A perturbation signal based data-driven Gaussian process regression model for in-process part quality prediction in robotic countersinking operations-Reference-Cited by-同舟云学术

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A perturbation signal based data-driven Gaussian process regression model for in-process part quality prediction in robotic countersinking operations

Published:2021-10 Issue: Volume:71 Page:102105
ISSN:0736-5845
Container-title:Robotics and Computer-Integrated Manufacturing
language:en
Short-container-title:Robotics and Computer-Integrated Manufacturing

Author:

Leco Mateo,Kadirkamanathan Visakan

Funder

Engineering and Physical Sciences Research Council

FP7 People: Marie-Curie Actions

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,General Mathematics,Software,Control and Systems Engineering

Reference25 articles.

1. Robotics in industry—their role in intelligent manufacturing;Day;Engineering,2018

2. Advanced monitoring of machining operations;Teti;CIRP Ann. - Manuf. Technol.,2010

3. A review of machining monitoring systems based on artificial intelligence process models;Abellan-Nebot;Int. J. Adv. Manuf. Technol.,2010

4. Tool condition monitoring techniques in milling process-a review;Mohanraj;J. Mater. Res. Technol.,2020

5. In-process tool condition forecasting based on a deep learning method;Sun;Robot. Comput. Integr. Manuf.,2020

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