Journal of Textile Research ›› 2021, Vol. 42 ›› Issue (10): 150-156.doi: 10.13475/j.fzxb.20201103507

• Apparel Engineering • Previous Articles     Next Articles

Optimization of components screening for hanging production line in suit mass customization

XIE Ziang1, DU Jinsong1,2(), YU Yayun1, CHEN Qingting1, FEI Zhonghua3   

  1. 1. College of Fashion and Design, Donghua University, Shanghai 200051, China
    2. Key Laboratory of Clothing Design and Technology, Ministry of Education, Donghua University, Shanghai 200051, China
    3. Zhejiang Semir Garment Co., Ltd., Wenzhou, Zhejiang 362000, China
  • Received:2020-11-16 Revised:2021-05-27 Online:2021-10-15 Published:2021-10-29
  • Contact: DU Jinsong E-mail:ducccp@dhu.edu.cn

RichHTML

14

PDF (PC)

79

Abstract:

In order to solve the asynchronous production of each component of suit customization orders, and reduce the backlogs in screening area before assembly in cellular manufacturing mode of suit mass customization, an order sequencing model was established based on cellular manufacturing line, and the genetic algorithm was designed to optimize the order sequence, reduce the matching operations and to shorten the life cycle of customized orders. Then, simulations were conduct based on the real enterprise data including the 48 suit styles, 200 pieces orders, 4 hanging production lines, 36 workstations and the layout of the workshop. The result shows that the orders completion time of ordinary rule is 26 784 s and the optimization rule is 25 134 s, the efficiency improves 6.2%. The backlogs in store area are further improved by introducing the line scheduling methods: the backlogs is reduced from 18 to 9 pieces, completion time is reduced from 25 134 s to 23 035 s, the average movement of components in store area is reduced form 2.89 to 1.925.

Key words: suit customization, garment mass customization, genetic algorithm, hanging production line

CLC Number: 

  • TS941.62

Fig.1

Organizational structure of suit customized hanging production line"

Tab.1

Process of customized suit components"

工位
编号		 部件加工内容 吊挂生产线 工时/s
1~2 前片加工 前片

吊挂生产线Ⅰ		 253
3~4 嵌袋加工 357
5 贴袋加工 146
6~7 手巾袋/假手巾袋 334/171
8~9 前片胸衬 261
10~11 直型挂面/弯型挂面 里料+挂面

吊挂生产线Ⅱ		 185/305
12~14 手巾袋/嵌袋
手巾袋/贴袋
假手巾袋/嵌袋		 514
180
362
15~16 上挂面(直)/上挂面(弯) 354/298
17~18 前片+挂面 248
19 后开衩 后片+领+袖

吊挂生产线Ⅲ		 128
20 后背中缝 125
21~22 平驳领/戗驳领/
青果领		 250/288
/210
23~26 袖子 648
27~29 摆缝开衩/肩缝
摆缝不开衩/肩缝		 组装

吊挂生产线Ⅳ		 426
495
30~31 组装平驳领/戗驳领/
青果领		 308/308
/201
32~34 组装袖子 622
35-36 钉扣 256

Fig.2

Backlogs of solution based on ordinary rule"

Fig.3

Backlogs of solution based on optimized rule"

Fig.4

Backlogs of solution when introducing hanging line scheduling methods"

