scholarly journals Complex Order PIα+jβ Dγ+jθ Design for Surface Roughness Control in Machining CNT Al-Mg Hybrid Composites

2020 ◽  
Vol 5 (6) ◽  
pp. 299-306
Author(s):  
Ravi Sekhar ◽  
Tejinder Paul Singh ◽  
Pritesh Shah
Keyword(s):  
Surface Roughness ◽  
Hybrid Composites ◽  
Complex Order ◽  
Roughness Control

Multi Objective Optimization of Cutting Parameters in Machining Cellulose Based Hybrid Composites

2015 ◽  
Vol 761 ◽  
pp. 287-292
Author(s):  
Raja Izamshah ◽  
Zainudin Zuraidah ◽  
Mohd Shahir Kasim ◽  
M. Hadzley ◽  
M. Amran
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Hybrid Composites ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Machining Performance ◽  
Machined Surface ◽  
Multi Objective ◽  
Optimization Of Cutting Parameters

Cellulose based hybrid composites are gaining popularity in the growing green communities. With extensive studies and increasing applications for future advancement, the need for an accurate and reliable guidance in machining this type of composites has increased enormously. Smooth and defect free machined surface are always the ultimate objectives. The present work deals with the study of machining parameters (i.e. spindle speed, feed rate and depth of cut) and their effects on machining performance (i.e. surface roughness and delamination) to establish an optimized setup of machining parameters in achieving multi objective machining performance. Cellulose based hybrid composites consist of jute (a bast fiber) and glass fiber embedded in polyester resins. Response Surface Methodology (RSM) using Box-Behnken Design (BBD) was chosen as the design of experiment approach for this study. Based on that experimental approach, 17 experimental runs were conducted. Mathematical model for each response was developed based on the experimental data. Adequacy of the models were analyzed statistically using Analysis of Variance (ANOVA) in determining the significant input variables and possible interactions. The multi objective optimization was performed through numerical optimization, and the predicted results were validated. The agreement between the experimental and selected solution was found to be strong, between 95% to 96%, thus validating the solution as the optimal machining condition. The findings suggest that feed rate was the main factor affecting surface roughness and delamination .

Epitaxial Growth and Surface Roughness Control of Ferromagnetic Thin Films on Si by Sputter Deposition

2007 ◽  
Vol 37 (3) ◽  
pp. 355-360 ◽  
Author(s):  
Jianhua Joshua Yang ◽  
C.-X. Ji ◽  
Ying Yang ◽  
Hua Xiang ◽  
Y. A. Chang
Keyword(s):  
Thin Films ◽  
Surface Roughness ◽  
Epitaxial Growth ◽  
Sputter Deposition ◽  
Ferromagnetic Thin Films ◽  
Roughness Control

Optimization of the Properties of Macroporous Chromatography Silica Supports through Surface Roughness Control

2009 ◽  
Vol 21 (9) ◽  
pp. 1884-1892 ◽  
Author(s):  
Anne Galarneau ◽  
Nathalie Calin ◽  
Julien Iapichella ◽  
Maud Barrande ◽  
Renaud Denoyel ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Silica Supports ◽  
Roughness Control

scholarly journals Effect of different polishing systems on the surface roughness of nano-hybrid composites

2016 ◽  
Vol 19 (1) ◽  
pp. 37 ◽  
Author(s):  
Naveen Chhabra ◽  
Brijesh Patel ◽  
Disha Jain
Keyword(s):  
Surface Roughness ◽  
Hybrid Composites
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