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Self-adjusting on-line cutting condition for high-speed milling process

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Abstract

The paper presents an intelligent control system for self-adjusting on-line cutting condition for high speed machining (self-HSM) with considering the tool-wear amount to keep the machined product’s quality in allowable limit. For realizing the self-HSM, the empirical analysis of variance (ANOVA) and artifical neural network (ANN) are used. The ANOVA is used for generating the empirical functions which are used as the boundary condition as well as constraint evaluation. The ANN is used for generating the new optimal cutting condition. Then, the self-HSM updates this cutting condition on the real machine — HS Super MC500. The new optimal cutting parameter is sent to the controller for updating the new machining condition to keep the machined part’s quality. The integration of the empirical analysis and ANN enables generating the optimal cutting parameters correctly and efficiently for high-speed milling.

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Abbreviations

ACC:

Adaptive control with constraints

ACO:

Adaptive control with optimization

ANN:

Artificial neural networks

ANOVA:

Analysis of variance

CNC:

Computer numerically controlled

DOE:

Design of experiments

GA:

Genetic algorithms

GAC:

Geometric adaptive control

GRA:

Grey relational analysis

HSM:

High speed machining

ICS:

Intelligent control systems

PSO:

Particle swarm optimization

RSM:

Response surface methodology

SA:

Simulated annealing

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Acknowledgments

The research fund is Nafosted (Code: 107.01-2014.23).

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Authors and Affiliations

  1. Faculty of Mechanical Engineering, Hanoi University of Industry, Hanoi, Vietnam

    Tien-Dung Hoang

  2. Faculty of Mechanical Engineering, University of Transport and Communications, Hanoi, Vietnam

    Quang-Vinh Nguyen, Van-Cuong Nguyen & Ngoc-Hien Tran

Authors
  1. Tien-Dung Hoang
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  2. Quang-Vinh Nguyen
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  3. Van-Cuong Nguyen
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  4. Ngoc-Hien Tran
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Corresponding author

Correspondence to Ngoc-Hien Tran.

Additional information

Recommended by Editor Hyung Wook Park

Tien-Dung Hoang received the B.Sc., M.Sc. and Ph.D. from Hanoi University of Science and Technology in 2003, 2007 and 2016, respectively, in Vietnam. He is a Lecturer in Mechanical Engineering, Hanoi University of Industry, Hanoi, Vietnam. His research interests include CAD/CAM/CAE/CNC, optimization and intelligent manufacturing system

Quang-Vinh Nguyen received the B.Sc. and M.Sc. from Hanoi University of Science and Technology, in 2003 and 2008, respectively. He is a Lecturer in Mechanical Engineering, University of Transport and Communi-cations, Hanoi, Vietnam. His research interests include CAD/CAM/CAE, rapid prototyping and manufacturing technology

Van-Cuong Nguyen received the B.Sc. from University of Transport and Communications in 2007 in Vietnam. He received his Ph.D. from Tula State University in Russia in 2013. He is a Lecturer in Mechanical Engineering, University of Transport and Communications, Hanoi, Vietnam. His research interests include CAD/CAM/CAE and manufacturing technology

Ngoc-Hien Tran received the B.Sc. from University of Transport and Communications and M.Sc. in Mechanical Engineering from Hanoi University of Science and Technology, in 2001 and 2007, respectively, in Vietnam. He received his Ph.D. in Mechanical Engineering from Ulsan University in Korea in 2011. Currently, he is an Associate Professor of Mechanical Engineering, University of Transport and Communications, Hanoi, Vietnam. His research interests include CAD/CAM/CAE, intelligent manufacturing system, and additive manufacturing

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Hoang, TD., Nguyen, QV., Nguyen, VC. et al. Self-adjusting on-line cutting condition for high-speed milling process. J Mech Sci Technol 34, 3335–3343 (2020). https://doi.org/10.1007/s12206-020-0726-y

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  • DOI: https://doi.org/10.1007/s12206-020-0726-y

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