Please wait a minute...
工程设计学报  2023, Vol. 30 Issue (4): 399-408    DOI: 10.3785/j.issn.1006-754X.2023.00.057
【主题栏目】数字孪生 · 智能制造     
基于数字底座的涂装车身缓存区智能设计与调度优化
王柏村1,2(),朱凯凌1,鲍劲松3,王峰2,4,谢海波1,2,杨华勇1,2
1.浙江大学 机械工程学院,浙江 杭州 310058
2.浙江大学 高端装备研究院,浙江 杭州 311106
3.东华大学 机械工程学院,上海 201620
4.无锡雪浪数制科技有限公司,江苏 无锡 214131
Intelligent design and scheduling optimization of painted body storage based on digital pedestal system
Baicun WANG1,2(),Kailing ZHU1,Jinsong BAO3,Feng WANG2,4,Haibo XIE1,2,Huayong YANG1,2
1.School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China
2.Institute of Advanced Machines, Zhejiang University, Hangzhou 311106, China
3.College of Mechanical Engineering, Donghua University, Shanghai 201620, China
4.Wuxi Xuelang Industrial Intelligence Technology Co. , Ltd. , Wuxi 214131, China
 全文: PDF(4487 KB)   HTML
摘要:

在汽车生产环节进行数字建模、系统仿真与优化对提升汽车的生产质量和效率具有重要意义。为了解决目前汽车制造企业普遍存在的因数据链断裂而导致的资源配置效率低下等难题,以汽车涂装车身缓存区(painted body storage,PBS)为研究对象,提出了一种新型的数字底座平台,来实现数据链整合和多源异构数据融合。同时,设计了一种针对PBS的车身调序策略,考虑了总装工艺对车序优化的约束,采用遗传算法获得了PBS出车序列,然后以逆序数对为参考指标,进行PBS车道排布。将基于数字底座的PBS系统应用于某汽车制造企业,应用效果验证了所提出方法和策略的有效性。研究结果为企业构建内部集成制造平台和设计具体车间单元提供了参考。

关键词: 涂装车身缓存区数字底座系统设计建模仿真调序优化    
Abstract:

Digital modeling, system simulation and optimization in the automotive production process are of great significance for improving the quality and efficiency of automotive production. In order to solve the common problem of low resource allocation efficiency caused by data link breakage in automobile manufacturing enterprises, a new type of digital pedestal system was proposed based on the painted body storage (PBS) of automobile, to achieve data chain integration and multi-source heterogeneous data fusion. At the same time, a vehicle sequencing strategy for PBS was designed, taking into account the constraints of the final assembly process on sequence optimization. The PBS outbound sequence was obtained by a genetic algorithm, and then the inverse ordinal pair was used as a reference index for PBS lane layout. The effectiveness of the proposed method and strategy was verified by applying the PBS system based on digital pedestal system to a certain automotive manufacturing enterprise. The research results provide a reference for enterprises to build internal integrated manufacturing platforms and design specific workshop units.

Key words: painted body storage    digital pedestal system    system design    modeling and simulation    sequencing optimization
收稿日期: 2023-06-15 出版日期: 2023-09-04
CLC:  TP 273  
基金资助: 浙江省重点研发计划资助项目(2021C01018);国家自然科学基金资助项目(52205542)
作者简介: 王柏村(1990—),男,安徽太湖人,研究员,博士,从事智能制造与数字孪生研究,E-mail: baicunw@zju.edu.cn, https://orcid.org/0000-0002-4324-7420|杨华勇(1961—),男,重庆人,教授,中国工程院院士
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
王柏村
朱凯凌
鲍劲松
王峰
谢海波
杨华勇

引用本文:

王柏村,朱凯凌,鲍劲松,王峰,谢海波,杨华勇. 基于数字底座的涂装车身缓存区智能设计与调度优化[J]. 工程设计学报, 2023, 30(4): 399-408.

Baicun WANG,Kailing ZHU,Jinsong BAO,Feng WANG,Haibo XIE,Huayong YANG. Intelligent design and scheduling optimization of painted body storage based on digital pedestal system[J]. Chinese Journal of Engineering Design, 2023, 30(4): 399-408.

