Synthetic simulated environment for discrete manufacturing systems: A demonstrator through a computational modeling approach
Paper in proceeding, 2024
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.
Author
Silvan Marti
Chalmers, Industrial and Materials Science, Production Systems
Paulo Victor Lopes
Chalmers, Industrial and Materials Science, Production Systems
Instituto Tecnológico de Aeronáutica (ITA)
Siyuan Chen
Chalmers, Industrial and Materials Science, Production Systems
Mohan Rajashekarappa
Chalmers, Industrial and Materials Science, Production Systems
Elham Rekabi Bana
Chalmers, Industrial and Materials Science, Product Development
Amon Göppert
RWTH Aachen University
Mélanie Despeisse
Chalmers, Industrial and Materials Science, Production Systems
Johan Stahre
Chalmers, Industrial and Materials Science, Production Systems
Björn Johansson
Chalmers, Industrial and Materials Science, Production Systems
Proceedings - Winter Simulation Conference
08917736 (ISSN)
1716-17279798331534202 (ISBN)
2024 Winter Simulation Conference, WSC 2024
Orlando, USA,
Orlando, USA,
Subject Categories (SSIF 2025)
Computer Sciences
DOI
10.1109/WSC63780.2024.10838939