Industrial robot production data clustering for anomaly prediction

A system for robot data analysis, said system comprising:

• means for collecting time-series data for a plurality of joint parameters during operation of a robot;
• and
• a computing device with a processor and memory configured for;
• defining a range of numbers of clusters to evaluate;
• performing a clustering operation on the time-series data, using a first number of clusters selected from the range, to assign each time-series data point to one of the clusters;
• calculating a cluster consistency score for results of the clustering operation with the number of clusters;
• performing the clustering operation and calculating the score for each remaining number of clusters in the range;
• selecting the results of the clustering operation having a highest score;
• separating the time-series data points into datasets according to cluster assignment in the selected results, where at least one of the datasets contains data points corresponding to an operating condition of the robot;
• analyzing the datasets, including analyzing each of the datasets containing data points corresponding to an operating condition of the robot to identify data patterns;
• and
• sending an alert when an alert criteria is met in the analyzing.