链接本文:

https://www.zjujournals.com/gcsjxb/CN/10.3785/j.issn.1006-754X.2023.00.057        https://www.zjujournals.com/gcsjxb/CN/Y2023/V30/I4/399

图1  汽车生产的四大工艺
图2  基于数字底座的PBS系统框架
图3  PBS物理系统框架
图4  PBS内车身入库和出库流程
图5  基于数字底座的PBS优化仿真
图6  面向PBS车身排序的算法框架
图7  车型排序与编码示意
图8  车道排序策略示意
生产参数量值
产量400辆/d
平均生产节拍108 s
PBS静态库容量80辆
PBS进车道数7条
PBS返回车道数1条
表1  某汽车制造企业的生产参数
图9  基于数字底座的PBS系统应用模型
图10  PBS系统应用模型的界面
评价指标指标含义量值
应用前应用后
PBS流转时间/h车辆在PBS的平均流转时间1.261.17
物料准备失败率/%每月因物料准备失败造成的误出库车辆与每月汽车总产量之比0.0250.004
异常状态预警对存在的异常状态进行预警
生产综合效率/%实际产量与计划产量之比86.987.6
表2  PBS系统应用效果
1 雷晓斌,柴雯,马冬妍,等.我国汽车企业与新一代信息技术融合发展现状与趋势研究[J].制造业自动化,2021,43(12):37-42. doi:10.3969/j.issn.1009-0134.2021.12.009
LEI X B, CHAI W, MA D Y, et al. Research on the development status and trend of the integration of Chinese automobile enterprises and new generation of information technology[J]. Manufacturing Automation, 2021, 43(12): 37-42.
doi: 10.3969/j.issn.1009-0134.2021.12.009
2 杨华勇,王峰,王柏村,等.“工业数据+工业机理”驱动的数字底座系统:助推新型工业化[J].新型工业化,2023,13(3):10-15.
YANG H Y, WANG F, WANG B C, et al. Digital pedestal system (DPS) driven by “industrial data plus industrial mechanism” boosts new industrialization[J]. The Journal of New Industrialization, 2023,13(3): 10-15.
3 LI L, LEI B, MAO C. Digital twin in smart manufacturing[J]. Journal of Industrial Information Integration, 2022, 26: 100289.
4 张培,黄智源,陈琨,等.数字化车间多源异构质量数据集成方案研究[J].现代制造工程,2015(1):59-65. doi:10.3969/j.issn.1671-3133.2015.01.012
ZHANG P, HUANG Z Y, CHEN K, et al. Research on multi-source heterogeneous quality data integration in digital shop[J]. Modern Manufacturing Engineering, 2015(1): 59-65.
doi: 10.3969/j.issn.1671-3133.2015.01.012
5 SYAFRUDIN M, ALFIAN G, FITRIYANI N L, et al. Performance analysis of IoT-based sensor, big data processing, and machine learning model for real-time monitoring system in automotive manufacturing[J]. Sensors, 2018, 18(9): 2946-2972
6 夏栋. 总装厂多车型生产线改造及产能提升研究[D].长安:长安大学,2018:1-5.
XIA D. The research on the renovation and productive capacity of the mixing line in the assembly plant[D]. Chang'an: Chang'an University, 2018:1-5.
7 李燚.面向汽车混流生产的多级流水车间排产与调度问题研究[D].重庆:重庆大学,2021:34-39.
LI Y. Research on multi-level flow shop scheduling and dispatching for automobile mixed-flow production[D]. Chongqing: Chongqing University, 2021: 34-39.
8 武文杰.白车身混流焊装线物流仿真和投产序列研究[D].合肥:合肥工业大学,2016:3-4.
WU W J. The BIW mixed welding line logistics simulation and production sequence research[D]. Hefei: Hefei University of Technology, 2016: 3-4.
9 杨一昕,袁兆才,皮智波,等.智能透明汽车工厂的构建与实施[J].中国机械工程,2018,29(23):2867-2874. doi:10.3969/j.issn.1004-132X.2018.23.014
YANG Y X, YUAN Z C, PI Z B, et al. Construction and implementation of intelligent transparent automotive factories[J]. China Mechanical Engineering, 2018, 29(23): 2867-2874.
