Abrasive jet drilling of hard alumina flat: an experimental investigation and predictive modeling by ANN

Authors

  • Deb Kumar Adak College of Engineering and Management, Kolaghat, Purba Medinipur, West Bengal, India & Kalyani Government Engineering College, Kalyani, West Bengal, India
  • Prosenjit Dutta Kalyani Government Engineering College, Kalyani, West Bengal, India
  • Barun Haldar College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Kingdom of Saudi Arabia
  • Santanu Das Kalyani Government Engineering College, Kalyani, West Bengal, India
  • Naser Abdulrahman Alsaleh College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Kingdom of Saudi Arabia
  • Sibsankar Dasmahapatra Kalyani Government Engineering College, Kalyani, West Bengal, India

Keywords:

Abrasive Jet Machining (AJM), Alumina, Drilling, ANN, Estimation

Abstract

Abrasive jet machining (AJM) is often applied in drilling of hard and brittle ceramic materials, and is also used for other processes like surface preparation, deburring, shot-peening, polishing, etc. AJM process parameters need be appropriately selected to have optimized responses like MRR, nozzle wear, etc. Experimental investigation is performed in this work by precisely controlling abrasive flow rate. Along with system pressure, abrasive flow rate, stand-off distance (SOD) and grain size are considered during performing AJM with silicon carbide abrasive on commercially pure 4 mm thick alumina tiles using response surface methodology (RSM). Analysis of variance is done to detect the relative significance of each of the variables. Artificial neural network (ANN) is constructed to estimate the response in AJM based on input parameters. Estimation of machining performance is effectively carried out by ANN based on the training data with less than 8% estimation error, particularly for MRR and NWR.

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Published

01-11-2022

How to Cite

Adak, D. K., Dutta, P., Haldar, B., Das, S., Alsaleh, N. A., & Dasmahapatra, S. (2022). Abrasive jet drilling of hard alumina flat: an experimental investigation and predictive modeling by ANN. Manufacturing Technology Today, 21(11-12), 11–24. Retrieved from https://mtt.cmti.res.in/index.php/journal/article/view/72

Issue

Vol. 21 No. 11-12 (2022): November-December 2022

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Articles

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