Towards a simulation-based understanding of smart remanufacturing operations: a comparative analysis

While the majority of literature on remanufacturing operations examines an end-of-life (EOL) strategy which is both manual and mechanised, authors generally agree that digitalisation of remanufacturing is expected to increase in the next decade. Subsequently, a new research area described as digitally-enabled remanufacturing, remanufacturing 4.0 or smart remanufacturing is emerging. This is an automated, data-driven system of remanufacturing by means of Industry 4.0 (I4.0) paradigms. Insights into smart remanufacturing can be provided through simulation modelling of the remanufacturing process. While the use of simulation modelling in order to predict responses and behaviour is prevalent in remanufacturing, the use of these tools in smart remanufacturing is still limited in literature. The goal of this research is to present, as a first of its kind, a comparative understanding of simulation modelling in remanufacturing in order to suggest the ideal modelling tool for smart remanufacturing. The proposed comparison includes system dynamics, discrete event simulation and agent based modelling techniques. We apply these modelling techniques on a smart remanufacturing space of a sensor-enabled product and use assumptions derived from industry experts. We then proceed to model the remanufacturing operation from sorting and inspection of cores to final inspection of the remanufactured product. Through our analysis of the assumptions utilised and simulation modelling results we conclude that, while individual modelling techniques present important strategic and operational insights, their individual use may not be sufficient to offer comprehensive knowledge to remanufacturers due to the challenge of data complexity that smart remanufacturing offers.

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