Dennis Luo ^* Meiling He Justice Darko Fatime Ly Seymour Francisco Maturana

• Rockwell Automation (United States), Milwaukee, United States

Bioreactors play a crucial role in the production of biopharmaceuticals and bioproducts, necessitating continuous operational monitoring for quality assurance. Manual processes in manufacturing plants can lead to anomalies, such as outof-trend and out-of-spec incidents, requiring extensive root cause analysis, typically taking 2 to 8 weeks. This paper presents an innovative methodology focused on the golden batch profile, serving as a benchmark to identify deviations and root causes in subsequent industrial batches. The approach involves normalizing the data and calculating the variances of a specified batch from the golden batch profile. Examining the contribution of each critical process parameter to these variances underscores the importance of critical process parameters in root cause analysis. The detailed root cause analysis framework ensures transparency in analytical tools and processes. In conclusion, the paper provides a robust framework for analyzing industrial batch processes, introducing novel golden batch profile concepts, and demonstrating effectiveness through application to the IndPenSim dataset. The emphasis on deviations of critical quality attributes and critical process parameters from the specified batch compared to the golden batch profile contributes valuable insights to industrial process analysis and significantly reduces root cause analysis time.