Countering abnormalities
This online article, “High-quality production with the fusion of process knowledge and data analysis technology—process data analysis using machine learning,” show how Sumitomo Seika Chemicals Co.’s plant in Himeji, Japan, improved its production of super-absorbent polymers by drafting an observation item list, developed a workflow for process analytics, identified disturbances, and reduced fluctuations.
Yokogawa
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Basic stages and video
This online article, “A step-by-step guide to the data analysis process” by Will Hillier, covers the stages of data analytics, including defining questions, data collection, cleaning with exploratory analyses, and descriptive, diagnostic, predictive and prescriptive analyses.
Career Foundry
Monitor, model batches
This online article, “Understanding the basics of batch process analytics,” covers process monitoring and diagnostics, modeling outputs to monitor quality, batch modeling of completed batches, introducing statical process control (SPC), and batch evolution and level models.
Sartorius
Predictive gas optimization
This two-minute video, “Nippon Gases prevents unplanned downtime, extends APM strategy with Predictive Asset Intelligence,” shows how it used AI-based condition monitoring software to improve the performance of critical equipment such as compressors, turbines, and purifiers. It deployed SymphonyAI’s Predictive Asset Intelligence software built on Iris Foundry dataops platform to calculate asset health, maximize uptime with predictive warnings, and optimize operations using deep learning AI-models.
