Optimizing smart manufacturing systems using digital twin

Robert Ojsteršek (Author), Aljaž Javernik (Author), Borut Buchmeister (Author)

Abstract

Presented paper investigates the application of digital twins for the optimisation of intelligent manufacturing systems and focuses on the comparison between simulation modelling results and real-world production conditions. A digital twin was created in the Simio software environment using a data-driven simulation model derived from a real-world production system. Running the digital twin in real time, which was displayed graphically, facilitated the analysis of key parameters, including the number of finished products, average flow time, workstation utilization and product quality. The discrepancies were attributed to the use of random distributions of input data in the dynamic digital twin, as opposed to the long-term measurements and averages in the real-world system. Despite the limitations in the case study, the results underline the financial justification and predictive capabilities of digital twins for optimising production systems. Real-time operation enables continuous evaluation and tracking of parameters and offers high benefits for intelligent production systems. The study emphasises the importance of accurate selection of input data and warns that even small deviations can lead to inaccurate results. Finally, the paper high-lights the role of digital twins in optimising production systems and argues for careful consideration of input data. It highlights the importance of analysing real-world production systems and creating efficient simulation models as a basis for digital twin solutions. The results encourage extending the research to different types of production, from job shop to mass production, in order to obtain a comprehensive optimisation perspective.

Keywords

pametna proizvodnja;simulacijsko modeliranje;digitalni dvojček;optimizacija;študija primera;smart manufacturing;digital twin;optimisation;simulation modelling;Simio;case study;

Data

Language:	English
Year of publishing:	2023
Typology:	1.01 - Original Scientific Article
Organization:	UM FS - Faculty of Mechanical Engineering
Publisher:	Chair of Production Engineering (CPE), University of Maribor, Faculty of Mechanical Engineering
UDC:	658.5:004.94
COBISS:	182000131
ISSN:	1854-6250
Views:	78
Downloads:	2
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary keywords:	pametna proizvodnja;simulacijsko modeliranje;digitalni dvojček;optimizacija;študija primera;
Type (COBISS):	Article
Pages:	str. 475-485
Volume:	ǂVol. ǂ18
Issue:	ǂno. ǂ4
Chronology:	Dec. 2023
DOI:	10.14743/apem2023.4.486
ID:	23247182