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Manufacturing Process Simulation in a Hybrid Cloud Setup

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Standard

Manufacturing Process Simulation in a Hybrid Cloud Setup. / Weiß., Gerhard; Pietraroia., Dario; Sassanelli., Claudio et al.
Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2021. SCITEPRESS Digital Library, 2021. p. 49-58.

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Harvard

Weiß., G, Pietraroia., D, Sassanelli., C & Macedo., H 2021, Manufacturing Process Simulation in a Hybrid Cloud Setup. in Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2021. SCITEPRESS Digital Library, pp. 49-58, 2nd International Conference on Innovative Intelligent Industrial Production and Logistics, 25/10/2021. https://doi.org/10.5220/0010641700003062

APA

Weiß., G., Pietraroia., D., Sassanelli., C., & Macedo., H. (2021). Manufacturing Process Simulation in a Hybrid Cloud Setup. In Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2021 (pp. 49-58). SCITEPRESS Digital Library. https://doi.org/10.5220/0010641700003062

CBE

Weiß. G, Pietraroia. D, Sassanelli. C, Macedo. H. 2021. Manufacturing Process Simulation in a Hybrid Cloud Setup. In Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2021. SCITEPRESS Digital Library. pp. 49-58. https://doi.org/10.5220/0010641700003062

MLA

Weiß., Gerhard et al. "Manufacturing Process Simulation in a Hybrid Cloud Setup". Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2021. SCITEPRESS Digital Library. 2021, 49-58. https://doi.org/10.5220/0010641700003062

Vancouver

Weiß. G, Pietraroia. D, Sassanelli. C, Macedo. H. Manufacturing Process Simulation in a Hybrid Cloud Setup. In Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2021. SCITEPRESS Digital Library. 2021. p. 49-58 doi: 10.5220/0010641700003062

Author

Weiß., Gerhard ; Pietraroia., Dario ; Sassanelli., Claudio et al. / Manufacturing Process Simulation in a Hybrid Cloud Setup. Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2021. SCITEPRESS Digital Library, 2021. pp. 49-58

Bibtex

@inproceedings{ff08f61b00d24dcba23add477763ee87,
title = "Manufacturing Process Simulation in a Hybrid Cloud Setup",
abstract = "Model-based design of manufacturing robotic systems involving the usage of different tools, models and the co-simulation of the system behaviour benefits from collaborative platforms enabling ready-to-use and cloud-hosted tools and models. Nonetheless, due to market segmentation and the difficulty to deploy and support all the existing tools and models in such a platform, it is, therefore, reasonable to consider a hybrid cloud-setup where some tools run in the public cloud and other are only available in private clouds or dedicated machines behind the walls of the licensed institution. In this paper, we report on a experiment of such scenario, where a Matlab/Simulink TM, LS-Dyna, and Model.CONNECT TM powered co-simulation tool suite running in a private cloud is combined with the DDD Simulation tool running inside a public cloud. Due to this setup it was possible to combine a 1D hot stamping process simulation with a 3D visualisation. Finally the results of the process simulation were improved by considering realistic movement of the robot. Our study elicited several limitations and feature requests that need to be addressed to better support a hybrid cloud setup for model-based design practitioners. We expect this initial contribution to trigger ground breaking research encompassing all the community members interested in hybrid co-simulation setups.",
keywords = "Co-simulation, Hybrid-cloud, Manufacturing, Model-based Design, Tools",
author = "Gerhard Wei{\ss}. and Dario Pietraroia. and Claudio Sassanelli. and Hugo Macedo.",
year = "2021",
doi = "10.5220/0010641700003062",
language = "Udefineret/Ukendt",
isbn = "978-989-758-535-7",
pages = "49--58",
booktitle = "Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2021",
publisher = "SCITEPRESS Digital Library",
note = "2nd International Conference on Innovative Intelligent Industrial Production and Logistics ; Conference date: 25-10-2021 Through 27-10-2021",

}

RIS

TY - GEN

T1 - Manufacturing Process Simulation in a Hybrid Cloud Setup

AU - Weiß., Gerhard

AU - Pietraroia., Dario

AU - Sassanelli., Claudio

AU - Macedo., Hugo

PY - 2021

Y1 - 2021

N2 - Model-based design of manufacturing robotic systems involving the usage of different tools, models and the co-simulation of the system behaviour benefits from collaborative platforms enabling ready-to-use and cloud-hosted tools and models. Nonetheless, due to market segmentation and the difficulty to deploy and support all the existing tools and models in such a platform, it is, therefore, reasonable to consider a hybrid cloud-setup where some tools run in the public cloud and other are only available in private clouds or dedicated machines behind the walls of the licensed institution. In this paper, we report on a experiment of such scenario, where a Matlab/Simulink TM, LS-Dyna, and Model.CONNECT TM powered co-simulation tool suite running in a private cloud is combined with the DDD Simulation tool running inside a public cloud. Due to this setup it was possible to combine a 1D hot stamping process simulation with a 3D visualisation. Finally the results of the process simulation were improved by considering realistic movement of the robot. Our study elicited several limitations and feature requests that need to be addressed to better support a hybrid cloud setup for model-based design practitioners. We expect this initial contribution to trigger ground breaking research encompassing all the community members interested in hybrid co-simulation setups.

AB - Model-based design of manufacturing robotic systems involving the usage of different tools, models and the co-simulation of the system behaviour benefits from collaborative platforms enabling ready-to-use and cloud-hosted tools and models. Nonetheless, due to market segmentation and the difficulty to deploy and support all the existing tools and models in such a platform, it is, therefore, reasonable to consider a hybrid cloud-setup where some tools run in the public cloud and other are only available in private clouds or dedicated machines behind the walls of the licensed institution. In this paper, we report on a experiment of such scenario, where a Matlab/Simulink TM, LS-Dyna, and Model.CONNECT TM powered co-simulation tool suite running in a private cloud is combined with the DDD Simulation tool running inside a public cloud. Due to this setup it was possible to combine a 1D hot stamping process simulation with a 3D visualisation. Finally the results of the process simulation were improved by considering realistic movement of the robot. Our study elicited several limitations and feature requests that need to be addressed to better support a hybrid cloud setup for model-based design practitioners. We expect this initial contribution to trigger ground breaking research encompassing all the community members interested in hybrid co-simulation setups.

KW - Co-simulation

KW - Hybrid-cloud

KW - Manufacturing

KW - Model-based Design

KW - Tools

U2 - 10.5220/0010641700003062

DO - 10.5220/0010641700003062

M3 - Konferencebidrag i proceedings

SN - 978-989-758-535-7

SP - 49

EP - 58

BT - Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2021

PB - SCITEPRESS Digital Library

T2 - 2nd International Conference on Innovative Intelligent Industrial Production and Logistics

Y2 - 25 October 2021 through 27 October 2021

ER -