Kulac, OrayEkren, Banu Y.Toy, A. Ozgur2023-02-142023-02-142023-02-06Kulac O, Ekren BY, Toy AO. (2023) Digital twins for decision making in supply chains. In: Global Joint Conference on Industrial Engineering and Its Application Areas: Industrial Engineering in the Covid-19 Era, 29-30 October 2022, Istanbul, Turkey. GJCIE 2022. Lecture Notes in Management and Industrial Engineering. Springer, Cham. pp. 86-96978-3-031-25846-62198-0772https://doi.org/10.1007/978-3-031-25847-3_9https://dspace.lib.cranfield.ac.uk/handle/1826/19179This paper studies the utilization of digital twins (DTs) as a decision support tool in supply chains (SCs) by providing a framework. DT is an emerging technology-based modeling approach reflecting a virtual representation of an object or system that can help organizations monitor operations, perform predictive analytics, and improve their processes. For instance, it may provide a digital replica of operations in a factory, communications network, or the flow of goods through an SC system. In this paper, by focusing on SC systems, we explore the critical decisions in SCs and their related data to track, to make the right decisions within DTs. We introduce six main functions in SCs and define frequent decisions that can be taken under those functions. After defining the required decisions, we also identify which data/information would help to make correct decisions within those DTs.enDigital twinSupply chainDecision problemsDecision supportConference paper978-3-031-25847-32198-0780