基于GSPN的过程建模分析方法研究

针对过程模型执行的不确定性特点,对基于广义随机Petri网(GSPN)的过程建模和仿真分析技术进行研究和讨论。该方法适用于使用随机变量,特别是分布函数描述过程模型中的活动、状态和转移这些基本特征。它可以最终通过稳定状态概率求解制造系统过程模型或子过程中等待时间、资源的利用率以及过程模型吞吐量等性能参数。建立了流程重构的定量分析技术基本方法,它为动态制造模型过程建模提供了持续改进的机制和计算方法。最后通过一个质量保证的工作流给出了分析的实例与步骤。

STUDY ON ANALYSIS OF PROCESS MODEL BY GENERAL STOCHASTIC PETRI NET(GSPN)

Considering the uncertainty during execution of process model, the performance evaluation and analysis of process model are presented by general stochastic Petri net (GSPN). This methodology describes the basic process characters of activities, states and transitions associated with exponential distribution or other stochastic variables. The capabilities of latency time, utility of resource and throughput of the process model and its subnet are calculated through the solving of steady probability. The result also provides the quantitative functions in reconfiguration of process model and manufacturing system for continuous improvement. Finally a quality assurance workflow model demonstrates the process steps.