Abstract
The emergence of Industry 4.0 has led to a wide use of sensors which have facilitated manufacturing operations. Predictive maintenance has significantly benefited from these technological advancements with the use of real-time detection and prediction algorithms regarding future failures. During the last years, there is also an increasing interest on decision making algorithms triggered by failure predictions. The current paper reviews the literature on decision making in predictive maintenance in the context of smart manufacturing. Moreover, it discusses the results, identifies the existing research gaps and outlines a research agenda on the field.
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