A digital twin-based cyber-physical system for resilient short-term equipment leasing

Short-term equipment leasing (STEL) is a vital business model supporting small- and medium-sized enterprises by addressing the challenges of limited production capacities through temporary equipment leasing. To enhance the operational resilience of STEL, this study proposes a novel digital twin (DT)-based cyber-physical system (CPS), which implements service composition for leasing scheduling, dynamic prognosis, and dynamic response during type and instance phases in STEL environments. The CPS incorporates a leasing request platform for handling interactions between the STEL centre and clients and a leasing scheduling application based on the tabu search algorithm for leasing scheduling and rescheduling as elemental technical functionalities. The DT application supports virtual commissioning, prognostic simulation, and reactive simulation, minimising operational ripple effects caused by dynamic disturbances such as machine breakdowns or quality issues. The effectiveness of the CPS is demonstrated through an industrial case study in the ceramic industry, where it enhances resilience and operational efficiency. Validation experiments with industrial benchmark samples and various algorithmic comparisons showcase its capability to provide near-optimal solutions, adapt to dynamic disruptions, and maintain performance under dynamic events. This study highlights the potential of DT-based CPSs to revolutionise STEL practices and underscores the importance of resilience in ensuring successful leasing operations.