Abstract
Article history: Received January 6 2014 Received in Revised Format June 15 2014 Accepted July 25 2014 Available online August 1 2014 In the present work, a multi-response optimization method is used to optimize the machining parameters in turning of glass fiber reinforced polymer (GFRP) composites. Parameters like spindle speed (N), feed rate (f) and depth of cut (d) are taken to obtain the responses such as surface roughness (Ra) and material removal rate (MRR). Taguchi’s L9 orthogonal array has been used for machining the work-piece. Analysis of variance (ANOVA) has been carried out to check the significant process parameter in a single objective performance characteristic. The multiple performance characteristics have been analysed using Grey relational analysis and an appreciable result has been reported with this approach. © 2014 Growing Science Ltd. All rights reserved
Highlights
The use of machining such as turning, drilling, milling, etc. in glass fiber reinforced polymer (GFRP) composite is increasing as the field of application of composite is quite a lot
It is often made difficult to machine the GFRP composites as it brings many undesirable results such as rapid tool wear, a defective surface layer with cracks or delamination, a rough surface finish etc
Surface roughness of unidirectional GFRP composite was experimented by Işık (2008) on the basis of process parameters such as cutting speed, feed, depth of cut and tool geometry in turning with CERMET cutting tool and found that the surface quality is closely related with speed, feed and tool geometry
Summary
The use of machining such as turning, drilling, milling, etc. in GFRP composite is increasing as the field of application of composite is quite a lot. It is often made difficult to machine the GFRP composites as it brings many undesirable results such as rapid tool wear, a defective surface layer with cracks or delamination, a rough surface finish etc To avoid this problem, it is necessary to select the appropriate process parameters to get the highest performance for desired dimensional accuracy. Gupta and Kumar (2013) applied successfully the Grey relational theory to optimize the process parameters in multiple performance characteristics such as surface roughness and material removal rate during turning of GFRP with Poly-crystalline diamond cutting tool. Rao et al (2012) used Grey relational analysis for optimizing the multi- response characteristics to minimize the surface roughness and cutting force and maximize the tool life in machining of Inconel-718 with process parameters such as speed, feed, depth of cut and approach angle. Confirmation tests are conducted to validate the experimental results
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Industrial Engineering Computations
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
