A framework to support a simulation-based understanding of digitalisation in remanufacturing operations

Abstract

Modelling and simulations are important in predicting the response and behavior of manufacturing shop-floor operations such as predictive maintenance in relation to the real-life operations. Thus, remanufacturing operations, an end-of-life operation focused on returning a “disassemble-able” product to a condition which is at least as new as the original specification, can be influenced by modelling and simulation. While simulations have a limitation in their ability to enable real-time business decisions in environments of complexity due to costs and time required to build these models, remanufacturing operations in particular will benefit from the application of simulations. As remanufacturing is characterized by an uncertain nature of product returns, simulation modelling can be used to support the understanding of different methods from a real-time scenario context. With manufacturing digitalization, complexity in remanufacturing is further increased with more data produced as sensor-enabled products enter the remanufacturing shop-floor. This paper investigates how modelling and simulation could be used to provide clarity to the digitalization of remanufacturing operations and proposes a framework to support simulation modelling for remanufacturing sensor-enabled products. Findings from the synthesis of a systematic literature review and five remanufacturing case studies reveal that system dynamics modelling has greater application to remanufacturing over other modelling techniques. Additionally, the importance of digitalisation across the six stages ofremanufacturing is expected to be similar and, as such, reduces medium term cost implications for remanufacturers looking to digitalise.