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Online modeling and monitoring of power consumption, aerosol emissions, and surface roughness in wire cut electric discharge machining of Ti-6Al-4 V

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Abstract

Estimation of energy consumption in machining plays an irreplaceable role in monitoring and improving energy efficiency with reduced emission and surface roughness. This paper proposed a novel data-based grey online modeling and monitoring system for the power consumption, aerosol emissions, and surface roughness in wire cut electrical discharge machining of Ti-6Al-4 V using the grey theory GM(1,N). The proposed methodology needs a very less number of data samples for modeling and monitoring with no training time. Amplitude of wire vibration in X- and Y-directions and absolute difference of wire amplitude in data series are inputs for the grey online modeling and monitoring system. The root mean square error for different parameter settings is estimated and identified as an optimum combination of parameters. The combination of amplitude of wire vibration in X-direction and absolute difference of wire amplitude in X- and Y-directions is significant in estimation of power consumption (root mean square error is 0.81) as well as aerosol emissions (root mean square error is 0.75), and the combination of amplitude of wire vibration in Y-direction and absolute difference of wire amplitude in X- and Y-directions is significant in estimation of surface roughness (root mean square error is 0.41). An artificial neural network is also developed and trained with a feedforward backpropagation algorithm that predicted the power consumption, emissions, and surface roughness. A comparison between the grey online modeling and monitoring system and the system developed by the neural network found that grey online modeling and monitoring showed better performance with less training models.

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The authors confirm that the data supporting the findings of this study are available within the article.

Abbreviations

AGO:

Accumulated generating operation

ANN:

Artificial neural network

EDM:

Electrical discharge machining

GOMM:

Grey online modeling and monitoring

MRR:

Material removal rate

WEDM:

Wire electrical discharge machining

A E :

Aerosol emissions

A X :

Amplitude of cutter vibration in X-direction

A Y :

Amplitude of cutter vibration in Y-direction

CR:

Cutting rate

F X :

Frequency of wire vibration in X-direction

F Y :

Frequency of wire vibration in Y-direction

I :

Current

KW:

Kerf width

M E :

Mass of aerosol

P :

Power consumption

Ra :

Surface roughness

RMSE:

Root mean square error

T ON :

Pulse-on time

WC-I:

Working condition I

WC-II:

Working condition II

WC-III:

Working condition III

WT:

Wire tension

\({X}_{i}^{(0)}\) :

0Th-order sequences of variables

\({X}_{i}^{(1)}\) :

1St-order sequences of variables

\({Z}_{j}^{1}\) :

Mean sequence

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Funding

This work was supported by FIST-DST (Sanction No. SR/FST/ETI-361/2014).

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Authors and Affiliations

  1. Department of Mechanical Engineering, Vignan’s Foundation for Science, Technology and Research, Vadlamudi, India, 522213

    Kaki Venkata Rao

  2. Department of Mining, College of Engineering and Technology, Bule Hora University, 144, Oromia, Ethiopia

    Yekula Prasanna Kumar

  3. Department of Mechanical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, Uttar Pradesh, India, 273010

    Vijay Kumar Singh

  4. Department of Mechanical Engineering, GITAM Institute of Technology, Visakhapatnam, India, 530045

    Balla Srinivasa Prasad

Authors
  1. Kaki Venkata Rao
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  2. Yekula Prasanna Kumar
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  3. Vijay Kumar Singh
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  4. Balla Srinivasa Prasad
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Contributions

Dr. K. Venkata Rao and Dr. B. S. Prasad have designed the experimental plan and carried out the experimentation. They also involved in the application of OGM(1,3) for prediction of responses. Dr. Y. Prasanna Kumar and Dr. V. K. Singh have proposed the methodology and prepared the manuscript.

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Correspondence to Yekula Prasanna Kumar.

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Rao, K.V., Kumar, Y.P., Singh, V.K. et al. Online modeling and monitoring of power consumption, aerosol emissions, and surface roughness in wire cut electric discharge machining of Ti-6Al-4 V. Int J Adv Manuf Technol 119, 3205–3222 (2022). https://doi.org/10.1007/s00170-021-08297-4

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  • DOI: https://doi.org/10.1007/s00170-021-08297-4

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