基于随机赋时Petri网的原烟卸货物流系统建模与仿真

Modeling and simulation of raw tobacco unloading cargo flow system based on stochastic timed Petri nets

复烤厂物流活动中原烟卸货环节存在工人作业不合理、装框时间过慢、空框准备时间过长,造成整体卸货效率低,导致后续生产不连续。为解决上述问题提出改进方案,首先,根据卸货作业流程建立原烟卸货物流系统的随机赋时Petri网模型;其次,建立对应Anylogic仿真模型;最后,通过复烤厂实际数据进行仿真优化。仿真实验表明所用方法缩短了空框准备时间、自动装框时间,提高了其整体装框效率和卸车工人、整形工人的资源利用率。同时,验证了模型的有效性,为复烤厂在卸货环节提供参考。

Aiming at the problems of unreasonable work of workers,too slow loading time,and too long preparation time for empty frames in unloading of raw tobacco in logistics activities of redrying plant,the overall unloading efficiency is low,and the subsequent production is discontinuous.First,the random timed Petri net model of the raw tobacco unloading logistics system was established according to unloading operation process;secondly,the corresponding Anylogic simulation model was established;finally,the simulation optimization was carried out through the actual data of the redrying plant.The simulation experiment shows that the method used shortens the preparation time of empty frame and the time of automatic frame loading,and improves the overall frame loading efficiency and the resource utilization rate of unloading workers and shaping workers.Meanwhile,the validity of the model is verified,which provides a reference for redrying plant in unloading process.