Real-time task processing for spinning cyber-physical production systems based on edge computing
Shiyong Yin,
Jinsong Bao (),
Jie Zhang,
Jie Li,
Junliang Wang and
Xiaodi Huang
Additional contact information
Shiyong Yin: Donghua University
Jinsong Bao: Donghua University
Jie Zhang: Donghua University
Jie Li: Donghua University
Junliang Wang: Donghua University
Xiaodi Huang: Charles Sturt University
Journal of Intelligent Manufacturing, 2020, vol. 31, issue 8, No 16, 2069-2087
Abstract:
Abstract With a high-speed, dynamic and continuous yarn manufacturing process, spinning production suffers from different problems of dynamic disturbances such as yarn breakage, machine breakdown, and yarn quality. Processing real-time tasks is critical for tackling these problems, except for satisfying the requirements of mass production. The existing spinning cyber-physical production systems (CPPS), however, rely on a cloud center for centralized processing of real-time tasks. Thus, it becomes increasingly difficult for them to meet real-time requirements. As such, this paper proposes a novel real-time task processing method for spinning CPPS based on edge computing. First, a new hybrid structure of edge computing nodes (ECN) that consists of both 1-1 and N-1 modes is introduced for different types of tasks in spinning CPPS such as fixed tasks, decision-intensive tasks, and data-intensive tasks. Second, a collaboration mechanism is developed for collaborations between ECNs. The mathematical model and algorithms for real-time task processing are provided for a single ECN. Finally, a case study on a real spinning production is conducted. The results of this case study have demonstrated that the proposed method can significantly reduce the processing time of real-time tasks, as well as improve the production flexibility and production efficiency in spinning CPPS. The proposed method could be applied to continuous and batch manufacturing fields with high real-time requirements, such as weaving, chemical fiber production, and the pharmaceutical industry.
Keywords: Edge computing; Real-time task; Resource allocation; CPPS; Spinning (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://link.springer.com/10.1007/s10845-020-01553-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:joinma:v:31:y:2020:i:8:d:10.1007_s10845-020-01553-6
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845
DOI: 10.1007/s10845-020-01553-6
Access Statistics for this article
Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak
More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().