Towards a digital twin simulation for cycle times analysis in a cyber-physical production system

4Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The Digital Twin concept refers to the virtual representation of physical assets and is an emerging technology in the I4.0 paradigm for digital transformation. Digital Twin integration with discrete-event simulation models is the key enabler to create digital models of real dynamic manufacturing systems. Usually, simulation alone does not support optimization and advanced analytics, especially considering the lack of real-time data from the physical system. One of the biggest challenges for manufacturers is to enable integration between simulation models and Digital Twin technology for real-time data exchange, such as monitoring and optimization of cycle times and reducing waste. The lack of standards to build the Digital Twin concept explains this issue. This study addresses this problem by proposing a communication interface between a Python-based Digital Twin (DINASORE) and a Java-based AnyLogic simulation model. DINASORE supports Function Blocks compliant with the IEC 61499 standard and external communication using OPC UA. Cycle time data is collected automatically by the Digital Twin in the Edge layer of the Cyber-Physical Production System and made available to the simulation model via OPC UA. Results show that it is possible to analyse the production process and propose optimizations in real-time.

Cite

CITATION STYLE

APA

Barbosa, V., Pinto, R., Pinheiro, J., Gonçalves, G., & Ribeiro, A. (2023). Towards a digital twin simulation for cycle times analysis in a cyber-physical production system. In Proceedings of the International Conference on Simulation and Modeling Methodologies, Technologies and Applications (Vol. 1, pp. 369–376). Science and Technology Publications, Lda. https://doi.org/10.5220/0012123100003546

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free