Machine Learning Algorithms for Predictive Maintenance: A Systematic Literature Mapping
DOI:
https://doi.org/10.47187/perspectivas.7.1.227Keywords:
Machine Learning, predictive maintenance, systematic literature mapping, PdMAbstract
Predictive maintenance is a practice that industrial companies can apply to their processes thanks to technologies such as artificial intelligence and the Internet of Things. Machine Learning algorithms are used in many fields to make predictions or classifications. Predictive maintenance is an area of research that provides new practices, strategies, or methodologies. As a relatively new field, the methodologies are still scattered and there is little information on the maturity of the algorithms. To provide a solid foundation, a systematic literature review is presented to give engineers and researchers an overview of machine learning algorithms used in predictive maintenance. The results obtained show some growth in recent years, demonstrating the interest in this area of research. However, most of the contributions in this field can be summarized as concept proofs and it is still difficult to obtain a prototype that can be validated as a complete and certified system. This paper describes the main machine learning algorithms used in predictive maintenance according to their type of use and supervision, analyses their input and output parameters, and determines their maturity.
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