基于ESPN的柔性制造车间多层级表征建模研究

doi:10.3901/JME.2025.08.399

摘要/Abstract

摘要： 数字化表征模型是柔性制造车间优化分析的基础。针对基于排队论构建的数学表征模型在精度不足或过于精细时需重新构建的表征模型问题，对经典的扩展随机Petri网(Extended stochastic Petri nets，ESPN)的定义及触发规则进行了改进，并结合分层建模理论，提出一种基于ESPN的多层级柔性制造车间数字化表征模型。以某航空航天筒段柔性制造车间为例，构建车间层、加工单元层和设备层的多层级Petri网数字化表征模型，并基于蒙特卡洛方法对多层级模型进行了仿真分析。通过1 000 000次模拟仿真，从产能瓶颈分析和产能可靠性分析两个方面评估了不同层级模型的模拟性能。结果表明，各层级Petri网模型具备相似的模拟能力，因此多层级表征模型能够有效解决传统模型在低精度或高计算复杂度情况下表征模型难以重构的问题。这为柔性制造系统车间数字表征模型的构建提供了新的思路和方法，并为切换表征模型的分析层级提供了一种简便的解决方案。

关键词: 扩展随机Petri网, 数字化表征模型, 多层级Petri网模型, 产能瓶颈分析, 产能可靠性

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

中图分类号:

TH165
TP301

邓文章, 张倩, 吴乐, 杨万然, 杨春柳. 基于ESPN的柔性制造车间多层级表征建模研究[J]. 机械工程学报, 2025, 61(8): 399-412.

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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