[1] 陈洪倩, 陈雁, 丁佳, 等. 服装吊挂线生产组织分析[J]. 丝绸, 2012, 49(1):30-32.
CHEN Hongqian, CHEN Yan, DING Jia, et al. Analysis of garment hanging production line organiza-tion[J]. Journal of Silk, 2012, 49(1):30-32.
[2] LI X, JIANG T, RUIZ R. Heuristics for periodical batch job scheduling in a MapReduce computing frame-work[J]. Information Sciences, 2016, 326:119-33.
doi: 10.1016/j.ins.2015.07.040
[3] 梁艳杰, 杨明顺, 高新勤, 等. 加工与装配车间集成调度的多目标优化模型[J]. 计算机工程与应用, 2016, 52(10):247-253.
LIANG Yanjie, YANG Mingshun, GAO Xinqin, et al. Multi-objective optimizing model for solving mixed modelshop of fabrication and assembly[J]. Computer Engineering and Applications, 2016, 52(10):247-253.
[4] 曾强, 杨育, 王小磊, 等. 并行机作业车间等量分批多目标优化调度[J]. 计算机集成制造系统, 2011, 17(4):816-825.
ZENG Qiang, YANG Yu, WANG Xiaolei, et al. Parallel machine job shop equal batch multi-objective optimization scheduling[J]. Computer Integrated Manufacturing System, 2011, 17(4):816-825.
[5] 谢子昂, 杜劲松, 赵国华. 衬衫吊挂流水线的自适应动态调度[J]. 纺织学报, 2020, 41(10):144-149.
XIE Ziang, DU Jinsong, ZHAO Guohua. Adaptive dynamic scheduling of garment hanging production line[J]. Journal of Textile Research, 2020, 41(10):144-149.
[6] SALMASI N, LOGENDRAN R, SKANDARI M R. Total flow time minimization in a flow shop sequence-dependent group scheduling problem[J]. Computer & Operations Research, 2010, 37(1):199-212.
doi: 10.1016/j.cor.2009.04.013
[7] 黄基诞, 郑斐峰, 徐寅峰, 等. 基于MapReduce模型带任务分割的平行机调度优化[J]. 控制与决策, 2019, 34(7):1514-1520.
HUANG Jidan, ZHENG Feifeng, XU Yinfeng, et al. Parallel machine scheduling optimization with task partition based on MapReduce model[J]. Control and Decision, 2019, 34(7):1514-1520.
[8] SHAH N K, IERAPETRITOU M G. Integrated production planning and scheduling optimization of multi-site, multi-product process industry[J]. Computers & Chemical Engineering, 2012, 37:214-226.
doi: 10.1016/j.compchemeng.2011.08.007
[9] 赵东方, 张晓冬, 周宏丽. 面向并行制造的多生产单元协同调度研究[J]. 中国管理科学, 2020, 28(8):188-195.
ZHAO Dongfang, ZHANG Xiaodong, ZHOU Hongli. Multi-manufacturing cells collaborative scheduling based on parallel manufacturing[J]. Chinese Journal of Management Science, 2020, 28(8):188-195.
[10] 于晓义, 孙树栋, 褚崴. 基于并行协同进化遗传算法的多协作车间计划调度[J]. 计算机集成制造系统, 2008, 14(5):991-1000.
YU Xiaoyi, SUN Shudong, CHU Wei. Parallel collaborative evolutionary genetic algorithm for multi-workshop planning and scheduling problems[J]. Computer Integrated Manufacturing Systems, 2008, 14(5):991-1000.
[1] . Optimization of Components Screening in Suit Mass Customization [J]. , 2021, 42(10): 0-0.
[2] XU Xuemei. Improved genetic algorithm for fabric formulation prediction based on simulated annealing algorithm [J]. Journal of Textile Research, 2021, 42(07): 123-128.
[3] ZHOU Yaqin, WANG Pan, ZHANG Peng, ZHANG Jie. Research on production scheduling method for weft knitting workshops [J]. Journal of Textile Research, 2021, 42(04): 170-176.
[4] ZHANG Zhuo, CONG Honglian, JIANG Gaoming, DONG Zhijia. Polo shirt rapid style recommendation system based on interactive genetic algorithm [J]. Journal of Textile Research, 2021, 42(01): 138-144.
[5] LI Liang, NI Junfang. Automatic generation algorithm for pattern processing codes of quilting machines [J]. Journal of Textile Research, 2020, 41(11): 162-167.
[6] XIE Ziang, DU Jinsong, ZHAO Guohua. Adaptive dynamic scheduling of garment hanging production line [J]. Journal of Textile Research, 2020, 41(10): 144-149.
[7] ZHANG Xiaoxia, LIU Fengkun, MAI Wei, MA Chongqi. Prediction of loom efficiency based on BP neural network and its improved algorithm [J]. Journal of Textile Research, 2020, 41(08): 121-127.
[8] HUANG Zhenzhen, MOK Pikyin, WEN Lihong. Garment production line balance based on genetic algorithm and simulation [J]. Journal of Textile Research, 2020, 41(07): 154-159.
[9] ZHENG Xiaohu, BAO Jinsong, MA Qingwen, ZHOU Heng, ZHANG Liangshan. Spinning workshop collaborative scheduling method based on simulated annealing genetic algorithm [J]. Journal of Textile Research, 2020, 41(06): 36-41.
[10] MO Shuai, FENG Zhanyong, TANG Wenjie, DANG Heyu, ZOU Zhenxing. Performance optimization of elastic spindle pipe based on neural network and genetic algorithm [J]. Journal of Textile Research, 2020, 41(04): 161-166.
[11] HUANG Qi, ZHOU Qihong, ZHANG Qian, WANG Shaozong, FAN Wei, SUN Huifeng. Layout optimization of dip dyeing workshop based on system layout planning-genetic algorithm [J]. Journal of Textile Research, 2020, 41(03): 84-90.
[12] ZHANG Xujing, WANG Lichuan, CHEN Yan. Balancing optimization of garment sewing assembly line based on genetic algorithm [J]. Journal of Textile Research, 2020, 41(02): 125-129.
[13] WANG Xiaohui, LIU Yuegang, MENG Zhuo, SUN Yize. Optimization of process parameters for 3D additive screen printing based on genetic algorithm and neural network [J]. Journal of Textile Research, 2019, 40(11): 168-174.
[14] MENG Shuo, PAN Ruru, GAO Weidong, WANG Jing'an, ZHOU Lijun. Research on weaving scheduling using main objective evolutionary genetic algorithm [J]. Journal of Textile Research, 2019, 40(08): 169-174.
[15] . Optimum and application of automatic cotton blending based on high volume instrument data by improved genetic algorithm [J]. JOURNAL OF TEXTILE RESEARCH, 2016, 37(09): 151-155.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备14006648号
Copyright 2021 © Editorial office of Journal of Textile Research
Supported by Beijing Magtech Co.Ltd