TY - GEN
T1 - Implementation of a Digital Twin Framework in the Modular Housing Industry
AU - Fischer, Anne
AU - Llorens, Jorge Rodriguez
AU - Cai, Zhen
AU - Wilke, Michael
AU - Kessler, Stephan
AU - Fottner, Johannes
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The construction industry is one of the minor digitized industries, and it has been characterized by a below- average increase in productivity in recent decades. The modular housing sector copies the production system of the manufacturing industry to meet these deficits, which makes it a perfect example for evaluating Industry 4.0 technologies. This paper explores the methodology and possibilities of implementing a digital twin of a modular housing production plant to optimize its production. The proposed approach based on a Digital Twin (DT) framework consists of three consecutive parts: (1) analyzing the production system by using the Lean tool of Value-Stream Mapping extended (x-VSM) towards Discrete-Event Simulation (DES) models, (2) collecting real- time data to track and trace the system's bottleneck by using Radio-Frequency Identification Devices (RFID) as a Tracking- and-Tracing system (TaT), and (3) optimizing it by using DES. Three scenarios to eliminate waste, increase throughput, and identify the best possible TaT implementation have been simulated. The results are a 64 % inventory reduction, a 20 % faster production lead time, and the finding of the critical part to be tracked using RFID. The resulting model has shown to be a valuable instrument for understanding the different process interdependencies. Moreover, it has been used as a support tool for middle management to assess the impact of different optimization approaches quantitatively. Overall, this paper shows the implications of combining DES and TaT systems towards a DT of a modular housing production plant.
AB - The construction industry is one of the minor digitized industries, and it has been characterized by a below- average increase in productivity in recent decades. The modular housing sector copies the production system of the manufacturing industry to meet these deficits, which makes it a perfect example for evaluating Industry 4.0 technologies. This paper explores the methodology and possibilities of implementing a digital twin of a modular housing production plant to optimize its production. The proposed approach based on a Digital Twin (DT) framework consists of three consecutive parts: (1) analyzing the production system by using the Lean tool of Value-Stream Mapping extended (x-VSM) towards Discrete-Event Simulation (DES) models, (2) collecting real- time data to track and trace the system's bottleneck by using Radio-Frequency Identification Devices (RFID) as a Tracking- and-Tracing system (TaT), and (3) optimizing it by using DES. Three scenarios to eliminate waste, increase throughput, and identify the best possible TaT implementation have been simulated. The results are a 64 % inventory reduction, a 20 % faster production lead time, and the finding of the critical part to be tracked using RFID. The resulting model has shown to be a valuable instrument for understanding the different process interdependencies. Moreover, it has been used as a support tool for middle management to assess the impact of different optimization approaches quantitatively. Overall, this paper shows the implications of combining DES and TaT systems towards a DT of a modular housing production plant.
KW - Digital Twin (DT)
KW - Discrete-Event Simulation (DES)
KW - Modular housing building
KW - Radio-Frequency Identification Devices (RFID)
KW - Tracking-and- Tracing system (TaT)
KW - extended Value-Stream Mapping (x- VSM)
UR - http://www.scopus.com/inward/record.url?scp=85137097691&partnerID=8YFLogxK
U2 - 10.1109/ICE/ITMC-IAMOT55089.2022.10033306
DO - 10.1109/ICE/ITMC-IAMOT55089.2022.10033306
M3 - Conference contribution
AN - SCOPUS:85137097691
T3 - 2022 IEEE 28th International Conference on Engineering, Technology and Innovation, ICE/ITMC 2022 and 31st International Association for Management of Technology, IAMOT 2022 Joint Conference - Proceedings
BT - 2022 IEEE 28th International Conference on Engineering, Technology and Innovation, ICE/ITMC 2022 and 31st International Association for Management of Technology, IAMOT 2022 Joint Conference - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 28th IEEE International Conference on Engineering, Technology and Innovation, ICE/ITMC 2022 and 31st International Association for Management of Technology, IAMOT 2022 Joint Conference
Y2 - 19 June 2022 through 23 June 2022
ER -