Abstract
A transition towards circular manufacturing systems (CMS) has brought awareness of untapped economic and environmental benefits for the manufacturing industry. Conventional manufacturing systems already present a high level of complexity in terms of physical flows of materials and products as well as information and financial flows linked to them. Closing the loop of materials and products through multiple lifecycles, as proposed in CMS, increases this complexity manifold. To support practitioners in implementing CMS through enhanced decision-making, this research studies CMS from a complex adaptive systems (CAS) perspective and proposes to exploit methods and tools used in the study of CAS to characterise, model and analyse CMS. By viewing CMS as CAS composed of autonomous, interacting agents, this research proposes a multi-method model architecture for modelling and simulating CMS. The different CMS stakeholders are modelled individually as autonomous agents by integrating agent-based, discrete-event, and/or system dynamics modules within each agent to capture their diverse and heterogeneous nature. The applicability of the proposed multi-method approach is illustrated through a case study of a white goods manufacturing company implementing CMS in practice. This case study shows the relevance and feasibility of the proposed multi-method approach as a decision support tool for the systemic exploration and quantification of CMS. It also shows how a transition towards CMS necessitates a lifecycle approach in terms of costs, revenues and environmental impacts to identify hotspots and, therefore, design circular systems that are viable in both economic and environmental terms. In fact, the analyses of the simulation results indicate how decisions in terms of business models, product design, and supply chain might affect the CMS performance of the case company. For instance, implementing a service-based model led to a high number of usecycles (on average six usecycles per washing machine), which, in turn, led to high lifecycle costs and emissions due to more frequent transportation and recovery operations. Similarly, the deployment of long-lasting washing machines, which is a core principle of CMS, led to high manufacturing costs. Due to the high initial costs and a time mismatch between revenues and costs in the service-based model, it required a longer time for the company to reach the break-even point (approximately 23 months). Overall, the case study shows that multi-method simulation modelling can provide decision-making support for a successful implementation of CMS. © 2022 The Author(s)