Optimization of Laser Parameters and Dimple Geometry Using PCA-Coupled GRG

Ganesan, Saravanan Kandasamy; Thanigaivelan, R.

doi:10.5545/sv-jme.2021.7246

Cited by 9 publications

(11 citation statements)

References 12 publications

(14 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…High µ occurred, owing to destruction of these tribo-layers. These findings were in agreement with literature data [22] to [24].…”

Section: Effect Of Load On µ and A Wsupporting

confidence: 94%

“…For multi-objective optimization, GRA has been developed exploiting the Taguchi design to estimate the degree of correlation between test trials (series) via grey relational grade (GRG). To reduce data inconsistency, the data is normalized to a comparable range between 0 and1 [22]. Different objective functions exist, such as larger is better and smaller is better.…”

Section: Abrasive Testmentioning

confidence: 99%

“…Using this method, optimal parameter settings of were found to be an applied load of 60 N, a sliding speed of 1 ms -1 , and a sliding distance of 1000 m. Validation testing showed an improvement of 35.25 % in GRA. Savaran and Thanigaivelan [22] coupled Taguchi-particle component analysis and GRA to optimize the dimple geometry of stainless steel (SS36L). The results indicated that optimum parameter values for the highest GRG peak value of 0.2642 were an average power of 12 W, a pulse duration of 1500 ns, and a frequency of 15 Hz.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multi-Response Optimization of the Tribological Behaviour of PTFE-Based Composites via Taguchi Grey Relational Analysis

Ibrahim¹,

Çamur²,

Savas³

et al. 2022

sv-jme

View full text Add to dashboard Cite

Polymer-based composites find applications in several areas because of their exceptional properties. This article deals with Taguchi grey relational optimization method of abrasive parameters (load (L), grit size (G) and sliding distance (D)) and their influence on abrasive performance of reinforced polytetrafluoroethylene (PTFE) composites. A Taguchi L9 orthogonal array was designed, and nine experimental tests were conducted based on the Taguchi designed experiments. A pin-on-disc tribology machine was used for the experiments. The coefficient of friction (µ) and abrasive specific wear rate (Aw) were recorded for each experiment. An analysis of variance (ANOVA) was performed to establish the significance and percentage contribution of each parameter affecting the abrasive wear performance. Results from the Taguchi-grey-relational method showed that the optimal combination of parameters was achieved at load of 10 N, grit size of 1000 mesh, and sliding distance of 350 m (coded as L3G1D3). ANOVA findings revealed that a grit size with 67.69 % as the most influential on the abrasive performance of polymer-based composites. Validation tests performed using the optimal combination parameter showed an enhancement of 55.22 % in grey relational grade.

show abstract

“…High µ occurred, owing to destruction of these tribo-layers. These findings were in agreement with literature data [22] to [24].…”

Section: Effect Of Load On µ and A Wsupporting

confidence: 94%

Section: Abrasive Testmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multi-Response Optimization of the Tribological Behaviour of PTFE-Based Composites via Taguchi Grey Relational Analysis

Ibrahim¹,

Çamur²,

Savas³

et al. 2022

sv-jme

View full text Add to dashboard Cite

show abstract

“…Many data preprocessing techniques can be utilized in Taguchi-Deng method, depending upon the features of the actual sequence. Generally, series is normalized between 0 and 1 20 . For this study, the target value is “the smaller the better”.…”

Section: Methodsmentioning

confidence: 99%

“…ANOVA showed that speed significantly affect the wear property of the co-continuous composite. Savaran and Thanigaivelan 20 optimized dimple geometry and laser parameter using principal component analysis (PCA) coupled GRA. ANOVA showed that average power contributed most while depth contributed less to performance measures.…”

Section: Introductionmentioning

confidence: 99%

Optimization and prediction of tribological behaviour of filled polytetrafluoroethylene composites using Taguchi Deng and hybrid support vector regression models

Ibrahim

Çamur²,

Savas³

et al. 2022

Sci Rep

View full text Add to dashboard Cite

This study presents optimization and prediction of tribological behaviour of filled polytetrafluoroethylene (PTFE) composites using hybrid Taguchi and support vector regression (SVR) models. To achieve the optimization, Taguchi Deng was employed considering multiple responses and process parameters relevant to the tribological behaviour. Coefficient of friction (µ) and specific wear rate (Ks) were measured using pin-on-disc tribometer. In this study, load, grit size, distance and speed were the process parameters. An L27 orthogonal array was applied for the Taguchi experimental design. A set of optimal parameters were obtained using the Deng approach for multiple responses of µ and KS. Analysis of variance was performed to study the effect of individual parameters on the multiple responses. To predict µ and Ks, SVR was coupled with novel Harris Hawks’ optimization (HHO) and swarm particle optimization (PSO) forming SVR-HHO and SVR-PSO models respectively, were employed. Four model evaluation metrics were used to appraise the prediction accuracy of the models. Validation results revealed enhancement under optimal test conditions. Hybrid SVR models indicated superior prediction accuracy to single SVR model. Furthermore, SVR-HHO outperformed SVR-PSO model. It was found that Taguchi Deng, SVR-PSO and SVR-HHO models led to optimization and prediction with low cost and superior accuracy.

show abstract

Investigation on the effect of laser parameters and hatch patterns on the dimensional accuracy of micro-dimple and micro-channel texture geometries

Rajurkar

Chinchanikar

2023

Int J Interact Des Manuf

View full text Add to dashboard Cite

Optimization of Laser Parameters and Dimple Geometry Using PCA-Coupled GRG

Cited by 9 publications

References 12 publications

Multi-Response Optimization of the Tribological Behaviour of PTFE-Based Composites via Taguchi Grey Relational Analysis

Multi-Response Optimization of the Tribological Behaviour of PTFE-Based Composites via Taguchi Grey Relational Analysis

Optimization and prediction of tribological behaviour of filled polytetrafluoroethylene composites using Taguchi Deng and hybrid support vector regression models

Investigation on the effect of laser parameters and hatch patterns on the dimensional accuracy of micro-dimple and micro-channel texture geometries

Contact Info

Product

Resources

About