Conceptualizing maintenance knowledge and learning in digitalized production

Paper in proceeding, 2026

Maintenance knowledge and learning are essential within maintenance organizations, as they drive broader organizational learning and facilitate maintenance digitalization. However, accelerating technological development challenges maintenance organizations in new ways, particularly in learning how to maintain data-driven factories. Maintenance operations require both manual dexterity for repair work and human ingenuity for complex problem-solving. This positions maintenance organizations as learning entities that can also drive learning across the wider organization. In digitalized production, a successful maintenance organization is therefore a learning organization. Despite this, scholars remain uncertain about the levels and organizational interfaces where maintenance knowledge and learning need to occur to facilitate maintenance digitalization. In response, this study aims to conceptualize maintenance knowledge and learning in digitalized production. We focus on how maintenance knowledge should be understood, shared, and utilized, and on why learning within maintenance organizations, between maintenance organizations and other organizational functions, and from maintenance knowledge and learning facilitates maintenance digitalization. Using conceptual modeling, we draw on fundamental theories from knowledge management and organizational learning within the context of maintenance operations in industrial manufacturing. The resulting conceptual model clarifies where knowledge and learning occur and explains how maintenance organizations act as central drivers of learning beyond their own boundaries. The study contributes by providing a shared conceptual understanding of maintenance knowledge and learning in digitalized production for both scholars and industry professionals.