Machine Learning
Due to the availability of cheap and reliable instrumentation and powerful historians, a large amount of process data is now available. However, this also means that plant engineers are overwhelmed with a large amount of data. It is difficult to make out underlying issues in the process using short term trend data alone.
Machine learning techniques provide a powerful mechanism for analysing large quantities of process data and identifying the underlying patterns. Machine learning helps categorize the data and identify normal and abnormal operational areas. We use these machine learning alrogirthms for analysing process data. The end applications are built in Excel, which means that there is no need for additional computing infrastructure or new software. In addition, the familiar Excel environment means that there is a minimal learning curve for users.
The following screenshot is an example of our solution. It is simple and intuitive for the users.
Also view this Linked in article on Machine Learning for process operators.
Contact us at sales@xlncontrol.com to discuss the use of machine learning algorithms for your plant.