Education, Science, Technology, Innovation and Life
Open Access
Sign In
  1. Home
  2. Journals
  3. Advances in Computer, Signals and Systems
  4. Vol 7, Issue 6, 2023

Design of Data Acquisition System for Clothing Production Line

Download as PDF

DOI: 10.23977/acss.2023.070613 | Downloads: 9 | Views: 370

Author(s)

Junlian He 1, Kaisheng Zhang 2

Affiliation(s)

1 School of Clothing Technology, Shaanxi Fashion Engineering University, Xi'an, Shaanxi, China
2 Intellectual Property Information Service Center, Shaanxi Fashion Engineering University, Xi'an, Shaanxi, China

Corresponding Author

Kaisheng Zhang

ABSTRACT

To solve the problems of production information diversification and slow transmission of production data, a data acquisition system for clothing production line is designed. Firstly, by analyzing the clothing production process, an overall structure consisting of electronic tag, RFID reader, ZigBee routing node, coordination gateway node and upper computer database is constructed; secondly, hardware circuit design and software function program design are focused on RFID module, ZigBee module, human-machine interaction module and the memorizer in the RFID reader; and finally, according to system requirements from the electronic tags data acquisition system, the whole system is tested from two aspects: electronic tags data acquisition and information transmission. The experiment vertified that the system can feed back the processing information of the clothing production line into database of the supreme machine in real time, which enhances the enterprise information management ability to a certain extent and improves the clothing production efficiency.

KEYWORDS

Clothing production process, RFID, ZigBee, informatization, production efficiency

CITE THIS PAPER

Junlian He, Kaisheng Zhang, Design of Data Acquisition System for Clothing Production Line. Advances in Computer, Signals and Systems (2023) Vol. 7: 102-109. DOI: http://dx.doi.org/10.23977/acss.2023.070613.

REFERENCES

[1] Ge Qingqing. The Clothing Customization Pattern under the Experience Economy. Chemical Fiber and Textile Technology, 2022, 51(6):92-94. DOI:10. 3969/j. issn. 1672-500X. 2022. 06. 030. 
[2] Lasi H, Fettke P, Kemper H, et al. Industry 4. 0. Business & Information Systems Engineering, 2014, 6(4):239-242. 
[3] Serpanos D, Wolf M. Industrial Internet of Things. Switzerland: Springer, Cham, 2018: 37-54. 
[4] Feng Yujing and Zhai Liangliang. Industrial Policy, Innovation and Manufacturing Firms Servitization: Empirical Study on Quasi-natural Experiment of Made in CHina 2025. Science and Technology Progress and Policy, 2022, 39(13): 114-123. DOI: 10. 6049/kjbydc. 2021060257. 
[5] Foidl H, Felderer M. Research challenges of industry 4. 0 for qualitymanagement //International conference on enterprise resource planning systems. Munich, Germany: Springer, Cham, 2015: 121-137. 
[6] Wang B, Tao F, Fang X, et al. Smart Manufacturing and Intelligent Manufacturing: A Comparative Review. Engineering, 2021, 7(6):738-757. 
[7] Zhou J, Li P, Zhou Y, et al. Toward New-Generation Intelligent Manufacturing. Engineering, 2018, 4(1):11-20. 
[8] Zhuang Meiling. A novel apparel surface flattening algorithm. International Journal of Clothing Science and Technology, 2013, 25(4):300-316. 
[9] Chen Sha, Xiu Yi and Li Xuefei. Balance Optimization of Clothing Mass Customization Production Line Based on Genetic Algorithm. Journal of Textile Research, 2022,43(12):144-150,159.DOI:10.13475/ j.fzxb.20211100208. 
[10] Aric Bartle, Alla Sheffer, Kim Vladimir G, et al. Physics-driven pattern adjustment for direct 3D garment editing. ACM Transactions on Graphics, 2016, 35(4):50. 
[11] Li Jituo, Zhang Dongliang, Lu Guodong, et al. Flattening triangulated surfaces using a mass-spring model. The International Journal of Advanced Manufacturing Technology, 2005, 25 (1/ 2): 108 - 117. 
[12] Li Zhe and Liu Tianyu. Strategic Design of Clothing Flexible Platform Based on Mass Customization. Wool Textile Journal, 2022, 50(4):112-118. DOI:10. 19333/j. mfkj. 20210703708. 
[13] Batty M. Digital twins. Environment and Planning B: Urban Analytics and City Science, 2018, 45(5):817-820. 
[14] Chen Sha, Xiu Yi, Zhang Haibo. Research on Optimization of Order Scheduling for Apparel Mass Customization Manufacturing Enterprises. Journal of Beijing Institute of Fashion Technology (Natural Science Edition), 2022, 42(1): 65-73. DOI:10. 3969/j. issn. 1001-0564. 2022. 01. 010.

Subscription
E-Mail Alert
Most popular papers
Call for Special Issue
Publication Ethics & OA Statement
Plagiarism Policy
Contact Us
Downloads: 15649
Visits: 269920

Sponsors, Associates, and Links

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.