doi: 10.3969/j.issn.1004-132X.2018.23.014
10 ZHANG X, MING X. An implementation for smart manufacturing information system (SMIS) from an industrial practice survey[J]. Computers & Industrial Engineering, 2021, 151: 106938.
11 JALILVAND-NEJAD A, FATTAHI P. A mathematical model and genetic algorithm to cyclic flexible job shop scheduling problem[J]. Journal of Intelligent Manufacturing, 2015, 26(6): 1085-1098.
12 SHEN Z, TANG Q, HUANG T. Dynamic production scheduling modeling and multi-objective optimization for automobile mixed-model production[J]. Communications in Computer and Information Science, 2018, 924: 25-33.
13 胡婷婷,叶建.基于两阶段匹配度的PBS路由调度策略的研究[J].现代制造技术与装备,2017(5):3. doi:10.3969/j.issn.1673-5587.2017.05.083
HU T T, YE J. Research on PBS routing scheduling strategy based on two stage matching degree[J]. Modern Manufacturing Technology and Equipment, 2017(5): 3.
doi: 10.3969/j.issn.1673-5587.2017.05.083
14 WU J, DING Y, SHI L. Mathematical modeling and heuristic approaches for a multi-stage car sequencing problem[J]. Computers & Industrial Engineering, 2021, 152: 107008.
15 SHEN Z, TANG Q, HUANG T. Dynamic production scheduling modeling and multi-objective optimization for automobile mixed-model production[J]. Communications in Computer and Information Science, 2018, 924: 25-33.
16 王柏村,薛塬,延建林,等.以人为本的智能制造:理念、技术与应用[J].中国工程科学,2020,22(4):139-146. doi:10.15302/j-sscae-2020.04.020
WANG B C, XUE Y, YAN J L, et al. Human-centered intelligent manufacturing: Overview and perspectives[J]. Strategic Study of CAE, 2020, 22(4): 139-146.
doi: 10.15302/j-sscae-2020.04.020
17 陈广阳.汽车生产线缓冲区设计及排序问题研究[D].武汉:华中科技大学,2007:9-12. doi:10.1007/s11596-007-0118-x
CHEN G Y. Research on buffer design and resequence in automobile production line[D]. Wuhan: Huazhong University of Science and Technology, 2007: 9-12.
doi: 10.1007/s11596-007-0118-x
18 马永杰,云文霞.遗传算法研究进展[J].计算机应用研究,2012,29(4):1201-1206,1210. doi:10.3969/j.issn.1001-3695.2012.04.001
MA Y J, YUN W X. Research progress of genetic algorithm[J]. Application Research of Computers, 2012, 29(4): 1201-1206, 1210.
doi: 10.3969/j.issn.1001-3695.2012.04.001
19 丁述勇,张征,丁文洁,等.多巷道式立体车库优化设计与车辆存取策略研究[J].工程设计学报,2021,28(4):443-449. doi:10.3785/j.issn.1006-754X.2021.00.055
DING S Y, ZHANG Z, DING W J, et al. Optimization design of multi-lane stereo garage and research on vehicle access strategy[J]. Chinese Journal of Engineering Design, 2021, 28(4): 443-449.
doi: 10.3785/j.issn.1006-754X.2021.00.055
[1] 钱锦远, 金志江. 含阻系统分析方法及其在先导式截止阀阀芯小孔设计中的应用[J]. 工程设计学报, 2017, 24(5): 496-502,517.
[2] 刁红泉, 胡伟雄, 颜钢锋. 电子提花龙头检测器系统设计[J]. 工程设计学报, 2004, 11(2): 93-95.
[3] 邱林金, 邱清盈, 何斌. 复杂传动系统知识建模及其组织策略研究[J]. 工程设计学报, 2002, 9(5): 251-256.
[4] 蒋雯. 系统设计——产品功能组合的手法[J]. 工程设计学报, 2001, 8(1): 28-30.