|本期目录/Table of Contents|

[1]邵景峰,李 宁,袁玉楼.面向绿色制造的涤纶低弹丝生产关键工艺参数优化[J].丝绸,2020,57(12):121107.
　SHAO Jingfeng,LI Ning,YUAN Yulou.Optimization of key process parameters for polyester drawn textured yarn oriented to green manufacturing[J].Journal of Silk,2020,57(12):121107.
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面向绿色制造的涤纶低弹丝生产关键工艺参数优化(PDF)

《丝绸》[ISSN:1001-7003/CN:33-1122/TS]

卷:
57
期数:
2020年12期
页码:
121107
栏目:
研究与技术
出版日期:
2020-12-20

文章信息/Info

Title:
Optimization of key process parameters for polyester drawn textured yarn oriented to green manufacturing
文章编号:
1001-7003（2020）12-0000-00
作者:
邵景峰; 李 宁; 袁玉楼
1.西安工程大学 管理学院,西安 710048;2.咸阳纺织集团有限公司,陕西 咸阳 712000
Author(s):
SHAO Jingfeng1;  LI Ning 1;  YUAN Yulou 2
1. School of Management , Xi’an Polytechnic University , Xian 710048 , China; 2. Xianyang Textile Group Co ., Ltd ., Xianyang 712000, China
关键词:
工艺参数优化; 涤纶低弹丝; 绿色制造; 碳排放核算; 纺织生产
Keywords:
process parameter optimization;  polyester low elastic yarn;  green manufacturing;  carbon emission accounting;  textile production
分类号:
TS102.522；
doi:
-
文献标志码:
A
摘要:
为了实现涤纶低弹丝生产过程绿色低碳制造，文章以加弹工艺为研究对象，提取关键工艺参数并考虑实际约束条件，构建以涤纶低弹丝韧度最大、碳排放最小及能量效率最高为综合目标的多目标优化模型。采用信噪比与改进综合赋权的灰色关联分析相结合的方法，将模型优化从多目标向单目标转化；通过Box-Behnken Design试验设计获取试验数据，基于响应曲面法建立灰色关联度与关键工艺参数之间的二阶响应模型，进而应用遗传算法对优化模型进行求解。最后，通过算例验证与分析，结果表明该模型更为合理地优化了涤纶低弹丝生产过程中的关键工艺参数，在保证纤维质量的同时使碳排放量较传统工艺条件下降低了3.81%，提高了能源利用效率。
Abstract:
In order to realize green and low carbon manufacturing of polyester drawn textured yarn (P-DTY) , the texturing process was selected as the research object, and the key process parameters were extracted . Besides, the actual constraints were considered to establish a multi-objective optimization model with the maximum toughness, the minimum carbon emission and the maximum energy efficiency of P-DTY as the comprehensive objective . The model optimization was transformed from multi-objective to single objective by combining signal-to-noise ratio and grey correlation analysis with improved comprehensive weighting . Then, Box-Behnken Design was used to obtain test data, and a second-order response model between the gray correlation degree and key process parameters was established based on the response surface method. Further, genetic algorithm was applied to solve the optimization model. Finally, the results of example verification and analysis show that the model is more reasonable, because it optimize d the key process parameters in the production process of P-DTY, which can reduce the carbon emission by 3.81% and improve energy use efficiency under the precondition of ensuring fiber quality, compared with the traditional process

参考文献/References:

[1]向峰, 黄圆圆 , 张智, 等. 基于数字孪生的产品生命周期绿色制造新模式[J]. 计算机集成制造系统, 2019, 25(6): 1505-1514.
XIANG Feng, HUANG Yuanyuan, ZHANG Zhi, et al. New paradigm of green manufacturing for product life cycle based on digital twin[J]. Computer Integrated Manufacturing Systems, 2019, 25(6): 1505-1514.
[2]中华人民共和国工业和信息化部. 纺织工业“十三五”发展规划[J]. 纺织科技进展, 2016(10): 2-4.
Ministry of Industry and Information Technology of the People’s Republic of China. The 13th five years plan for the development of textile industry[J]. Progress in Textile Science & Technology, 2016(10): 2-4.
[3] DEIF A M. A system model for green manufacturing[J]. Journal of Cleaner Production, 2011, 19(14): 1553-1559.
[4] AHN S H, CHUN D M, CHU W S. Perspective to green manufacturing and applications [J]. International Journal of Preclsion Engineering and Manufacturing, 2013, 14(6): 873-874.
[5] DORNFELD D A. Moving towards green and sustainable manufacturing[J]. International Journal of Preclsion Engineering and Manufacturing-Green Technology, 2014, 1 (1): 63 -66.
[6] ALAY E, DURAN K, KORLU A . A sample work on green manufacturing in textile industry[J] . Sustainable Chemistry and Pharmacy, 2016 , 3: 39-46．
[7] SINGH A, PHILIP D, RAMKUMAR J, et al. A simulation based approach to realize green factory from unit green manufacturing processes[J]. Journal of Cleaner Production, 2018, 182: 67-81.
[8] ZHANG X, MING X, LIU Z, et al. General reference model and overall frameworks for green manufacturing[J]. Journal of Cleaner Production, 2019, 237: 117757.
[9] JAGADISH, BHOWMIK S, RAY A. Development of fuzzy logic-based decision support system formulti-response parameter optimization of green manufacturing process: a case study[J]. Soft Computing, 2019, 23(21): 11015 -11034.
[10]文笑雨, 孙海强 , 魏新龙 , 等. 绿色制造模式下多目标柔性工艺规划问题研究[J]. 机械设计与制造, 2019(5): 222-227.
WEN Xiaoyu, SUN Haiqiang, WEI Xinlong, et al. Research on multi-objective flexible process planning under green manufacturing mode[J]. Machinery Design & Manufacture, 2019(5): 222-227.
[11]潘建新. 基于绿色制造的加工参数优化研究[J]. 机电工程, 2019, 36(7): 669-674.
PAN Jianxin. Optimal selection of machining parameters based on green manufacturing[J]. Journal of Mechanical & Electrical Engineering, 2019, 36(7): 669-674.
[12]郭桥生, 吴梦芳 , 裴付宇. 新型节能聚酯纤维DTY生产工艺研究[J]. 丝绸, 2015, 52(9): 11-15.
GUO Qiaosheng, WU Mengfang, PEI Fuyu. Research on production process of new energy-saving polyester DTY[J]. Journal of Silk, 2015, 52(9): 11-15.
[13]吴金亮, 卢庆丰 , 丁国军 , 等. 83 dtex/36 f 轻网高弹涤纶DTY生产工艺[J]. 丝绸, 2016, 53(6): 11-14.
WU Jinliang, LU Qingfeng, DING Guojun, et al. Production process of 83 dtex /36 f high elasticity PET DTY[J]. Journal of Silk, 2016, 53(6): 11-14.
[14]魏艳红, 刘新金 , 胡晗 , 等. XLA与LYCRA两种包芯纱的工艺优化及其质量对比分析[J]. 丝绸, 2019, 56(9): 35-42.
WEI Yanhong, LIU Xinjin, HU Han, et al. Process optimization and quality comparison of XLA and LYCRA core-spun yarns[J]. Journal of Silk, 2019, 56(9): 35-42.
[15]张国祥, 吉卫喜 , 王煜. 面向绿色高效制造的数控加工参数优化研究[J]. 机械设计与研究, 2016, 32(5): 123-127.
ZHANG Guoxiang, JI Weixi, WANG Yu. Research of NC machining parameters optimization for green and high efficiency[J]. Machine Design & Research, 2016, 32(5): 123-127.
[16]顾敏明, 戴文战. 涤纶织物热定型降耗优化算法[J]. 纺织学报, 2018, 39(1): 164-168.
GU Minming, DAI Wenzhan. Optimization algorithm for energy saving in heat setting of polyester fabric[J]. Journal of Textile Research, 2018, 39(1): 164-168.
[17]詹欣隆, 张超勇 , 孟磊磊 , 等. 基于改进引力搜索算法的铣削加工参数低碳建模及优化[J]. 中国机械工程,2020(12):1481-1491.
ZHAN Xinlong, ZHANG Chaoyong, MENG Leilei, et al. Solving multi-objective parameter optimization problem of CNC milling by an improved non-dominated sorting gravity search algorithm[J]. China Mechanical Engineering,2020(12):1481-1491.
[18]邵景峰, 马创涛 , 王蕊超 , 等. 基于碳排放核算的涤纶低弹丝生产工艺优化[J]. 纺织学报, 2019, 40(2): 166-172.
SHAO Jingfeng, MA Chuangtao, WANG Ruichao, et al. Polyester drawn textured yarn production process optimization based on carbon emission accounting[J]. Journal of Textile Research, 2019, 40(2): 166-172.
[19]王小林, 裴洪全 , 姚阿大. 变形热箱温度对75 dtex/72 f涤纶DTY物性影响的研究[J]. 聚酯工业, 2017, 30(5): 20-24.
WANG Xiaolin, PEI Hongquan, YAO Ada. Research on the influence of temperature in hot box on physical properties of 75 dtex / 72 f polyester DTY[J]. Polyester Industry, 2017, 30(5): 20-24.
[20]邓朝晖, 符亚辉 , 万林林 , 等. 面向绿色高效制造的铣削工艺参数多目标优化[J]. 中国机械工程, 2017, 28(19): 2365-2372.
DENG Zhaohui, FU Yahui, WANG Linlin, et al. Multi objective optimization of milling process parameters for green high-performance manufacturing[J]. China Mechanical Engineering, 2017, 28(19): 2365-2372.
[21]傅为忠, 陈文静. 基于改进CRITIC-GGI-VIKOR的工业发展绿色度动态评价模型构建及其应用研究[J]. 科技管理研究, 2017, 37(10): 249-257.
FU Weizhong, CHEN Wenjing. Dynamic evaluation model building and application study of industrial development green degree based on improved CRITIC-GGI-VIKOR[J]. Science and Technology Mangament Research, 2017, 37(10): 249-257.
[22]周洁, 张楠. 基于响应面法的碳纤维铺放工艺参数优化及耦合作用分析[J]. 工程塑料应用, 2018, 46(9): 66-71.
ZHOU Jie, ZHANG Nan. Process parameters optimization and coupling effect of carbon fiber placement based on response surface method[J]. Engineering Plastics Application, 2018, 46(9): 66-71.
[23]赵鹏程, 王俊元 , 梅林玉 , 等. 基于响应面法的静电纺丝制备壳聚糖/聚氧化乙烯的工艺参数优化[J]. 丝绸, 2020, 57(2): 31-34.

备注/Memo

备注/Memo:
收稿日期：2020-04-09
修回日期：2020-11-06基金项目：中国纺织之光科技教育基金会应用基础研究项目(J201508)；中国纺织工业联合会指导性计划项目(2016076)；陕西省教育厅服务地方科学研究项目(16JF009)；陕西省重点研发计划项目(2017GY-039)；西安市科技计划项目(2017074CG/RC037(XAGC005))；西安工程大学研究生创新基金项目(chx2020021)
作者简介：邵景峰（1980—），男，教授，博士，主要从事智能信息处理的研究。
更新日期/Last Update: 2020-11-13