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Data & AI Use Cases in manufacturing
ai-tag AgenticAI

Automated root cause analysis in production

Use Case Use Case Family: Predictive Analytics & Forecasting, Agentic AI
Business Domain Business Domain: Manufacturing
Process Processes: Quality Management
Challenge:

In quality management, preparing root cause analyses is highly time-consuming and resource-intensive. Identifying defects requires collecting and analyzing data from multiple sources, leading to delays in resolving production issues. Manual processes like Ishikawa diagrams are slow and limit responsiveness to quality deviations.

Solution:

Instead of manually creating an Ishikawa diagram with the categories "human", "machine", "method", "milieu", "material", for example, the existing production data is analysed by means of a multi-agent system. The agents mirror real-world roles (quality managers, production managers, developers) and communicate autonomously to generate insights. A project manager agent oversees discussions, ensuring a structured and goal-oriented problem-solving process. This approach accelerates Ishikawa diagram generation and enables fast issue resolution.

AI Agent Roles

  1. Quality Manager Agent – Collects and analyzes quality-related data from production lines, identifying trends and potential defect sources.
  2. Production Manager Agent – Evaluates operational efficiency, machine performance, and production data to detect anomalies affecting quality.
  3. Developer Agent – Analyzes system logs and software-related issues, ensuring that automation systems and sensors are functioning correctly.
  4. Supplier Interaction Agent – Communicates with external data sources to assess whether defects originate from raw materials or supplier inconsistencies.
  5. Project Manager Agent – Oversees AI-agent discussions, ensuring that insights align with business objectives and troubleshooting efforts remain structured.
Benefits:
  • Resource efficiency: Reduces workload for specialists by automating analyses.
  • Faster problem resolution: AI-powered agents generate partial Ishikawa diagrams within minutes.
  • Scalability: Multi-agent collaboration enables cross-team integration and adaptability.
  • Improved decision-making: AI synthesizes diverse data sources for more precise root cause detection.
Target Group Target Group:
Quality managers production managers process engineers
Potential Industries Potential Industries:
Automotive Industrial Manufacturing Aerospace
Low Risk
Low Risk systems Art. 50
with transparency obligations
Disclaimer The information provided regarding the risk assessment is without guarantee. The complete classification of a use case according to the EU AI Act depends on numerous regulatory and company-specific factors. Therefore, the risk assessment is always case-specific. The risk assessment logic of Casebase is used for this purpose.