Edge computing for the production industry a systematic approach to enable decision support and planning of edge

Because the Edge Computing (EC) paradigm allows processing of vast amounts of data in proximity to the respective source, latency and quantity constraints are no longer a limiting factor. That enables the development of novel data-driven applications and the extension of the solutions space for value-added services in production. The complexity and diversity of factories, combined with the continuing discovery of new data-driven solutions, poses a challenge for practitioners to thoroughly determine where, which, and how data should be processed. This, however, is crucial for deciding how and whether to invest in EC. This paper proposes a multiphase concept for the systematic assessment of whether and where EC is most beneficial in a given production environment. It is comprised of human and machine interpretable functions. Combining multiple functions leads to a data-driven solution, which forms links between the data sources (assets) of a production environment and the desired outcome (goals). Four main criteria for EC are derived to enable the exposure of areas with increased EC potential, forming the baseline for a scoring system. The concept is designed so that its application is feasible within an industrial context. First analyses show the prospect of the approach and suggest potential benefits for providing practical implementation guidance.