摘要
火焰筒作为燃气轮机的核心零部件,关系到燃气轮机的热耗、性能以及排放等众多指标,为了提升火焰筒生产线的产量,缩短产品的生产周期,提高产品的质量,同时验证工艺路线的合理性,设备选型与设备数量的合理性,路径规划的合理性。通过在虚拟环境中真实的还原火焰筒生产线,利用虚拟仿真技术,对火焰筒产线进行等尺寸的二维建模、布局,并结合车间的工艺、物料、设备、库存、物流、班次等,模拟实际工厂的生产节拍创建仿真模型,开发仿真逻辑;然后通过实验管理器、瓶颈分析器,利用遗传算法[1~4]优化仿真模型,分析设备、物流瓶颈,并给出优化方案。最终实现在虚拟环境中对火焰筒生产线规划、部署、仿真、优化和验证,对于不合理的地方直接调整,不需要在实施阶段花费高成本来验证和调整,大大提升生产效率,提高产量,减少产品生产周期,保证此后大规模生产的稳定性,最大限度的降低企业成本。
As the core component of gas turbine,liner is related to many indexes such as heat consumption,performance and emission of gas turbine.In order to improve the output of liner production line,shorten the production cycle,improve the quality of products and the rationality of process route,equipment selection,equipment quantity and path planning.Using virtual simulation technology to restore the real liner production line in the virtual environment,the production line of liner is modeled and laid out in two dimensions of equal size.Combining with the process,material,equipment,inventory,logistics and shift of workshop,the simulation model is created to simulate the production rhythm of actual factory and the simulation logic is developed.Then,through the experiment manager and bottleneck analyzer,using the genetic algorithm[1~4]to optimize the simulation model,analyze the bottleneck of equipment and logistics,and give the optimization scheme.Finally,the liner production line planning,deployment,simulation,optimization and verification are realized in the virtual environment.For unreasonable situations,it can be adjusted directly in virtual environment,there is no need for costly verification and adjustment at the implementation stage.It greatly improves production efficiency,improves output,reduces product production cycle,guarantees the stability of large-scale production,and minimizes enterprise costs.
作者
石菁菁
苑鑫
张腾
SHI Jingjing;YUAN Xin;ZHANG Teng(Dalian University of Technology,Dalian 116000;703 Institute of CSIS,Harbin 150078)
出处
《舰船电子工程》
2019年第12期117-120,共4页
Ship Electronic Engineering
关键词
工厂仿真
燃气轮机
产能
物流
仿真
产线
遗传算法
plant simulation
gas turbine
capacity
logistics
virtual simulation
production line
genetic algorithm