Optimization of wear process parameters on 16-Cr Ferritic ODS steel through Taguchi approach

Dharmalingam, G.; Mariappan, R.; Prasad, M. Arun

doi:10.1016/j.matpr.2019.05.413

Cited by 4 publications

(4 citation statements)

References 13 publications

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“…The term 'signal' denotes the preferred response, while 'noise' denotes undesirable values resulting from uncontrollable factors. The S/N ratio is shown below (Equation ( 1)) [43,44].…”

Section: Design Of Experiments and Optimization Techniquesmentioning

confidence: 99%

Optimization of Abrasive Water Jet Machining Process Parameters on Onyx Composite Followed by Additive Manufacturing

et al. 2023

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Fiber-reinforced additive manufacturing components have been used in various industrial applications in recent years, including in the production of aerospace, automobile, and biomedical components. Compared to conventional methods, additive manufacturing (AM) methods can be used to obtainin lighter parts with superior mechanical properties with lower setup costs and the ability to design more complex parts. Additionally, the fabrication of onyx composites using the conventional method can result in delamination, which is a significant issue during composite machining. To address these shortcomings, the fabrication of onyx composites via additive manufacturing with the Mark forged 3D-composite printer was considered. Machinability tests were conducted using abrasive water jet machining (AWJM) with various drilling diameters, traverse speeds, and abrasive mass flow rates. These parameters were optimized using Taguchi analysis and then validated using the Genetic algorithm (GA) and the Moth Flame Optimization algorithm (MFO). The surface morphology (Dmax) and the roughness of the drilled holes were determined using a vision measuring machine with 2D software (MITUTOYO v5.0) and a contact-type surface roughness tester. Confirmation testing demonstrated that the predicted values werenearly identical to the experimental standards. During the drilling of an onyx polymer composite, regression models, genetic algorithms and the Moth-Flame Optimization algorithm were used to estimate the response surface of delamination damage and surface roughness.

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“…The term 'signal' denotes the preferred response, while 'noise' denotes undesirable values resulting from uncontrollable factors. The S/N ratio is shown below (Equation ( 1)) [43,44].…”

Section: Design Of Experiments and Optimization Techniquesmentioning

confidence: 99%

Optimization of Abrasive Water Jet Machining Process Parameters on Onyx Composite Followed by Additive Manufacturing

et al. 2023

View full text Add to dashboard Cite

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“…The 'Signal' term indicates the preferred responses, and the 'Noise' term indicates the undesirable values from uncontrollable factors. To compute the smaller is better, the S/N ratio in equation ( 3) is used and given below [15][16][17]. In equation ( 3), 'n' is denoted as replication number, and 'y' is denoted as observed response significance.…”

Section: Taguchi Techniquementioning

confidence: 99%

Optimization of milling speed and time in mechanical alloying of ferritic ODS steel through taguchi technique

Dharmalingam

Murali

Salunkhe

2021

Int. J. Simul. Multidisci. Des. Optim.

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The oxide dispersion strengthened (ODS) ferritic steels are one of the most important in fuel cladding materials for 4th Generation nuclear reactors because of their excellent mechanical properties such as irradiation resistance, swelling resistance, and elevated temperature tensile/compressive strength. Mechanical alloying (MA) is one of the most promising routes for developing nanocrystalline ferritic ODS steel materials. For the production of nanocrystalline ferritic ODS steel powders, the most influencing factor is the milling speed and milling time during the mechanical alloying process. With the improper selection of milling time and speed, the final milled powders become an amorphous structure consisting of high impurity inclusions in the microstructure, and strength was also affected. In order to overcome these drawbacks, the present investigation was taken into account for the selection of appropriate mechanical milling speed and time, which was optimized through Taguchi analysis followed by the MA process. The optimized mechanical milling speed and time of milled powders were characterized through X-Ray Diffraction Analysis (XRD) and Scanning Electron Microscope (SEM).

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“…Further the analogous weights were calculated in a digital balance with accuracy level of 0.1 mg. Standard formula shown in equation 3 was used to calculate the wear rates. [16]…”

Section: B Wear Testmentioning

confidence: 99%

Optimization of Wear Process Parameters on 17-Cr Ferritic ODS Steel

Dharmalingam,

Sellamuthu

2019

IJEAT

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The main aim of this article deals with the wear behavior of mechanically alloyed 17-Cr oxide dispersion strengthened (ODS) Ferritic steel consolidated through Vacuum Hot Pressing (VHP) at temperature level of 1170 °C under pressure level of 60 MPa with 60 minutes as holding time and with rate of cooling of 50 ˚C /min and a vacuum level of 10 -3 torr. The persuade of wear process parameters were investigated based on the load applied, sliding velocity and sliding distance at a temperature of 350°C on dry sliding track of 17-Cr Ferritic oxide dispersion strengthened steel (Fe-17Cr-0.35Y 2 O 3 -1.5ZrO 2 -4Al ( %wt). Wear test was conducted in a dry atmosphere using a pinon-disc wear testing machine. Wear behavior of 17-Cr Ferritic ODS steel was analyzed by using Taguchi approach. To examine the process parameter during high temperature wear rate analysis of variance and signal to noise ratios were used. During the wear analysis sliding distance was found to be influential parameters of wear rate for 17-Cr Ferritic oxide dispersion strengthened steel succeeded by functional load and sliding velocity. The regression model was found to calculate the rate of wear for 17-Cr Ferritic oxide dispersion strengthened steel.

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Optimization of wear process parameters on 16-Cr Ferritic ODS steel through Taguchi approach

Cited by 4 publications

References 13 publications

Optimization of Abrasive Water Jet Machining Process Parameters on Onyx Composite Followed by Additive Manufacturing

Optimization of Abrasive Water Jet Machining Process Parameters on Onyx Composite Followed by Additive Manufacturing

Optimization of milling speed and time in mechanical alloying of ferritic ODS steel through taguchi technique

Optimization of Wear Process Parameters on 17-Cr Ferritic ODS Steel

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