Concept of hybrid modeled digital twins and its application for an energy management of manufacturing systems

Pascal Langlotz; Matthias Klar; Li Yi; Marco Hussong; Fábio J.P. Sousa; Jan C. Aurich

doi:10.1016/j.procir.2022.09.098

Concept of hybrid modeled digital twins and its application for an energy management of manufacturing systems

Pascal Langlotz^*
, Matthias Klar
, Li Yi
, Marco Hussong
, Fábio J.P. Sousa
, Jan C. Aurich

^*Corresponding author for this work

The University of Kaiserslautern-Landau
Universidade Federal do Rio Grande do Norte

Research output: Contribution to journal › Conference article › peer-review

25 Scopus citations

Abstract

Digital twins are used to digitally map properties and states of real manufacturing systems. Based on relevant data-driven and physics-based digital models, digital twins are employed to monitor, analyze and predict aspects of the corresponding manufacturing system. Therefore, digital twins are used on different manufacturing levels, e.g. the factory, machine, or process level. This paper presents a concept for digital twins that are modeled by physics-based and data-driven models. Furthermore, this concept is validated with the help of a use case that controls an energy management system of a model-scale factory by finding the optimal time for charging and using the battery.

Original language	English
Pages (from-to)	549-554
Number of pages	6
Journal	Procedia CIRP
Volume	112
DOIs	https://doi.org/10.1016/j.procir.2022.09.098
State	Published - 2022
Externally published	Yes
Event	15th CIRP Conference on Intelligent Computation in Manufacturing Engineering, ICME 2021 - Naples, Italy Duration: 14 Jul 2021 → 16 Jul 2021

Keywords

Data-driven Models
Digital Twin
Physics-based Models
Production

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10.1016/j.procir.2022.09.098

Cite this

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title = "Concept of hybrid modeled digital twins and its application for an energy management of manufacturing systems",

abstract = "Digital twins are used to digitally map properties and states of real manufacturing systems. Based on relevant data-driven and physics-based digital models, digital twins are employed to monitor, analyze and predict aspects of the corresponding manufacturing system. Therefore, digital twins are used on different manufacturing levels, e.g. the factory, machine, or process level. This paper presents a concept for digital twins that are modeled by physics-based and data-driven models. Furthermore, this concept is validated with the help of a use case that controls an energy management system of a model-scale factory by finding the optimal time for charging and using the battery.",

keywords = "Data-driven Models, Digital Twin, Physics-based Models, Production",

author = "Pascal Langlotz and Matthias Klar and Li Yi and Marco Hussong and Sousa, \{F{\'a}bio J.P.\} and Aurich, \{Jan C.\}",

note = "Publisher Copyright: {\textcopyright} 2022 The Author(s).; 15th CIRP Conference on Intelligent Computation in Manufacturing Engineering, ICME 2021 ; Conference date: 14-07-2021 Through 16-07-2021",

year = "2022",

doi = "10.1016/j.procir.2022.09.098",

language = "英语",

volume = "112",

pages = "549--554",

journal = "Procedia CIRP",

issn = "2212-8271",

publisher = "Elsevier B.V.",

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T1 - Concept of hybrid modeled digital twins and its application for an energy management of manufacturing systems

AU - Langlotz, Pascal

AU - Klar, Matthias

AU - Yi, Li

AU - Hussong, Marco

AU - Sousa, Fábio J.P.

AU - Aurich, Jan C.

PY - 2022

Y1 - 2022

N2 - Digital twins are used to digitally map properties and states of real manufacturing systems. Based on relevant data-driven and physics-based digital models, digital twins are employed to monitor, analyze and predict aspects of the corresponding manufacturing system. Therefore, digital twins are used on different manufacturing levels, e.g. the factory, machine, or process level. This paper presents a concept for digital twins that are modeled by physics-based and data-driven models. Furthermore, this concept is validated with the help of a use case that controls an energy management system of a model-scale factory by finding the optimal time for charging and using the battery.

AB - Digital twins are used to digitally map properties and states of real manufacturing systems. Based on relevant data-driven and physics-based digital models, digital twins are employed to monitor, analyze and predict aspects of the corresponding manufacturing system. Therefore, digital twins are used on different manufacturing levels, e.g. the factory, machine, or process level. This paper presents a concept for digital twins that are modeled by physics-based and data-driven models. Furthermore, this concept is validated with the help of a use case that controls an energy management system of a model-scale factory by finding the optimal time for charging and using the battery.

KW - Data-driven Models

KW - Digital Twin

KW - Physics-based Models

KW - Production

UR - https://www.scopus.com/pages/publications/85142607424

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DO - 10.1016/j.procir.2022.09.098

M3 - 会议文章

AN - SCOPUS:85142607424

SN - 2212-8271

VL - 112

SP - 549

EP - 554

JO - Procedia CIRP

JF - Procedia CIRP

T2 - 15th CIRP Conference on Intelligent Computation in Manufacturing Engineering, ICME 2021

Y2 - 14 July 2021 through 16 July 2021

ER -

Concept of hybrid modeled digital twins and its application for an energy management of manufacturing systems

Abstract

Keywords

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