System and method for forecasting industrial machine failures

A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to perform a process, the process comprising:

• receiving raw sensory inputs collected from at least one machine;
• generating a plurality of data features based on the raw sensory inputs;
• selecting from the plurality of data features a plurality of indicative data features, wherein the selection is based on a distribution of the plurality of indicative data features that determines an association between the plurality of indicative data features and a machine failure, wherein the distribution of the plurality of indicative data features is a set of abnormal parameters of each of the indicative data features;
• selecting, based on the plurality of indicative data features, a machine learning model;
• applying the selected machine learning model to the plurality of indicative data features;
• and
• determining a probability for a forthcoming machine failure.

A system for forecasting failures in industrial machines, comprising:

• a processing circuitry;
• and
• a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to:
• receiving raw sensory inputs collected from at least one machine;
• generate a plurality of data features based on the raw sensory inputs;
• select from the plurality of data features a plurality of indicative data features, wherein the selection is based on a distribution of the plurality of indicative data features that determines an association between the plurality of indicative data features and a machine failure, wherein the distribution of the plurality of indicative data features is a set of abnormal parameters of each of the indicative data features;
• select, based on the plurality of indicative data features, a machine learning model;
• apply the selected machine learning model to the plurality of indicative data features;
• and
• determine a probability for a forthcoming machine failure.