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Synthetic simulated environment for discrete manufacturing systems: A demonstrator through a computational modeling approach
Proceedings - Winter Simulation Conference · 2024
Abstract
Engelskt originalabstract
In light of the challenges posed by the often unavailability of coherent data in manufacturing for operational Artificial Intelligence (AI) decision support systems, the generation and utilization of synthetic datasets have become essential. This study introduces a simple numerical Synthetic Simulated Environment (SSE) using timed and parametrizable Petri Net (PN) modules, embedded in a Directed Acyclic Graph (DAG) structure described by an adjacency matrix to represent material flow. Implemented in PyTorch for seamless integration with AI components, our simulation framework simplifies manufacturing systems, yet remains expandable for diverse use cases. The simulation model was demonstrated displaying its capability of generating synthetic data. This approach explores the practicality and applicability of generated data. It could serve as an ideal environment to benchmark Artificial Intelligence (AI) algorithms in comparative experiments, investigating operational problems featured in the dynamic interactions of discrete manufacturing systems.
Originalkälla: Chalmers Research ↗
I korthet
Simuleringen i PyTorch genererar syntetiska data för diskreta tillverkningssystem. Tidsatta Petri-nät och en riktad graf beskriver produktionsflödet i en utbyggbar miljö för AI-experiment.
Huvudpunkter
- Representerar materialflöden med parametriserade Petri-nät i en riktad acyklisk graf.
- Implementerar simuleringen i PyTorch för integration med AI-komponenter.
- Demonstrerar syntetiska data och en möjlig miljö för jämförande AI-experiment.
Citera arbetet
Silvan Marti, Paulo Victor Lopes, Siyuan Chen, Mohan Rajashekarappa, Elham Rekabi Bana, Amon Göppert, Mélanie Despeisse, Johan Stahre, Björn Johansson (2024). Synthetic simulated environment for discrete manufacturing systems: A demonstrator through a computational modeling approach. Proceedings - Winter Simulation Conference, pp. 1716–1727. https://doi.org/10.1109/WSC63780.2024.10838939
@inproceedings{Chen2024SyntheticSimulationManufacturing,
title = {{Synthetic simulated environment for discrete manufacturing systems: A demonstrator through a computational modeling approach}},
author = {Marti, Silvan and Lopes, Paulo Victor and Chen, Siyuan and Rajashekarappa, Mohan and Rekabi Bana, Elham and Göppert, Amon and Despeisse, Mélanie and Stahre, Johan and Johansson, Björn},
year = {2024},
booktitle = {2024 Winter Simulation Conference (WSC)},
pages = {1716--1727},
doi = {10.1109/WSC63780.2024.10838939},
url = {https://research.chalmers.se/en/publication/545198}
}
Originalabstractet återges från den länkade källposten. Översikten och huvudpunkterna ger korta förklaringar av studien.