文章基本信息

标题：Digital Twin for Inventory Planning of Fresh Produce
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作者：Tsega Y. Melesse ; Matteo Bollo ; Valentina Di Pasquale 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2022
卷号：55
期号：10
页码：2743-2748
DOI：10.1016/j.ifacol.2022.10.134
语种：English
出版社：Elsevier
摘要：The management of perishable food inventory demands special attention. Fruits quickly lose their freshness and perish if they are not consumed within a specified period. It is critical to develop a management tool based on the Internet of Things that can efficiently integrate all the dynamic data associated with various types of resources in real-time along the supply chain. This research is part of a comprehensive supply chain framework developed to analyze food bank logistics supply chain interactions. The study will mainly focus on the use of historical time-series data to create a digital twin that can anticipate future events. The digital twin framework was built based on the operational trend of the Italian food bank to strengthen the decision support system related to the fresh food inventory. The SAP Analytics Cloud was used to create a solution that would help the organization better satisfy consumer needs by reducing fruit waste in the inventory.
关键词：Time-series;Digital Twin;Predictive Forecast;Inventory Planning;Fruits