Connect’In® by Axens is a smart digital platform that simplifies and strengthens refinery data management.
By combining advanced machine learning with deep process engineering expertise, Connect’In® automates the collection, validation, and analysis of complex operational data. This enables refineries to detect anomalies early, identify meaningful trends, and make informed decisions with greater speed and accuracy.
› Normalization ensures the comparability of data
› Demonstrating normalization in pilot testing
› What is principal component analysis and how does it work?
› Principal component analysis detects drops in catalyst performance
› Principal component analysis validates feed and reformate data
› Mature pre- and post-combustion technologies
› The reconciliation method improves data quality
› Industrial case study 1: Identifying and correcting flow meter calibration errors
› Industrial case study 2: Avoiding misguided operational adjustments
› Preprocessing the data
› Three data science methods for catalyst monitoring
Through detailed case studies and practical examples, this white paper provides an
in-depth exploration of the process expertise and data science techniques behind
DataVize by Connect’in®.
The core techniques are Axens’ catalyst normalization, principal component analysis (Chapter 1), mass balance reconciliation (Chapter 2) and
advanced analytical methods (Chapter 3).