Investigation of Abrasive Aqua Jet Hole Making (AAJHM) parameters using desirability analysis on Inconel-625 space alloy

Vijayakumar, R.; Srirangarajalu, N.; Santhanakumar, M.; Paul, N.E. Edwin; Rajesh, M.

doi:10.1016/j.jmapro.2023.03.008

Cited by 11 publications

(5 citation statements)

References 17 publications

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“…The optimal parameters obtained were P water = 300 MPa, T SP = 75 mm/min, G d = 2.4 mm , and AM FR = 0.55 kg/min to minimise R a and K θ and maximise MRR. Vijayakumar et al [ 130 ] determined the optimal parameter values, using a desirability analysis, to generate quality holes on INCONEL ® 625 by optimising abrasive water jet drilling (AWJD). P water , G d , T SP and AM FR of garnet and SiC were identified as potential process variables.…”

Section: Literature Reviewmentioning

confidence: 99%

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An In-Depth Exploration of Unconventional Machining Techniques for INCONEL® Alloys

Pedroso,

Sebbe,

Silva

et al. 2024

Materials

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Build-up-edge (BUE), high-temperature machining and tool wear (TW) are some of the problems associated with difficult-to-machine materials for high-temperature applications, contributing significantly to high-cost manufacturing and poor tool life (TL) management. A detailed review of non-traditional machining processes that ease the machinability of INCONEL®, decrease manufacturing costs and suppress assembly complications is thus of paramount significance. Progress taken within the field of INCONEL® non-conventional processes from 2016 to 2023, the most recent solutions found in the industry, and the prospects from researchers have been analysed and presented. In ensuing research, it was quickly noticeable that some techniques are yet to be intensely exploited. Non-conventional INCONEL® machining processes have characteristics that can effectively increase the mechanical properties of the produced components without tool-workpiece contact, posing significant advantages over traditional manufacturing.

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Section: Literature Reviewmentioning

confidence: 99%

“… Desirability condition P water = 300 MPa, G d = 1 mm, T SP = 72 mm/min, and abrasive material is constituted by 100% SiC. ( a ) Scanning electron microscopy (SEM) image, ( b ) 3D surface image, ( c ) 2D roughness profile image [ 130 ]. …”

Section: Figurementioning

confidence: 99%

An In-Depth Exploration of Unconventional Machining Techniques for INCONEL® Alloys

Pedroso,

Sebbe,

Silva

et al. 2024

Materials

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“…For offline quality control, research factors and their impacts on quality characteristics were critical, and an appropriate combination of factors was required to achieve improved cut surface characteristics [6,7]. SZ characteristics in the PGI method (zone length and SA) directly impact surface texture; hence, lowering the SZ and its angle was critical for producing a superior cut surface [8,9]. It is possible to think of the AWJC technique as a multiple-input procedure that necessitates the simultaneous optimization of several answers [10,11].…”

Section: Introductionmentioning

confidence: 99%

A Characterization Study of the ZE41 Magnesium Alloy Using Abrasive Waterjet Cutting

Padmaraja,

Sasi,

Shanmugasundaram

et al. 2024

The International Conference on Processing and Performance of Materials (ICPPM 2023)

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“…Among the nickel-based alloys, Inconel 625 is a superalloy widely used in the aerospace sector and especially the engines and turbines [6], [7]. This material is strengthened through solid solution hardening that enables the achievement of high mechanical properties.…”

Section: Introductionmentioning

confidence: 99%

Using artificial neural networks to model single bead geometries processed by laser-wire direct energy deposition

Asadi,

Queguineur,

Ylä-Autio

et al. 2023

IOP Conf. Ser.: Mater. Sci. Eng.

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Wire-feed laser additive manufacturing processes have gained researchers’ attention because of their potential to reduce material waste, guarantee accuracy, increase material quality and density, and produce a wide dimensional range of final products. Nevertheless, printing materials with desired geometrical properties of the beads is still challenging in such processes. This might be attributed to the need for more sufficient experimental data and precise modeling approaches. In this study, an architecture based on Artificial Neural Networks (ANNs) is developed to model the bead geometries (width, height, and area), considering the wire feed rate, laser power, and travel speed as process parameters. A design-of-experiment based on full factorial design is considered for processing single beads with a Fraunhofer coaxial wire-feed laser system. Inconel 625 wire with a diameter of 1.14 mm and stainless steel substrate are utilized as the experimental materials. Geometrical data is obtained using a laser scanner model RA-7525 SE with 0.026mm volumetric accuracy. The beads’ geometrical details are provided as the feeding data for the proposed ANN. For each bead, a length of 10 mm is considered to calculate the average geometrical parameters, which increases the accuracy of the dataset in comparison to the values acquired via a macroscopic picture of the cross-section of each weld bead. A variety of hyperparameters are chosen and compared regarding precision criteria, including Mean Square Error (MSE), to increase the model‘s accuracy. A train-test separation strategy is considered to evaluate the model‘s accuracy on independent data points. The outcome of this research is an ANN-based geometry prediction model that can be utilized to enhance the development of offline path planners and optimize process parameter selection for a precise geometry toward process control.

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Investigation of Abrasive Aqua Jet Hole Making (AAJHM) parameters using desirability analysis on Inconel-625 space alloy

Cited by 11 publications

References 17 publications

An In-Depth Exploration of Unconventional Machining Techniques for INCONEL® Alloys

An In-Depth Exploration of Unconventional Machining Techniques for INCONEL® Alloys

A Characterization Study of the ZE41 Magnesium Alloy Using Abrasive Waterjet Cutting

Using artificial neural networks to model single bead geometries processed by laser-wire direct energy deposition

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