A Smart system in Manufacturing with Mass Personalization (S-MMP) for blueprint and scenario driven by industrial model transformation

Xianyu Zhang () and Xinguo Ming ()
Additional contact information
Xianyu Zhang: Shanghai Jiao Tong University
Xinguo Ming: Shanghai Jiao Tong University

Journal of Intelligent Manufacturing, 2023, vol. 34, issue 4, No 20, 1875-1893

Abstract: Abstract In order to meet the changing needs of customers, the manufacturing model of products is constantly changing from mass manufacturing model to mass customization model, and to mass personalization model, which is the research object of this paper. Using the research method of system engineering, the system model, characteristic, technology, application blueprints, application scenarios, implementation paths of S-MMP from the perspective of top-level planning are studied. The complete system model of S-MMP proposed in this paper is in line with the development trend of today's industry and meets the urgent needs of enterprises, and it can provide theoretical guidance for enterprises in policy upgrading, model transformation, and business process reengineering. The search results of this paper can provide a reference value for companies to implement high-level planning of the smart system in manufacturing with mass personalization.

Keywords: Smart system; Mass personalization; Smart manufacturing; Mass customization; Industrial value chain (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10845-021-01883-z 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:34:y:2023:i:4:d:10.1007_s10845-021-01883-z

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845

DOI: 10.1007/s10845-021-01883-z

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 ().