Machine learning approach based on fractal analysis for optimal tool life exploitation in CFRP composite drilling for aeronautical assembly-Reference-Cited by-同舟云学术

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Machine learning approach based on fractal analysis for optimal tool life exploitation in CFRP composite drilling for aeronautical assembly

Published:2018 Issue:1 Volume:67 Page:483-486
ISSN:0007-8506
Container-title:CIRP Annals
language:en
Short-container-title:CIRP Annals

Author:

Caggiano Alessandra^ORCID,Rimpault Xavier^ORCID,Teti Roberto,Balazinski Marek^ORCID,Chatelain Jean-François,Nele Luigi

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Reference12 articles.

1. Monitoring in Precision Metal Drilling Process Using Multi-Sensors and Neural Network;Cruz;International Journal of Advanced Manufacturing Technology,2013

2. High Performance Cutting of Advanced Aerospace Alloys and Composite Materials;M’Saoubi;CIRP Annals—Manufacturing Technology,2015

3. High Performance Cutting of Fibre Reinforced Plastic Composite Materials;Lopresto;Procedia CIRP,2016

4. Cloud-Enabled Prognosis for Manufacturing;Gao;CIRP Annals—Manufacturing Technology,2015

5. Cloud-Based Manufacturing Process Monitoring for Smart Diagnosis Services;Caggiano;International Journal of Computer Integrated Manufacturing,2018

Cited by 45 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Spot-checking machine learning algorithms for tool wear monitoring in automatic drilling operations in CFRP/Ti6Al4V/Al stacks in the aircraft industry;Journal of Manufacturing Systems;2024-12

2. Partition five-axis surface machining of CFRP laminate structures considering fiber orientation;International Journal of Computer Integrated Manufacturing;2024-07-05

3. Digital twin-driven real-time suppression of delamination damage in CFRP drilling;Journal of Intelligent Manufacturing;2024-02-03

4. Improving the useful life of tools using active vibration control through data-driven approaches: A systematic literature review;Engineering Applications of Artificial Intelligence;2024-02

5. Operations research applied to aerospace manufacturing and assembly: a survey;European J. of Industrial Engineering;2024

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