Conference Agenda

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Session Overview
D2S3T1: Industry 4.0 and Digital Twins
Thursday, 24/Feb/2022:
2:45pm - 3:45pm

Session Chair: Walter Lang

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Managing Interfaces between Smart Factories and Digital Supply Chains

Zander, Bennet1,2; Lange, Kerstin1; Haasis, Hans-Dietrich2

1Jade University of Applied Sciences, Germany; 2University of Bremen, Germany

The digital transformation of industry and the accompanying virtualization of supply chains are creating new physical, contractual and organizational boundaries between the physical and virtual world. These interfaces need to be analyzed in order to solve potential challenges at an early stage. The aim of this paper is to provide an overview of future interfaces between smart factories, systems and parties in the supply chain. Furthermore, it is fundamentally investigated how they are managed and communicated. The approach is based on a comprehensive literature review, in which the design preconditions of smart factories and adaptive environments are examined. Subsequently, the review results are analyzed using the three interface management steps definition, control and communication to identify their future controlling. The paper demonstrates how five technology network levels can make a significant contribution to successful operations by handling interfaces and defining responsibilities between transformed processes in the supply chain.

Digital Twin features for the Intelligent Container

Jedermann, Reiner1; Lang, Walter1; Geyer, Martin2; Mahajan, Pramod2

1Universität Bremen, Germany; 2Leibniz-Institut für Agrartechnik und Bioökonomie e.V. (ATB)

The “Intelligent Container” for remote monitoring of refrigerated transports of fresh fruits already implements typical features of digital twins, including remote sensing and modeling of physical and biological objects. This article asks how the Intelligent Container can be extended to make the best use of digital twin concepts. Existing applications in agricultural science focus on offline simulation models that can predict shelf life and the effects of packaging on cooling but cannot integrate real-time data or correct their current estimates according to those data. This update feature is considered a key component of digital twins. The related challenges and algorithms can be best understood from the viewpoint of systems theory and state-space description. Internal properties of real objects can be either directly measurable, hidden, or unobservable, and implementation of the update process should be adapted accordingly. Using ocean transport and banana processing as an example, this paper demonstrates how models can be made “updateable”, in addition to discussing the necessary steps for linking different sub-models over a standardized platform according to the “publish/subscribe” pattern.

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