Abstract
The creation of current assembly lines can benefit from the new advances made in the fields of Computer Science and the Internet of Things (IoT) to increase their flexibility and improve their reliability. There are assembly line simulators developed for this purpose. However, these simulators have been designed to model every detail of the line and take hours to be done. The aim of this paper is to introduce a faster and more accurate computer-based solution - ManufactSim- allowing the simulation of a real production system. This implementation derives from a behavioral modular robots simulator enhanced with a 3D display option. The results show that ManufactSim ’s performances are above the standards with an execution time less than 11 s for 8 h shift running on a CAD computer. Our developed solution is able to face this challenge with an highly accurate and efficient simulator without compromise. The performed benchmarks show that we obtain a robust and agile tool needed for a global future solution based on Machine Learning. The benefits of this contribution will permit to automate the generation of industrial assembly lines while caring on multiple optimization criteria.
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Acknowledgemnts
This work was done as a part of a CIFRE (2018-0927) project with Faurecia, funded by the Ministry of Higher Education and Research of France, managed by the Association Nationale de la Recherche et de la Technologie (ANRT).
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Piranda, B., Gautam, I., Meyer, J., El Houd, A., Bourgeois, J. (2022). ManufactSim: Manufacturing Line Simulation Using Heterogeneous Distributed Robots. In: Barolli, L., Hussain, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2022. Lecture Notes in Networks and Systems, vol 450. Springer, Cham. https://doi.org/10.1007/978-3-030-99587-4_12
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