GE Predix's machine learning (anomaly detection) capabilities
(full disclosure, I do work for GE)

GE itself has been using their GE Predix Anomaly detection algorithms to establish a relationship between anomalies &amp; machine failure for their factories, in an effort to establish a preventive maintenance framework. The algorithms have been heavily tested to catch any point anomalies from a machine data.  Go ahead and test it out for your datasets: The algorithms are available for registered developers (in catalog) to use in their applications.

Technical approaches (algorithms): Univariate/Multi-variate anomaly detection algorithms.  It detect Shift anomalies , Unexpected trends in physical system behaviors, Anomalous patterns &amp; detect changes in relationship among different variables. It also detects data with very high dimensions (>100). Mann-Kendall, Mann-Whitney, Kernel density estimate etc are some of the key algorithms used.