Device and component state prediction and failure prevention

An apparatus comprising:

• a processing device operatively coupled to a memory and configured:
• to receive data corresponding to operation of a plurality of elements, wherein the plurality of elements comprise at least one of a plurality of devices and a plurality of device components, wherein the data corresponding to the operation of the plurality of elements comprises one or more current operational states of respective elements of the plurality of elements;
• to predict, using one or more machine learning algorithms, one or more future operational states of one or more elements of the plurality of elements based, at least in part, on the data corresponding to the operation of the plurality of elements, wherein the predicting further comprises using a conformal prediction model to predict the one or more future operational states of the one or more elements based on respective probabilities of the one or more future operational states;
• to predict, using the one or more machine learning algorithms, transition times for the one or more elements of the plurality of elements to transition from the one or more current operational states to the one or more future operational states;
• and
• to identify, using the one or more machine learning algorithms, one or more actions to be taken in advance of the predicted transition times to prevent the one or more elements from transitioning to the one or more future operational states.

An article of manufacture comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes said at least one processing device to perform the steps of:

• receiving data corresponding to operation of a plurality of elements, wherein the plurality of elements comprise at least one of a plurality of devices and a plurality of device components, and wherein the data corresponding to the operation of the plurality of elements comprises one or more current operational states of respective elements of the plurality of elements;
• predicting, using one or more machine learning algorithms, one or more future operational states of one or more elements of the plurality of elements based, at least in part, on the data corresponding to the operation of the plurality of elements, wherein the predicting further comprises using a conformal prediction model to predict the one or more future operational states of the one or more elements based on respective probabilities of the one or more future operational states;
• predicting, using the one or more machine learning algorithms, transition times for the one or more elements of the plurality of elements to transition from the one or more current operational states to the one or more future operational states;
• and
• identifying, using the one or more machine learning algorithms, one or more actions to be taken in advance of the predicted transition times to prevent the one or more elements from transitioning to the one or more future operational states.