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Multi parameter optimization in end milling of S-glass fiber reinforced polymer composite using Taguchi technique coupled with Grey Relational Analysis
https://orcid.org/http://orcid.org/0000-0002-5702-886X
This research paper presents a novel investigation into optimizing the milling process of S-GFRP composites using a combination of spindle speed, cutting depth, and feed rate. The study utilizes the Taguchi method and a unique Orthogonal Array L9 design to examine the impact of different parameter combinations on cutting force, surface roughness, and delamination. The results of this study are further analyzed through a combination of Grey Relational Analysis and ANOVA to determine the significance of each input parameter. The findings of this work demonstrate that the speed of the spindle is the most influential factor with largest contribution of 66.64% on all three responses, followed by feed with 26.12% contribution and cutting depth contribution 5.78%. this research provides a valuable insights for the optimization of end milling processes in S-GFRP composite materials. The findings can be used to improve the performance and quality of machined S-GFRP composite parts.
Multi parameter optimization in end milling of S-glass fiber reinforced polymer composite using Taguchi technique coupled with Grey Relational Analysis
https://orcid.org/http://orcid.org/0000-0002-5702-886X
This research paper presents a novel investigation into optimizing the milling process of S-GFRP composites using a combination of spindle speed, cutting depth, and feed rate. The study utilizes the Taguchi method and a unique Orthogonal Array L9 design to examine the impact of different parameter combinations on cutting force, surface roughness, and delamination. The results of this study are further analyzed through a combination of Grey Relational Analysis and ANOVA to determine the significance of each input parameter. The findings of this work demonstrate that the speed of the spindle is the most influential factor with largest contribution of 66.64% on all three responses, followed by feed with 26.12% contribution and cutting depth contribution 5.78%. this research provides a valuable insights for the optimization of end milling processes in S-GFRP composite materials. The findings can be used to improve the performance and quality of machined S-GFRP composite parts.
Multi parameter optimization in end milling of S-glass fiber reinforced polymer composite using Taguchi technique coupled with Grey Relational Analysis
https://orcid.org/http://orcid.org/0000-0002-5702-886X
This research paper presents a novel investigation into optimizing the milling process of S-GFRP composites using a combination of spindle speed, cutting depth, and feed rate. The study utilizes the Taguchi method and a unique Orthogonal Array L9 design to examine the impact of different parameter combinations on cutting force, surface roughness, and delamination. The results of this study are further analyzed through a combination of Grey Relational Analysis and ANOVA to determine the significance of each input parameter. The findings of this work demonstrate that the speed of the spindle is the most influential factor with largest contribution of 66.64% on all three responses, followed by feed with 26.12% contribution and cutting depth contribution 5.78%. this research provides a valuable insights for the optimization of end milling processes in S-GFRP composite materials. The findings can be used to improve the performance and quality of machined S-GFRP composite parts.
Multi parameter optimization in end milling of S-glass fiber reinforced polymer composite using Taguchi technique coupled with Grey Relational Analysis
Int J Interact Des Manuf
Kumar, G. Vijay (author) / Gopalakrishnaiah, P. (author) / Devi, M. Radha (author) / Vardhan, T. Vishnu (author) / Yelamasetti, Balram (author)
2024-07-01
10 pages
Article (Journal)
Electronic Resource
English
S-GFRP composite , Milling optimization , Taguchi method , Orthogonal Array , Grey Relational Analysis , ANOVA , Spindle speed , Cutting depth , Feed rate , Cutting force , Surface roughness , Delamination Engineering , Engineering, general , Engineering Design , Mechanical Engineering , Computer-Aided Engineering (CAD, CAE) and Design , Electronics and Microelectronics, Instrumentation , Industrial Design
| British Library Online Contents | 2016