Synthetic Simulated Environment for Discrete Manufacturing Systems: A Demonstrator Through a Computational Modeling Approach

Winter Simulation Conference, pp. 1716–1727

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.

Authors 9

1. Silvan Marti

   Chalmers University of Technology

   Affiliation as printed

   Chalmers University of Technology,Dept. of Industrial and Materials Science,Gothenburg,SWEDEN

2. Paulo Victor Lopes

   Chalmers University of Technology

   Affiliation as printed

   Chalmers University of Technology,Dept. of Industrial and Materials Science,Gothenburg,SWEDEN

3. Siyuan Chen

   Chalmers University of Technology

   Affiliation as printed

   Chalmers University of Technology,Dept. of Industrial and Materials Science,Gothenburg,SWEDEN

4. Mohan Rajashekarappa

   Chalmers University of Technology

   Affiliation as printed

   Chalmers University of Technology,Dept. of Industrial and Materials Science,Gothenburg,SWEDEN

5. Elham Rekabi Bana

   Chalmers University of Technology

   Affiliation as printed

   Chalmers University of Technology,Dept. of Industrial and Materials Science,Gothenburg,SWEDEN

6. Amon Göppert Aachen Lab. for Machine Tools and Production Eng. (WZL)

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Lab. for Machine Tools and Production Eng. (WZL),Aachen,GERMANY

7. Mélanie Despeisse

   Chalmers University of Technology

   Affiliation as printed

   Chalmers University of Technology,Dept. of Industrial and Materials Science,Gothenburg,SWEDEN

8. Johan Stahre

   Chalmers University of Technology

   Affiliation as printed

   Chalmers University of Technology,Dept. of Industrial and Materials Science,Gothenburg,SWEDEN

9. Björn Johansson

   Chalmers University of Technology

   Affiliation as printed

   Chalmers University of Technology,Dept. of Industrial and Materials Science,Gothenburg,SWEDEN