Optimization of Abrasive Waterjet Cutting by Using the CODAS Method with Regard to Interdependent Processing Parameters

Authors

  • Andrzej Perec Jacob of Paradies University, Faculty of Technology, Poland https://orcid.org/0000-0003-3132-9514
  • Elzbieta Kawecka Jacob of Paradies University, Faculty of Technology, Poland
  • Aleksandra Radomska-Zalas Jacob of Paradies University, Faculty of Technology, Poland https://orcid.org/0000-0002-3548-1807
  • Frank Pude Steinbeis Consulting Center High-Pressure Waterjet Technology, Germany & Inspire AG, ETH Zurich, Switzerland

DOI:

https://doi.org/10.5545/sv-jme.2023.647

Keywords:

abrasive waterjet cutting, process optimization, CODAS method, maximum cutting depth, minimum surface roughness

Abstract

The paper shows performance optimization effects of steel machining by abrasive water jet (AWJ). An innovative combinative distance-based assessment method (CODAS) is implemented for the optimization of cutting parameters like pump pressure, feed rate, and abrasive flow rate over cutting depth, and cut kerf surface roughness. The CODAS algorithm is among those based on measuring the distance between a scenario (in this case processing parameters in terms of performance and quality indicators) - and a certain benchmark. A benchmark is a specific hypothetical set of processing parameters devised or determined from available data. To determine the best set of process control parameters, a CODAS approach was performed with some weighting determinations. To set the initial parameters of the weights, it was proposed to calculate based on entropy weight method (EWM), that measures output value dispersion in cutting process. This technique simplifies multiple compound responses by preserving a single response.

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Published

2023-09-14

How to Cite

Perec, A. ., Kawecka, E., Radomska-Zalas, A., & Pude, F. (2023). Optimization of Abrasive Waterjet Cutting by Using the CODAS Method with Regard to Interdependent Processing Parameters. Strojniški Vestnik - Journal of Mechanical Engineering, 69(9-10), 367–375. https://doi.org/10.5545/sv-jme.2023.647