Enhancing High-Alloy Steel Cutting with Abrasive Water Injection Jet (AWIJ) Technology: An Approach Using the Response Surface Methodology (RSM).

Autor: Perec A; Faculty of Technology, Jacob of Paradies University, 66-400 Gorzów Wielkopolski, Poland., Kawecka E; Faculty of Technology, Jacob of Paradies University, 66-400 Gorzów Wielkopolski, Poland., Pude F; Inspire AG (ETH Zurich), CH-8005 Zurich, Switzerland.; Steinbeis Consulting Center High-Pressure Waterjet Technology, 86497 Horgau, Germany.
Jazyk: angličtina
Zdroj: Materials (Basel, Switzerland) [Materials (Basel)] 2024 Aug 13; Vol. 17 (16). Date of Electronic Publication: 2024 Aug 13.
DOI: 10.3390/ma17164020
Abstrakt: The common machining technologies for difficult-to-machine materials do not remarkably ensure acceptable efficiency and precision in bulk materials cutting. High-energy abrasive water injection jet (AWIJ) treatment can cut diverse materials, even multi-layer composites characterized by divergent properties, accurately cutting complex profiles and carrying them out in special circumstances, such as underwater locations or explosion hazard areas. This work reports research on the AWIJ machining quality performance of X22CrMoV12-1 high-alloy steel. The response surface method (RSM) was utilized in modeling. The most influencing process control parameters on cut kerf surface roughness-abrasive flow rate, pressure, and traverse speed-were tested. The result is a mathematical model of the process in the form of a three-variable polynomial. The key control parameter affecting the cut slot roughness turned out to be the traverse speed. In contrast, pressure has a less significant effect, and the abrasive mass flow rate has the slightest impact on the cut slot roughness. Under the optimal conditions determined as a result of the tests, the roughness of the intersection surface Sq does not exceed 2.3 μm. Based on the ANOVA, we confirmed that the model fits over 96% appropriately with the research outcomes. This method reduces the computations and sharply determines the optimum set of control parameters.
Databáze: MEDLINE
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