Get in Touch

Course Outline

  • Introduction to AI and its applications in manufacturing
  • Product quality analysis using AI: identifying defects and anomalies
  • Optimization of products and processes based on collected data
  • Predictive maintenance: AI models for anticipating equipment failures
  • Integrating AI insights into dashboards and KPI reports
  • Best practices for data-driven decision-making in production

 Expected outcomes:

  • Understanding of AI principles applied to quality analysis and product optimization
  • Ability to identify and interpret anomalies and defects in production
  • Application of AI for predictive maintenance and reduction of downtime
  • Creation of dashboards and reports for KPI monitoring and decision-making

Requirements

  • Understanding of: concepts related to AI for quality analysis, product optimization, and predictive maintenance
  • Experience with: production data, reporting systems, Excel, and KPI visualization tools
  • Programming experience: basic knowledge of Python, R, or other languages used for AI applications (optional)
  • Target audience: production engineers, quality specialists, operational managers, data analysts

 

  • Covered topics: product quality analysis and defect identification
  • Covered topics: product and process optimization using AI
  • Covered topics: predicting equipment failures and making data-driven decisions
 7 Hours

Number of participants


Price per participant

Upcoming Courses

Related Categories