Driving Proactive Anomaly Detection and Root Cause Analysis in Polymer After‑Treatment Using Seeq – Kaneka North America

Ziyan Sheriff, Senior Process Data Analyst,  Kaneka North America

See how Kaneka transformed declining polymer after-treatment rates into a proactive manufacturing intelligence capability using Seeq. In this breakout session, learn how Kaneka unified quality, process, and recipe data; used year-over-year analysis and principal component analysis (PCA) to uncover root causes such as dryer airflow issues and duct gaps; and achieved an immediate 10% improvement in after-treatment rates. The session also explores real-time anomaly detection and statistical quality analysis to identify process and QC drifts earlier, support corrective action, scale best practices across six plants, and move from reactive investigations to continuous improvement.