基于Factory Simulation的增材制造智能产线优化研究
刘贺童，马瑞
（北京动力机械研究所，北京 100074）
摘要：为解决某航空发动机核心零部件增材制造产线预设方案的验证优化问题，利用Factory Simulation生产系统仿真软件，对车间布局和AGV物流路线进行二维化模型构建，输入物流调度数据，通过设计DOE试验，以最小化产量完成时间为目标，得到瓶颈工序为钳工、超声波清洗、X光工位，在仿真环境下得到当前预设条件下的AGV利用情况。分析瓶颈工位，对比后得到最优加工站个数，并以车间内正常工作时的AGV平均响应时长为依据讨论最优AGV台数。优化后完成产线年产量目标的时间缩短了12%，车间内投入的物流设备成本降低了20%。优化结果在现有车间预设方案的基础上为有效提高预设车间的生产效率、减少车间成本提出了改进建议。
关键词：智能制造；系统仿真；DOE
中图分类号：TH166 文献标志码：A doi：10.3969/j.issn.1006-0316.2024.04.002
文章编号：1006-0316 (2024) 04-0007-09
Optimization of Intelligent Production Line for Additive Manufacturing Based on Factory Simulation
LIU Hetong，MA Rui
( Beijing Power Machinery Research Institute, Beijing 100074, China )
Abstract：To address the verification and optimization of the preset program for the additive manufacturing production line of a certain aero engine's core components, Factory Simulation production system simulation software was used to construct a 2D model of workshop layout and AGV logistics route. Logistics scheduling data was input and the DOE method was used to minimize the completion time of production volume. The bottleneck processes were identified as fitter, ultrasonic cleaning and X-ray workstations. The AGVs utilization under the current preset conditions was obtained in the simulation environment. After analyzing the bottleneck workstations, the optimal number of processing stations was obtained through comparison. The optimal number of AGVs was discussed based on the average response time of AGVs during normal operation in the workshop. After optimization, the time to achieve the annual production target of the assembly line was reduced by 12%, and the logistics equipment cost in the workshop was reduced by 20%. The optimization results provide effective suggestions for improving the production efficiency and reducing the cost of the preset workshop.
Key words：smart manufacturing；system simulation；DOE
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收稿日期：2023-06-21
作者简介：刘贺童（1999－），女，内蒙古呼伦贝尔人，硕士研究生，主要研究方向为生产系统仿真优化，E-mail：lht_studyworking@126.com；马瑞（1983－），男，河南濮阳人，博士，研究员，主要研究方向为激光3D打印，E-mail：259128939@qq.com。
（北京动力机械研究所，北京 100074）
摘要：为解决某航空发动机核心零部件增材制造产线预设方案的验证优化问题，利用Factory Simulation生产系统仿真软件，对车间布局和AGV物流路线进行二维化模型构建，输入物流调度数据，通过设计DOE试验，以最小化产量完成时间为目标，得到瓶颈工序为钳工、超声波清洗、X光工位，在仿真环境下得到当前预设条件下的AGV利用情况。分析瓶颈工位，对比后得到最优加工站个数，并以车间内正常工作时的AGV平均响应时长为依据讨论最优AGV台数。优化后完成产线年产量目标的时间缩短了12%，车间内投入的物流设备成本降低了20%。优化结果在现有车间预设方案的基础上为有效提高预设车间的生产效率、减少车间成本提出了改进建议。
关键词：智能制造；系统仿真；DOE
中图分类号：TH166 文献标志码：A doi：10.3969/j.issn.1006-0316.2024.04.002
文章编号：1006-0316 (2024) 04-0007-09
Optimization of Intelligent Production Line for Additive Manufacturing Based on Factory Simulation
LIU Hetong，MA Rui
( Beijing Power Machinery Research Institute, Beijing 100074, China )
Abstract：To address the verification and optimization of the preset program for the additive manufacturing production line of a certain aero engine's core components, Factory Simulation production system simulation software was used to construct a 2D model of workshop layout and AGV logistics route. Logistics scheduling data was input and the DOE method was used to minimize the completion time of production volume. The bottleneck processes were identified as fitter, ultrasonic cleaning and X-ray workstations. The AGVs utilization under the current preset conditions was obtained in the simulation environment. After analyzing the bottleneck workstations, the optimal number of processing stations was obtained through comparison. The optimal number of AGVs was discussed based on the average response time of AGVs during normal operation in the workshop. After optimization, the time to achieve the annual production target of the assembly line was reduced by 12%, and the logistics equipment cost in the workshop was reduced by 20%. The optimization results provide effective suggestions for improving the production efficiency and reducing the cost of the preset workshop.
Key words：smart manufacturing；system simulation；DOE
———————————————
收稿日期：2023-06-21
作者简介：刘贺童（1999－），女，内蒙古呼伦贝尔人，硕士研究生，主要研究方向为生产系统仿真优化，E-mail：lht_studyworking@126.com；马瑞（1983－），男，河南濮阳人，博士，研究员，主要研究方向为激光3D打印，E-mail：259128939@qq.com。
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