Research library / 2024 / Conference paper
Synthetic simulated environment for discrete manufacturing systems: A demonstrator through a computational modeling approach
Proceedings - Winter Simulation Conference · 2024
Abstract
Original English abstract
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.
Original source: Chalmers Research ↗
In brief
This PyTorch-based simulation generates synthetic data for discrete manufacturing systems. Timed Petri nets and a directed graph represent production flow, creating an expandable environment for manufacturing AI experiments.
Key points
- Models material flow with parameterized Petri-net modules inside a directed acyclic graph.
- Implements the simulator in PyTorch to facilitate integration with AI components.
- Demonstrates synthetic-data generation and a potential environment for comparative AI experiments.
Cite this work
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}
}
Abstract reproduced from the linked source record. The overview and key points are concise explanations of the study.