Machine learning for monitoring

Focus

My work explores how machine learning can complement memory control charts and adaptive monitoring. My CV also identifies AI in financial markets as a research interest.

• Artificial neural networks
• Supervised learning for control charts
• Predictive analytics
• Monitoring count and continuous manufacturing data

Examples from the CV

• Memory control chart based on machine learning technique for efficient process monitoring (2025).
• Adaptive CUSUM control chart utilizing supervised learning for monitoring the process location parameter: A case study application (2025).
• Data-driven control charts for monitoring Gamma-distributed manufacturing processes using machine learning (2026).

Explore further

See the publication record for bibliographic details, or contact me to discuss a related research question.