г.
- Издание:
- CEN TR 22100 edition 1 version 1
- ICS:
- 13.110
This document addresses how artificial intelligence machine learning can impact the safety of machinery and machinery systems. This document describes how hazards being associated with artificial intelligence (AI) applications machine learning in machinery or machinery systems, and designed to act within specific limits, can be considered in the risk assessment process. This document is not applicable to machinery or machinery systems with AI applications machine learning designed to act beyond specified limits that can result in unpredictable effects. This document does not address safety systems with AI, for example, safety-related sensors and other safety-related parts of control systems.
Abstract
Overview
CEN ISO/TR 22100-5:2022 (identical to ISO/TR 22100-5:2021) gives guidance on how artificial intelligence (AI) - specifically machine learning (ML) - can affect the safety of machinery and how those effects should be addressed using the risk assessment principles of ISO 12100. The technical report clarifies scope, terms (AI, machine learning), typical AI use cases in machinery, and practical examples showing when AI introduces no new hazards and when it does.
Key topics
- Scope and applicability
- Focuses on AI/ML applications designed to act within specified limits; not applicable to systems intended to act beyond limits causing unpredictable effects.
- Excludes safety-related systems with AI (e.g., safety sensors and other safety-related control parts).
- Definitions
- Clear definitions of artificial intelligence and machine learning as used in the machinery context.
- AI lifecycle in machinery
- Distinction between training and inference (autonomous operation) phases of ML-enabled control systems.
- Risk assessment alignment
- Guidance on how to apply the ISO 12100 risk assessment and risk reduction process to AI/ML functions in machines.
- Examples and analysis
- Illustrative cases: packaging robots, precision herbicide spraying, laser cutting part removal (examples without safety implications) and autonomous guided vehicles (AGVs) operating without perimeter safeguards (examples with safety implications).
Applications and practical value
- Helps machinery designers, safety engineers, and manufacturers determine whether an AI/ML function:
- Introduces new hazards or increases existing risks,
- Requires additional risk reduction measures beyond those for conventional designs.
- Practical use cases include:
- Quality control, process optimization, condition/failure monitoring, and predictive maintenance.
- Design decisions for AGVs, automated material handling, agricultural machinery and automated cutting systems.
- Useful for:
- Design teams integrating ML into control systems,
- Compliance managers preparing CE/market safety documentation,
- Risk assessors applying ISO 12100 to AI-enabled machinery.
Related standards
- ISO 12100 - General principles for risk assessment and risk reduction (primary reference for applying this report).
- Other ISO/IEC terminology and ML references cited in the report (for definitions and broader AI context).
This technical report is a practical resource for organizations integrating AI/ML into machinery - helping ensure safe design choices, consistent risk assessment, and better alignment with established machinery safety standards. Keywords: safety of machinery, ISO 12100, AI machine learning, risk assessment, AGV, predictive maintenance.
Технические детали
- Технический комитет
- CEN/TC 114 - Safety of machinery
- SKU
- CEN ISO/TR 22100-5:2022
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