Modelling knowledge dynamics in industry 4.0 : a smart grid scenario

Abstract

New digital technological advancements are giving rise to the fourth industrial revolution, commonly termed as Industry 4.0, in which the physical and the digital world merge and the boundary between products and services blurs. This transformation is powered by smart, autonomous objects that communicate and interact among themselves or with actors through the connected, multi-loop, and multi-layer network of Internet of Things and Services. These interconnected smart objects create, carry, and share large volumes of data, leading to many potential opportunities for creating value from such data. Albeit particularly Big Data has been a much-discussed term in research concerning the Industry 4.0 paradigm, the role of knowledge, especially tacit knowledge has been neglected thus far. Furthermore, a conceptual model that would provide an aggregated framework to understand knowledge-based activities and flows does not exist yet. In this paper, we attempt to bridge this gap by firstly critically examining and clarifying the terms data, information, and tacit knowledge by drawing upon relevant knowledge management theories, foremost on Polanyi`s, a common (albeit often misinterpreted) reference point for his successors. Then, by reviewing and analyzing related literature, we develop a conceptual model of knowledge dynamics in the Smart Grid ecosystem, which is one of the potential application fields of Industry 4.0. Specifically, we conceptualize main components and their relations, and describe how knowledge-based activities are embedded in the multi-feedback loop and multi-layer network of Internet of Things and Services. We exemplarily outline a use case – a Smart Grid program of CLP Holdings Limited, the largest supplier of electricity in Hong Kong – as an example of how value is co-created through knowledge dynamics within such ecosystems. Furthermore, we discuss the theoretical and practical implications of the emerging knowledge dynamics model for the design of knowledge management systems.