Automate ISO 26262 Compliance with GPT-4 for Automotive Safety Analysis

:car: Business Value Proposition Accelerates ISO 26262 compliance for automotive/industrial systems by automating safety analysis while maintaining rigorous audit standards.

:gear: How It Works graph TD A[Engineer uploadssystem description] --> B(LLM identifies hazards) B --> C(LLM scores risks per ISO 26262) C --> D(Generates mitigation strategies) D --> E(Produces audit-ready reports)

:chart_with_upwards_trend: Key Benefits Time 50-70% faster than manual HAZOP/FMEA sessions Instant report generation vs. weeks of documentation

Risk Mitigation Pre-validated templates reduce human error Auto-generated traceability simplifies audits

:warning: Governance Controls Human-in-the-loop: All LLM outputs require engineer sign-off Version tracking: Full history of modifications Audit mode: Export all decision rationales

:computer: Technical Requirements Runs on existing n8n instances Docker deployment (<1hr setup) Integrates with JAMA/DOORS (optional)

:wrench: Setup and Usage

Prerequisites Docker (Install Guide) Docker Compose (Install Guide) n8n instance (Free Self-Hosted or Cloud - Paid) OpenAI API key (Get Key)

Enterprise-ready deployment: When supported by IT infrastructure teams, this solution transforms into a scalable AI safety assistant, providing real-time HARA guidance akin to engineering Co-pilot tools.

:arrow_down: Installation and :play_or_pause_button: Running the Workflow

For installation procedures and usage of workflow, refer the repository

:warning: Validation & Limitations

AI-Assisted Analysis Considerations | Advantage | Mitigation Strategy | Implementation Example | |-----------|---------------------|------------------------| | Rapid hazard identification | Human validation layer | Manual review nodes in workflow | | Consistent S/E/C scoring | Rule-based validation | ASIL-D → Redundancy check | | Edge case coverage | Cross-reference with historical data | Integration with incident databases |

Critical Validation Steps AI Output Review node in n8n
Example: (by code) { "type": "function", "parameters": { "functionCode": "if ($input.item.json.ASIL === 'D' && !$input.item.json.redundancy) throw new Error('ASIL D requires redundancy');" } }

Version Control Prompt versions tied to ISO standard editions (e.g., ISO26262:2018-v1.2) Git-tracked changes to ai_models/training_data/

Audit trails Providing a log structure for audit trails Log structure /logs/ └── YYYY-MM-DD/ ├── hazards_approved.log └── hazards_rejected.log