Post-processing parameter optimization to enhance the surface finish of HVOF-developed coatings

Srinath, M.K.; Nagendra, J.

doi:10.1007/s41939-022-00116-x

Cited by 4 publications

(2 citation statements)

References 24 publications

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“…Laser welding parameters were optimized to achieve suitable hardness and length of HAZ by employing the Taguchi methodology [7]. The Taguchi technique was paired with the Single-Response Performance Index (SPI) to optimize the post-processing parameters for obtaining minimum surface roughness of the coated items [8]. The turning experiments of pure iron metal utilized the central composite design (CCD) method.…”

Section: Introductionmentioning

confidence: 99%

“…RSM was used to visualize the findings, and the ANOVA approach was used to ensure that the model was appropriate [17]. When the number of contributing process parameters are large (6)(7)(8)(9)(10)(11)(12)(13)(14)(15), it is required to adopt a screening method for selecting significant factors for modeling and optimizing purpose. Placket-Burman design (PBD) is a popular screening approach that logically identifies the significant variables having an extreme influence on the outcome after studying the main effects of contributing factors [18].…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Process Variables for Prediction of Penetration Depth of HSLA Steel Welds Using Response Surface Methodology

Pathak

Kumar

Singh

et al. 2022

KEM

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The statistical model is created for predicting penetration depth in an alternating current-based additional axial magnetic field controlled shielded metal arc welding of ASTM A 516 Gr.70 steel. The design for the trials is developed using the Placket-Burman design and response surface methodology. The created model determines the optimum process variables for getting excellent penetration depth. The input variables (current, magnetic field density, and magnetic frequency) are chosen for a response like penetration depth. This model can predict the main effects and the interacting effects of three process variables. The findings reveal that a higher current value with a low magnetic field density leads to deeper penetration and vice versa. Furthermore, a greater penetration depth is achieved at lower magnetic field density and higher magnetic frequency. With a desirability of 98.8%, the optimum process variables are 110 A, 0 mT, and 60 Hz. The predicted response values produced from the regression equation based upon process variables are extremely similar to the observed output, demonstrating the usefulness of second-order regression equations. For improved joint efficiency, a high level of penetration is needed.

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Section: Introductionmentioning

confidence: 99%