(159a) “Digital Transformation 4.0” - Production Optimization with AI
AIChE Spring Meeting and Global Congress on Process Safety
2021
2021 AIChE Virtual Spring Meeting and 17th Global Congress on Process Safety
Industry 4.0 Topical Conference
Big Data Analytics - Vendor Perspective II (Session Speakers Invited)
Friday, April 23, 2021 - 11:00am to 11:30am
With the constant pressure to increase plant efficiency and uptime in a highly competitive environment, condition-based maintenance and the optimization of the production processes become more and more important for a plantâs economic success.
Siemens Predictive Analytics (SiePA) is a practical and robust tool that integrates human experience/ know-how and machine learning capability to extract the relevant information on the equipment and process status.
The information is summarized in an intuitive graphical user interface, used mainly by plant operators and maintenance staff. Thanks to AI, process data from the plant can be used optimally: Not only to predict the risk of a process failure and to display warnings, but also to efficiently diagnose possible malfunctions. The best prerequisites for increasing the efficiency, availability and safety of operations to a level that would have been unthinkable just a short time ago.