Process monitoring in submerged abrasive waterjet cutting of Ti6Al4V by vibration signal

ABSTRACT

The submerged AWJ reduces the supersonic cutting noise, reduces the divergence of the jet, and improves the performance characteristics, but affects the visibility of the workpiece. Hence, this work deals with the monitoring of the combined effect of responses, termed as the multi-response performance index (MRPI), by vibration signals. Firstly, the unsubmerged and submerged AWJs are compared, and the submerged condition gave an average improvement of 1.9 mm in depth of cut, 2.1 mm in smooth cutting zone, 1.03 mm in kerf width, and 1.4 µm in roughness. Furthermore, the TOPSIS method is applied to combine the aforementioned responses into MRPI. The wavelet transform (WT) was used to extract information from the vibration signals, and the features selected by principal component analysis were fed as inputs to ANN and ANFIS techniques. In ANN, 20 architectures were compared for the prediction of MRPI, and the architecture 4-8-4-1 gave a minimum mean absolute error (MAE) of 0.065, and ANFIS gave a minimum MAE of 0.03. Overall, the integrated WT-ANFIS efficiently predicted the MRPI. Finally, the most influential parameters affecting the MRPI were found to be the pressure followed by the transverse rate with contributions of 44% and 21%.

KEYWORDS:

• Submerged AWJ
• multi response performance index
• ANFIS
• vibration signals
• Ti6Al4V

Abbreviation

Table

Acknowledgments

The authors thank R.D. Brothers company for allowing us to utilise their facility for experimentation.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethical approval

This manuscript is original and has not been submitted elsewhere. The results are presented clearly without falsification or fabrication.

Consent to participate

This work does not involve participation of any other individual except the authors of the manuscript

Consent to publish

This work does not contain the data of any other individual except the authors of the manuscript. The authors hereby provide their consent to publish this manuscript.

Authors contributions

Author 1: Paramjit Thakur

Experimentation, measurement of responses and data analysis

Author 2: Dadarao Niwrutti Raut

Data analysis and paper writing

Data availability statement

The data generated during analysis are available in the manuscript, and the detailed data will be made available on request to corresponding authors.

Additional information

Funding

The authors have no funding to report.