Author Identifier

Jennifer Llanto

ORCID : 0000-0002-5703-7563

Ana Vafadar

ORCID : 0000-0002-7697-6443

Muhammad Aamir

ORCID : 0000-0003-0733-919X

Majid Tolouei Rad

ORCID : 0000-0002-9920-0808

Document Type

Journal Article

Publication Title

Metals

Volume

11

Issue

9

Publisher

MDPI

School

School of Engineering

RAS ID

36907

Funders

Edith Cowan University

Comments

Llanto, J. M., Vafadar, A., Aamir, M., & Tolouei-Rad, M. (2021). Analysis and optimization of process parameters in abrasive waterjet contour cutting of AISI 304L. Metals, 11(9), article 1362. https://doi.org/10.3390/met11091362

Abstract

Abrasive waterjet machining is applied in various industries for contour cutting of heat-sensitive and difficult-to-cut materials like austenitic stainless steel 304L, with the goal of en-suring high surface integrity and efficiency. In alignment with this manufacturing aspiration, experimental analysis and optimization were carried out on abrasive waterjet machining of austenitic stainless steel 304L with the objectives of minimizing surface roughness and maximizing material removal rate. In this machining process, process parameters are critical factors influencing contour cutting performance. Accordingly, Taguchi’s S/N ratio method has been used in this study for the optimization of process parameters. Further in this work, the impacts of input parameters are in-vestigated, including waterjet pressure, abrasive mass flow rate, traverse speed and material thickness on material removal rate and surface roughness. The study reveals that an increasing level of waterjet pressure and abrasive mass flow rate achieved better surface integrity and higher material removal values. The average S/N ratio results indicate an optimum value of waterjet pressure at 300 MPa and abrasive mass flow rate of 500 g/min achieved minimum surface roughness and maximum material removal rate. It was also found that an optimized value of a traverse speed at 90 mm/min generates the lowest surface roughness and 150 mm/min produces the highest rate of material removed. Moreover, analysis of variance in the study showed that material thickness was the most influencing parameter on surface roughness and material removal rate, with a percentage contribution ranging 90.72–97.74% and 65.55–78.17%, respectively.

DOI

10.3390/met11091362

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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Engineering Commons

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