Preprint Article Version 1 This version is not peer-reviewed

Towards the Implementation and Integration of a Digital Twin in a Discrete Manufacturing Context

Version 1 : Received: 30 September 2024 / Approved: 30 September 2024 / Online: 1 October 2024 (08:36:01 CEST)

How to cite: Lanzini, M.; Ferretti, I.; Zanoni, S. Towards the Implementation and Integration of a Digital Twin in a Discrete Manufacturing Context. Preprints 2024, 2024092442. https://doi.org/10.20944/preprints202409.2442.v1 Lanzini, M.; Ferretti, I.; Zanoni, S. Towards the Implementation and Integration of a Digital Twin in a Discrete Manufacturing Context. Preprints 2024, 2024092442. https://doi.org/10.20944/preprints202409.2442.v1

Abstract

In the context of enhanced decision-making related to Industry 4.0 and 5.0, this work examines the first step to implement a Digital Twin (DT) in a discrete manufacturing firm. The DT will be required to be adequately integrated with the information systems, especially the Manufacturing Execution System (MES), because the virtual counterpart of the DT itself, a Discrete Event Simulator (DES) model, will exploit MES data for the validation and the monitoring. The objective of the DT is to enhance the decision-making related to production planning, in particular, achieving better on-time delivery to customers. Therefore, the DT intends to depict material flows within the production department to enhance monitoring and control, facilitating the prompt identification of deviations from the plan, and supporting the decision-makers, enabling a more responsive and informed management of delay alerts. The first goal to achieve the DT implementation and integration is to establish a conceptual framework that improves material flow data synchronization. A conceptual integration and implementation framework for the DT will be proposed and discussed, underlying the technical decisions chosen to achieve the functional and integration requirements.

Keywords

digital twin; Industry 4.0; manufacturing execution system; discrete event simulation; dataflow management; decision-making support

Subject

Engineering, Industrial and Manufacturing Engineering

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