Manufacturing and supply chain operations are on the cusp of an era with the emergence of groundbreaking technologies. Among these technologies, the digital twin technology is characterized as a paradigm shift in managing production and supply networks since it facilitates a high degree of surveillance and a communication platform between humans, machines, and parts. Digital twins can also play a critical role in facilitating faster decision-making in product trade-ins by nearly eliminating the uncertainty in the conditions of returned end-of-life products.

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In this article, Dr. Tozanli proposed a conceptual predictive twin model for trade-in decision-making through a simulated product-recovery system. A game model embedded in a discrete event simulation model was performed from the manufacturer’s viewpoint to obtain a data-driven trade-in pricing policy in a fully transparent platform. 

Check out Dr. Ozden Tozanli’s article in collaboration with Prof. Elif Kongar and Prof. Surendra M. Gupta in the Sustainability Journal.