研究成果 / 2024 / 会议论文
Synthetic simulated environment for discrete manufacturing systems: A demonstrator through a computational modeling approach
离散制造系统的综合仿真环境：基于计算建模的演示
Proceedings - Winter Simulation Conference · 2024
摘要
原始英文摘要
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.
原始来源: Chalmers Research ↗
这项研究在做什么
本文基于 PyTorch 构建离散制造系统仿真，生成可用于研究的合成数据。定时 Petri 网与有向图共同描述生产流，为制造 AI 实验提供可扩展环境。
研究要点
- 使用有向无环图中的参数化 Petri 网模块描述物料流。
- 基于 PyTorch 实现仿真器，便于与 AI 组件集成。
- 演示合成数据生成，并为 AI 算法对比实验提供可扩展环境。
引用这项成果
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}
}
英文摘要来自所链接的原始记录；研究解读和要点用于简要说明论文内容。