Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to AI in Manufacturing
- Trends in smart manufacturing and Industry 4.0
- Overview of AI applications in operations
- Essential performance metrics and KPIs
Data Collection and Preparation
- Sources of manufacturing data (sensors, PLC, MES)
- Cleaning and formatting time-series data
- Utilising Pandas and Jupyter for preprocessing
Descriptive and Diagnostic Analytics
- Data exploration and visualisation
- Correlation analysis and identifying root causes
- Creating custom dashboards using Power BI
Machine Learning for Process Optimisation
- Supervised and unsupervised learning
- Clustering for pattern discovery
- Regression and classification for prediction
AI for Predictive Maintenance and Quality
- Anomaly detection and predictive alerts
- Models for predicting failures
- Enhancing product quality through model insights
Real-Time Analytics and Feedback Loops
- Streaming data and real-time processing
- Integration with SCADA/MES systems
- Feedback mechanisms for automatic process adjustments
Case Study and Capstone Project
- Hands-on analysis of real-world datasets
- Designing and validating an optimisation model
- Final presentation of an AI-driven improvement plan
Summary and Next Steps
Requirements
- A solid grasp of manufacturing processes or operations management
- Proficiency in data analysis or Excel-based reporting
- Fundamental familiarity with programming or scripting
Audience
- Process engineers
- Plant supervisors
- Lean Six Sigma professionals
21 Hours
