Abstract
AbstractUsing predictive and proactive maintenance methods for critical equipment and processes in industry can help reduce unplanned downtimes and improve process availability and stability. Artificial intelligence (AI) methods for process data analysis can provide plant operators with much‐needed insights for decision support and predictive plant maintenance strategies. In this article, a guideline for implementing AI methods in the process industry is provided using the AI‐based application Siemens Predictive Analytics (SiePA) and the results of a SiePA application in a milling process are presented.
Full Text 
Sign-in/Register to access full text options
Sign-in/Register to access full text options 
Published version (
Free)
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
