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Integrating PHM into production scheduling through a digital twin-based framework
Conference proceeding   Open access   Peer reviewed

Integrating PHM into production scheduling through a digital twin-based framework

Elisa Negri, Laura Cattaneo, Vibhor Pandhare, Marco Macchi and Jay Lee
IFAC-PapersOnLine, Vol.55(19), pp.31-36
5th IFAC workshop on advanced maintenance engineering, services and technologies AMEST 2022 (Bogotà, Colombia, 26/07/2022–29/07/2022)
2022
Scopus ID: 2-s2.0-85142237214
Web of Science ID: WOS:000860839700006

Abstract

Digital twin Equipment health Fault detection and diagnosis Health management PHM Production scheduling Prognostics Automation & control systems Science & technology Technology
Production scheduling has a long history of research but still presents open challenges, when considering production systems with uncertainty. The digitization, and in particular Digital Twins, may play a role in progressing the research field. The paper proposes a framework to exploit the Digital Twin synchronization with the field to include health assessment models into the simulation-based optimization of the production system scheduling. The health assessment is based on a modelling of failure modes and monitoring signals to connect the physical production resources to health and operating states in order to have a more accurate prediction of the makespan with respect to the actual makespan of the production system. The scheduling framework is validated through a laboratory application in the Industry 4.0 Lab at the School of Management of Politecnico di Milano. Copyright (C) 2022 The Authors.
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https://doi.org/10.1016/j.ifacol.2022.09.180View
Published (Version of record) Open CC BY-NC-ND V4.0

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