Root cause analysis objective is to understand the root cause leading to gaps at manufacturing process and extract insights to reduce faulty units and inefficiency. AI-powered root cause analysis is a game changer in  improving quality and problem-solving. It uses smart algorithms that show  exactly what is causing quality issues and alerting it to the team.

Statistical process control (SPC) mainly delivers Key Performance Indicators such as Cp/Cpk, first Pass yield and other statistical analysis related to the process, while AI root cause technology uses anomaly detection and automatically identifies correlations between different processes and product parameters. 

First Pass Yield improvements
Improve First Pass Yield by AI root cause analysis

AI-Powered Root Cause Analysis will deliver:

  • Machine learning 

  • Anomaly detection of quality and yield problems

  • Prediction of failures

  • Cross correlations between process and parameters

  • Automatic alerts 

  • Pattern recognition for automated data mapping

QualityLine AI analytics is designed to quickly turn project data into insight, and insight into action. 

Artificial intelligence technology is an important capability offered by QualityLine’s solution that is applied to automatically unify multiple manufacturing data sources into one database to identify product and process errors in order to deliver detailed insights into your manufacturing process. The AI analytics creates a total end-to-end process control, improving quality and problem-solving.