SparkPredict® Raises Machine Prognostics to a Cognitive Level
SparkPredict® enables truly predictive capabilities that can deliver billions of dollars in cost savings and operational efficiency improvements to machine operators. SparkPredict® learns from sensor data, identifies impending failures long before they occur and alerts operators to sub-optimal operation before it can cause any harm.
Existing machine condition monitoring systems are good at looking at individual variables and monitoring when each variable breaches its assigned thresholds. Some rely on legacy approaches such as mean time between failures (MTBF) to schedule interventions such as service and replacements. These methods simply aren’t very good at predicting what will happen next in a manner that’s timely enough to make a real difference. SparkPredict® is!
Sophisticated algorithms exceed accuracy of traditional methods
Automated model-building can shrink days or week-long model building processes to minutes
Minimum human engagement enables large-scale deployments
Automated model-building also enables the algorithm to adapt to specific maintenance schedules, load patterns and environmental conditions.
Self-Learning & adaptive algorithms ensure that results continue to improve over time
How SparkPredict® works
SparkPredict® applies sophisticated algorithms, including our own patent pending cognitive algorithms, to huge bodies of sensor data, and Big Analog Data, generated by pumps, rotors, motors and a variety of other machines. SparkPredict® can:
Collect large amounts of sensor data
Acquire and transform the data
Apply SparkCognition’s proprietary classification and prediction algorithms
Generate actionable insights and support root-cause analysis