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The digitalization of manufacturing industry, known as e.g., Industry 4.0 or smart production, has opened new opportunities for real-time optimization of production systems. Also, this technological leap has provided new possibilities for the maintenance of production equipment to become data driven and in many cases predictive. This fourth industrial revolution is changing the role of humans at the shop floor. Visions of the dark factory arises, meaning fully automated factories where humans are redundant, both for physical processing and for decision making. The research on Smart maintenance shows great advances in predictive diagnostics and prognostic techniques. However, in manufacturing industry, studies have shown that up to 50–60% of equipment breakdowns are due to human errors. Some of these errors are partly addressed through the development of improved information aid, such as e.g., instructions through Augmented Reality and training in Virtual Reality. Still, the root cause of human errors in manufacturing industry haven’t been properly categorized in terms of e.g., neglect, lack of competence, unclear processes, or poor leadership. In this paper the potential of data driven maintenance is discussed from a human centric perspective. Considering the large part of failures being due to human factors and the possibilities of improvement through implementation of smart technologies, this paper argues for exploring the root causes of human errors in discrete item manufacturing systems and address the proper human centric technologies as a means of reducing these failures.