Machine Learning & Artificial Intelligence

Plan today for tomorrow’s environment

After decades of using human and statistical techniques, machine learning methods are now being applied to further improve efficiency and accuracy in the diagnosis and prognosis of potential failure modes of rotating machinery. Machine learning methods allow monitoring systems to react even faster and more precisely than standard, traditional tools and methods.  It also further enhances the capability of skilled human experts.  ITR leverages artificial intelligence and machine learning throughout its suite of portable route-based systems, smart online dedicated systems, wireless sensor networks, and supporting predictive analytics services.

Each ITR system has connectivity to the ITR cloud services.  Verified findings are collated over time and form the basis of training sets used by ITR data scientists to develop system, site, and asset specific algorithms for advancing real-time exception tests and notifications.  This iterative process means each ITR system continually improves and evolves with the lifecycle of each monitored asset.

Similarly, ITR expert analysis services also leverage machine learning to digitize knowledge so experts avoid repetitive tasks and focus on the complex analysis that only 20+ year experts can do.  Each machine and customer are unique, so individualized algorithms are developed.  When verified as effective, these algorithms are used to augment human experts and can be deployed to edge devices to advance portable/offline monitoring methods.