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Data-driven smart production line and its common factors
Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China..
Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China..
KTH, School of Industrial Engineering and Management (ITM).ORCID iD: 0000-0001-9694-0483
Univ Hong Kong, Dept Ind & Mfg Syst Engn, Hong Kong, Peoples R China..
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2019 (English)In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 103, no 1-4, p. 1211-1223Article in journal (Refereed) Published
Abstract [en]

Due to the wide usage of digital devices and easy access to the edge items in manufacturing industry, massive industrial data is generated and collected. A data-driven smart production line (SPL), which is a basic cell in a smart factory, is derived primarily. This paper studies the data-driven SPL and its common factors. Firstly, common factors such as integration, data-driven, service collaboration, and proactive service of SPL are investigated. Then, a data-driven method including data self-perception, data understanding, decision-making, and precise control for implementing SPL is proposed. As a reference, the research of the common factors and the data-driven method could offer a systematic standard for both academia and industry. Moreover, in order to validate this method, this paper presents an industrial case by taking an energy consumption forecast and fault diagnosis based on energy consumption data in a prototype of LED epoxy molding compound (EMC) production lines for example.

Place, publisher, year, edition, pages
Springer, 2019. Vol. 103, no 1-4, p. 1211-1223
Keywords [en]
Smart production line (SPL), Common factors, Data-driven, Integration, Energy consumption
National Category
Other Engineering and Technologies
Identifiers
URN: urn:nbn:se:kth:diva-255570DOI: 10.1007/s00170-019-03469-9ISI: 000475921300089Scopus ID: 2-s2.0-85064345033OAI: oai:DiVA.org:kth-255570DiVA, id: diva2:1340151
Note

QC 20190802

Available from: 2019-08-02 Created: 2019-08-02 Last updated: 2019-08-02Bibliographically approved

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Wang, Xi Vincent

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  • apa
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