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The International Journal of Advanced Manufacturing Technology
Erschienen in: The International Journal of Advanced Manufacturing Technology 3-4/2021

31.07.2021 | ORIGINAL ARTICLE

Data-driven sustainability evaluation of machining system: a case study

verfasst von: Cuixia Zhang, Cui Wang, Conghu Liu, Guang Zhu, Wenyi Li, Mengdi Gao

Erschienen in: The International Journal of Advanced Manufacturing Technology | Ausgabe 3-4/2021

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Abstract

Improving resource efficiency and reducing waste discharge are the inevitable trends of the development of sustainable machining system. Therefore, a data-driven sustainability evaluation method of machining system is proposed. The input (energy, materials, equipment, R&D, and services) and output (wastes and products) data of machining system are collected. These dimensional data are processed by emergy. The emergy flow calculation model of the machining process is established for data modeling, and the sustainability evaluation index of machining system is constructed for data analysis. Finally, an engine base machining process is taken as a case study for innovative practice, and the targeted process optimization is adopted based on its sustainability evaluation for innovative practice. The feasibility and effectiveness of the method are verified. This study provides theoretical and methodological support for promoting the sustainability of the manufacturing industry.
Vorheriger Artikel Accurate prediction of the extrusion forming bonding reliability for heterogeneous welded sheets based on GA-BP neural network
Nächster Artikel Evaluating the hole quality produced by vibratory drilling: additive manufactured PLA+

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Metadaten
Titel
Data-driven sustainability evaluation of machining system: a case study
verfasst von
Cuixia Zhang
Cui Wang
Conghu Liu
Guang Zhu
Wenyi Li
Mengdi Gao
Publikationsdatum
31.07.2021
Verlag
Springer London
Erschienen in
The International Journal of Advanced Manufacturing Technology / Ausgabe 3-4/2021
Print ISSN: 0268-3768
Elektronische ISSN: 1433-3015
DOI
https://doi.org/10.1007/s00170-021-07779-9

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