An Implementation Approach for an Academic Learning Factory for the Metal Forming Industry with Special Focus on Digital Twins and Finite Element Analysis

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@article{cb95269aaa9b4513994db98974755d44,
title = "An Implementation Approach for an Academic Learning Factory for the Metal Forming Industry with Special Focus on Digital Twins and Finite Element Analysis",
abstract = "The requirements for the planning, implementation and operation of an academic learning factory vary depending on the specific area of the respective institution. This paper provides an approach for the planning and implementation of such a factory, specifically tailored to the requirements of the metal forming industry. This learning factory will then be operated at the Chair of Metalforming at the Montanuniversit{\"a}t Leoben (MUL). The objective is to monitor and control forming units of different technological maturity in a common system. The industrial software used, ibaPDA for data logging and ibaAnalyzer for automated further processing, is widespread in practice and enables students to learn the required skills as close to practice as possible. In addition, Analog to Digital (A/D) converters and machine hour counters will be implemented to illustrate the retrofitting approach in practice. For the planning and implementation of Digital Shadows and Digital Twins, common Finite Element (FE) simulation programs will be used and the possibilities of connectivity between machines, simulation programs and automation software will be demonstrated. The project presented here should thus make an important contribution to the training of future specialists with special consideration of the increasing interdisciplinarity in manufacturing technology.",
keywords = "digital twin, Smart factory, learning factory, digitalization, Industry 4.0",
author = "Benjamin Ralph and Andreas Schwarz and Martin Stockinger",
note = "Publisher Copyright: {\textcopyright} 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the 10th Conference on Learning Factories 2020.; Conference on Learning Factories, CLF 2020 ; Conference date: 15-04-2020 Through 17-04-2020",
year = "2020",
month = apr,
day = "29",
doi = "https://doi.org/10.1016/j.promfg.2020.04.103",
language = "English",
volume = "45",
pages = "253--258",
journal = "Procedia Manufacturing",
issn = "2351-9789",
publisher = "Elsevier",
number = "45",
url = "https://www.tugraz.at/events/clf2020/info/",

}

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TY - JOUR

T1 - An Implementation Approach for an Academic Learning Factory for the Metal Forming Industry with Special Focus on Digital Twins and Finite Element Analysis

AU - Ralph, Benjamin

AU - Schwarz, Andreas

AU - Stockinger, Martin

N1 - Conference code: 10

PY - 2020/4/29

Y1 - 2020/4/29

N2 - The requirements for the planning, implementation and operation of an academic learning factory vary depending on the specific area of the respective institution. This paper provides an approach for the planning and implementation of such a factory, specifically tailored to the requirements of the metal forming industry. This learning factory will then be operated at the Chair of Metalforming at the Montanuniversität Leoben (MUL). The objective is to monitor and control forming units of different technological maturity in a common system. The industrial software used, ibaPDA for data logging and ibaAnalyzer for automated further processing, is widespread in practice and enables students to learn the required skills as close to practice as possible. In addition, Analog to Digital (A/D) converters and machine hour counters will be implemented to illustrate the retrofitting approach in practice. For the planning and implementation of Digital Shadows and Digital Twins, common Finite Element (FE) simulation programs will be used and the possibilities of connectivity between machines, simulation programs and automation software will be demonstrated. The project presented here should thus make an important contribution to the training of future specialists with special consideration of the increasing interdisciplinarity in manufacturing technology.

AB - The requirements for the planning, implementation and operation of an academic learning factory vary depending on the specific area of the respective institution. This paper provides an approach for the planning and implementation of such a factory, specifically tailored to the requirements of the metal forming industry. This learning factory will then be operated at the Chair of Metalforming at the Montanuniversität Leoben (MUL). The objective is to monitor and control forming units of different technological maturity in a common system. The industrial software used, ibaPDA for data logging and ibaAnalyzer for automated further processing, is widespread in practice and enables students to learn the required skills as close to practice as possible. In addition, Analog to Digital (A/D) converters and machine hour counters will be implemented to illustrate the retrofitting approach in practice. For the planning and implementation of Digital Shadows and Digital Twins, common Finite Element (FE) simulation programs will be used and the possibilities of connectivity between machines, simulation programs and automation software will be demonstrated. The project presented here should thus make an important contribution to the training of future specialists with special consideration of the increasing interdisciplinarity in manufacturing technology.

KW - digital twin

KW - Smart factory

KW - learning factory

KW - digitalization

KW - Industry 4.0

UR - http://www.scopus.com/inward/record.url?scp=85085526547&partnerID=8YFLogxK

U2 - https://doi.org/10.1016/j.promfg.2020.04.103

DO - https://doi.org/10.1016/j.promfg.2020.04.103

M3 - Conference article

VL - 45

SP - 253

EP - 258

JO - Procedia Manufacturing

JF - Procedia Manufacturing

SN - 2351-9789

IS - 45

T2 - Conference on Learning Factories

Y2 - 15 April 2020 through 17 April 2020

ER -