Enterprises Must Transform Digitally To Face The Next Phase Of Their Competitive Lives. Together With Digital Platforms, Content Ubiquity, Social Amplification And New Dimensions Of Data Available Through Industrial-IoT, This Is A Transformation Like No Other.
A Strong Data-signal Of Impending Catastrophic Event In A Physical Machine Is Often The Function Of Tiny (Noisy) Signals Being Emitted From Smaller, Subliminal Events Upstream To It. Events That A Human Operator May Not Prioritize In The Course Of A Day’s Normal Operation At A Power-Generation Facility Or An Oil-Drilling Rig.
Many sophisticated computational & signal processing tools and methods have played a huge role in bringing machine learning and artificial intelligence into the industrial internet. Methods such as Kalman Filter smoothing automate the process of drawing inferences while also adjusting for noise inherent in sensors. Kalman filters use the prior belief about the state of a system, and ensembles measurement of the next measured state and model of how the system evolves from prior state (derived from the physics of an equipment) to make an improved estimate of the current system state. Analytic models that used Kalman smoothing produced better predictive performance than those applied to raw industrial sensor-data.