ESPN-Based Modeling of Multi-level Characterization of Flexible Manufacturing Workshop

doi:10.3901/JME.2025.08.399

Abstract

Abstract: Digital representation models serve as the foundation for optimization analysis in flexible manufacturing workshops. To address the issue of reconfiguring representation models when queueing theory-based mathematical models lack precision or become overly detailed， improvements are made to the definition and triggering rules of the classical Extended Stochastic Petri Nets (ESPN). By incorporating hierarchical modeling theory， a multi-level digital representation model for flexible manufacturing workshops based on ESPN is proposed. Using an aerospace tubular segment flexible manufacturing workshop as an example， multi-level Petri net digital representation models for the workshop layer， processing unit layer， and equipment layer are constructed. Simulation analysis of the multi-level model is conducted based on the Monte Carlo method. Through 1 000 000 simulation runs， the simulation performance of different level models is evaluated from two aspects: capacity bottleneck analysis and capacity reliability analysis. The results indicate that all level Petri net models exhibit similar simulation capabilities， meaning the multi-level representation model effectively addresses the issue of model reconfiguration under low precision or high computational complexity conditions. This provides a new approach and methodology for constructing digital representation models for flexible manufacturing system workshops and offers a simple solution for switching between different analysis levels in representation models.

Key words: extended stochastic Petri nets, digital characterization models, multilevel Petri net models, capacity bottleneck analysis, capacity reliability

CLC Number:

TH165
TP301

DENG Wenzhang, ZHANG Qian, WU Le, YANG Wanran, YANG Chunliu. ESPN-Based Modeling of Multi-level Characterization of Flexible Manufacturing Workshop[J]. Journal of Mechanical Engineering, 2025, 61(8): 399-412.

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