Journal of Textile Research ›› 2020, Vol. 41 ›› Issue (03): 84-90.doi: 10.13475/j.fzxb.20190601907

• Dyeing and Finishing & Chemicals • Previous Articles     Next Articles

Layout optimization of dip dyeing workshop based on system layout planning-genetic algorithm

HUANG Qi1, ZHOU Qihong1(), ZHANG Qian2, WANG Shaozong2, FAN Wei3, SUN Huifeng3   

  1. 1. College of Mechanical Engineering, Donghua University, Shanghai 201620, China
    2. Beijing National Innovation Institute of Lightweight Ltd., Beijing 100083, China
    3. Taian Companion Machinery Co., Ltd., Taian, Shandong 271000, China
  • Received:2019-06-08 Revised:2019-11-27 Online:2020-03-15 Published:2020-03-27
  • Contact: ZHOU Qihong E-mail:zhouqihong@dhu.edu.cn

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Abstract:

Unreasonable workshop layout and low automation level are primary factors affecting the efficiency of dip dyeing yarns, leading to increased material handling, shipping back of transportation routes, and inefficient production. In this study, a new automatic dyeing process was developed on the basis of the analysis of traditional dyeing process and logistics intensity. A new method based on improved genetic algorithm (GA) and system layout planning (SLP) was presented to solve the layout of dip dyeing workshop with the intensity of logistics and workshop area for establishing the objective function. The layout simulation was carried out using a plant simulation platform, which performed the dynamic planning and calculation of logistics intensity of the production line layout. Simulation results show that SLP-GA rapidly converged and is more effective than SLP. However, SLP-GA is approximately 10% lower than SLP on average in terms of logistics intensity. By implementing a dyeing and finishing enterprise under the constraints of process, this study provides a reasonable layout plan for developing intelligent dyeing and finishing demonstration production line that can achieve the lowest logistics cost and the smallest floor area.

Key words: dip dyeing, workshop layout, system layout planning, genetic algorithm

CLC Number: 

  • TH181

Fig.1

Parametric, decision variable and reference line diagram"

Tab.1

Full process automation production process"

作业区域 工艺 实现功能 作业设备
前络区 前络 原料纱进行络筒 络纱机
输送A 输送络筒后的纱筒 上筒机器人、传送系统
装笼区 集筒 将多个纱筒整理成串纱 下筒机器人
装笼 将整理后的串纱装入纱笼 装纱机器人
调湿缓存区 调湿 进筒纱进行调湿 调湿机
解/扣锁扣 对纱笼进行染前加锁,染后解锁 锁扣机器人
染色区 吊运 将纱笼吊运至染色机 天车
配剂 进行染色剂、助剂的称量 染化料系统
染色 对纱笼筒纱进行染色 染色机
脱水区 装脱机 将染后的纱筒装载至脱水机中 装筒机器人
脱水 筒纱进行脱水 脱水机
分装 脱水后将纱笼中筒纱分装至托盘 分盘装载机器人
烘干区 烘干 烘干机进行烘干 烘干机
卸载 卸载烘干后的纱筒 卸载机器人
后络区 输送B 输送烘干后的纱筒 上筒机器人、传送系统
后络 对染后筒纱进行络筒 络纱机

Fig.2

Logistics status diagram of operating units in dyeing workshop"

Fig.3

Flow chart of improved SLP layout for dyeing workshop"

Fig.4

SLP and GA combination method flow"

Tab.2

Area of each functional area"

编码序号 布置区域 主要设备 设备数量 必要面积/m2
1 前络区 输送系统 2 20×37.5
2 装笼区 装载机器人 2 22.5×15
3 调湿缓存区 锁扣机器人 3 37.5×15
4 染色区 染色机 16 40×37.5
5 脱水区 脱水机 8 60×22.5
6 烘干区 烘干机 6 35×15
7 后络区 卸载机器人 2 25×15
M0 总面积 — — 60×90

Fig.5

Algorithmic implementation interface"

Fig.6

Fitness convergence performance"

Tab.3

Comparative analysis of SLP-GA and SLP"

布局方法 序号 布局序列 物流强度 适应度
SLP-GA 1 7,6,5,2,3,1,4 94 500 378 090
2 6,7,5,4,3,2,1 105 000 419 690
3 7,6,5,3,4,1,2 105 000 420 090
SLP 4 7,6,1,2,4,3,5 104 900 419 620
5 3,4,2,1,5,6,7 106 500 426 090
6 2,1,3,4,7,6,5 106 500 426 090

Fig.7

Workshop layout plan"

Fig.8

Actual layout of workshop. (a) Pre-spinning area, loading area and humidifying area; (b) Dyeing area; (c) Dewatering area; (d) Drying area and back spinning area"

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