Multi-response optimization of dry sliding wear parameters of AA6026 using hybrid gray relational analysis coupled with response surface method

Gajalakshmi, K; Senthilkumar, N.; Prabu, B.

doi:10.1177/0020294019842603

Cited by 70 publications

(26 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to optimize the surface roughness, the experimental optimization method was preferred. In this investigation, the Taguchi method [27][28][29][30][31][32] was adopted so as to optimize the surface roughness.…”

Section: Optimization For Surface Roughness In Polishing Processmentioning

confidence: 99%

Experimental study on polishing process of cylindrical roller bearings

Nguyen

Chau

Dao

et al. 2019

Measurement and Control

View full text Add to dashboard Cite

The surface quality and accuracy of the geometry of the cylindrical rollers are important factors for bearing life. This paper presents effects of machining parameters on the surface roughness, topography and roundness of cylindrical rollers through the lapping and polishing experiments. And then the surface roughness of the cylindrical rollers is optimized. The results found that the surface roughness of rollers is significantly changed in lapping process with different abrasive particle sizes, while the surface roughness has slightly reduced in polishing process. It also indicated that the smoother surfaces with better roughness can be obtained after lapping and polishing process. In addition, the surface roughness of cylindrical rollers is rapidly reduced from Ra of 0.5 µm to Ra of 0.063 µm after the 3-h lapping process and Ra of 0.013 µm after the 1-h polishing process. The surface topography of rollers can be achieved by the smoother surface when loads are from 25 to 35 N in lapping process, and the loads are from 35 to 40 N in polishing process. Finally, the Taguchi method is applied to optimize the surface roughness in polishing process. The result found that the optimal surface roughness achieves 0.015 µm with respect to the time of 35 min and type of 4000# Al2O3.

show abstract

Section: Optimization For Surface Roughness In Polishing Processmentioning

confidence: 99%

Experimental study on polishing process of cylindrical roller bearings

Nguyen

Chau

Dao

et al. 2019

Measurement and Control

View full text Add to dashboard Cite

show abstract

“…The 3D response plot is an alternative and identical design to the contour plot. A response surface is a geometric illustration attained once an output parameter is designed as a relationship with one or more quantitative independent factors [37]. Response surface plots were drawn for the output responses SR and removal of material from workpiece for the most significant parameters based on the ANOVA table.…”

Section: Fig 5 Interaction Plot For Grgmentioning

confidence: 99%

Performance of Zinc Coated Electrode Wire and Parametric Optimization During Profile Cutting of Die-Steel

Saravanan*,

Thiyagarajan,

Somasundaram

2020

IJITEE

View full text Add to dashboard Cite

In this work, the effect of brass wire coated with zinc as electrode wire towards maximizing MRR and minimizing SR for the considered input parameters was studied in elaborate during profile cutting of tool steel AISI D3. Experiments were designed based on the L18(21 ,37 ) Taguchi’s orthogonal array considering cutting speed, Ton and Toff, wire tension, servo feed rate and voltage, current and electrode feed rate. The outputs MRR and SR were analyzed and optimized using Grey Relational Analysis (GRA) simultaneously. For both SR and MRR, the drawn chart shows that, the raw data’s lies within upper and lower control limits. The optimum input conditions obtained for higher MRR and lower SR were: 75% of cutting speed, 128 µsec of Ton, 54µsec of Toff, 190A of input current, electrode feed of 3 mm/min with 7 gm of electrode tension, 10V of servo voltage and 2060 mm/min of 10V. Execution of ANOVA on grey grade identifies that, wire tension was the parameter that influences more by 25.89%, followed by Ton and servo voltage by 21.37% and feed rate of wire by 11.89%, with an R2 value of 96.55%. For validating the results, confirmation experiment was also done

show abstract

“…Grey Relational Analysis (GRA) is adopted for identifying the best combination of input factors for obtaining better output variables [24], [25]. GRA is largely used for judging or to evaluate the dependent variable performance that has a little amount of information, but in grey analysis, the data must be initially pre-processed for conversion into some sort of indices that can quantify the data through normalizing the raw data for further analysis [26]- [28].…”

Section: Grey Relational Approachmentioning

confidence: 99%

Enhancing the Tool Die Steel P rofile C utting P erformance in WEDM P rocess

Saravanan*¹,

Thiagarajan²,

Somasundaram³

2019

IJEAT

View full text Add to dashboard Cite

This work elaborates the experimental work on Material Removal Rate (MRR) and Surface Roughness (SR) output conditions of Wire-Electrical Discharge Machining (WEDM) and finding the optimal input conditions through Taguchi method coupled with Grey relational analysis for lower SR and higher MRR during profile cutting of high strength D3 tool steel, which is the need of the hour in industries. The machining factors considered for investigation which influences MRR and SR were: cutting speed, pulse on-time and off-time, input current, wire tension and feed and servo feed and voltage. A L18 orthogonal array was considered for mixed-level experimental design through Taguchi’s approach and for multi-criteria optimization Grey Relational Analysis was applied. Outcome shows that SR increases with the increase of pulse on-time and decreases with increase in pulse off-time and MRR increases as the pulse on-time increases due to longer spark duration. Both SR and MRR are well within the control limits and servo voltage is the most influential parameter contributing by 48.48%, followed by wire feed rate, input current and servo feed rate with an R2 value of 95.85%, identified through Analysis of Variance (ANOVA). With obtained optimum conditions, a validation experiment was conducted to authenticate the results, which indicates a worthy agreement with predicted output characteristics.

show abstract

Multi-response optimization of dry sliding wear parameters of AA6026 using hybrid gray relational analysis coupled with response surface method

Cited by 70 publications

References 16 publications

Experimental study on polishing process of cylindrical roller bearings

Experimental study on polishing process of cylindrical roller bearings

Performance of Zinc Coated Electrode Wire and Parametric Optimization During Profile Cutting of Die-Steel

Enhancing the Tool Die Steel P rofile C utting P erformance in WEDM P rocess

Contact Info

Product

Resources

About