Manufacturing task data chain-driven production logistics trajectory analysis and optimization decision making method-Reference-Cited by-同舟云学术

Manufacturing task data chain-driven production logistics trajectory analysis and optimization decision making method

Published:2023-09-04 Issue: Volume: Page:
ISSN:2095-3127
Container-title:Advances in Manufacturing
language:en
Short-container-title:Adv. Manuf.

Author:

Ling Lin,Song Zhe-Ming,Zhang Xi,Cao Peng-Zhou,Wang Xiao-Qiao,Liu Cong-Hu,Liu Ming-Zhou

Funder

the University Discipline (Professional) Top-notch Talent Academic Funding Project of Anhui Province

the General Project of National Natural Science Foundation of Anhui Province

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Polymers and Plastics,Mechanical Engineering,Mechanics of Materials

Link

https://link.springer.com/content/pdf/10.1007/s40436-023-00454-0.pdf

Reference54 articles.

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2. Yue MY, Zhou YD (2013) Progress of theoretical research-oriented multi-species small batch machining process. Appl Mech Mater 364:470–473

3. Li Q, Wei F, Zhou S (2017) Early warning systems for multi-variety and small batch manufacturing based on active learning. J Intell Fuzzy Syst 33(5):2945–2952

4. Liu ZF, Zhang YZ, Zhang CX et al (1884) (2021) Real-time workshop digital twin scheduling platform for discrete manufacturing. J Phys: Conf Ser 1:012006. https://doi.org/10.1088/1742-6596/1884/1/012006

5. Qu T, Lei SP, Wang ZZ et al (2015) IoT-based real-time production logistics synchronization system under smart cloud manufacturing. Int J Adv Manuf Technol 84(1/4):147–164

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