Synopsis
Digital twin (DT) technology has emerged as a transformative enabler within Industry 4.0 frameworks, offering the potential to radically compress prototype development cycles by enabling
real-time simulation, fault prediction, and iterative design optimisation in virtual environments prior to physical realisation. Despite growing industrial uptake, systematic evidence on the measurable impact of digital twin integration on R&D workflow efficiency remains fragmented across literature. This paper addresses this gap through a multi-site empirical study conducted across eight manufacturing facilities in France, Germany, and Turkey between 2023 and 2025. Using a standardised R&D workflow audit instrument combined with discrete-event simulation modelling, we quantify the reduction in prototype iteration cycles, time-to-validation, and rework costs attributable to DT integration at different stages of the product development funnel. Our results indicate a mean reduction of 34.2% in iteration cycles and a 28.7% decrease in time-to-validation in facilities with mature DT deployment, alongside significant cross-site heterogeneity driven by model fidelity, sensor infrastructure maturity, and organisational readiness. A readiness index for DT-enabled R&D acceleration is proposed.
