Log-based predictive maintenance using multiple-instance learning

Abstract

A method of building a model for predicting failure of a machine, including parsing () daily machine event logs of one or more machines to extract data for a plurality of features, parsing () service notifications for the one or more machine to extract failure information data, creating () bags from the daily machine event log data and failure information data for multiple instance learning by grouping daily event log data into the bags based on a predetermined predictive interval, labeling each bag with a with a known failure as positive, and bags without known failures as negative, where a bag is a set of feature vectors and an associated label, where each feature vector is an n-tuple of features, transforming () the multiple instance learning bags into a standard classification task form, selecting () a subset of features from the plurality of features, and training () a failure prediction model using the selected subset of features.