Agentic AI for Quality Management

Production Data Analysis

Traditionally, identifying the causes of production issues involves manually creating diagrams to categorize factors such as people, machinery, methods, environment, and materials. To simplify this process, our experts developed an Agentic AI solution that automates the analysis of production data and enhances collaboration across departments. 

Integration of AI Agents

Essentially, each AI Agent takes on a specific role, reflecting real-life functions within the company. For example, agents may represent production leads, quality managers, or engineers, each focusing on areas like workflows, machine performance, material quality, or environmental conditions. They independently analyze data from their domains, applying their expertise to identify potential defect causes.

Agent-based Control Authority

A central project manager agent coordinates these specialized agents, managing the flow of information, prioritizing tasks, and ensuring all insights align with solving the issue. For instance, if the production agent flags unusual machine behavior, it may prompt the quality agent to investigate potential material inconsistencies.