Parametric optimization and modeling for flank wear of TiSiN-TiAlN Nanolaminate Cutting Insert / M. Kaladhar

Selection of machining parameters and better prediction for cutting tool flank wear is indispensable in hard machining as flank wear is directly influences the quality of machined surface. In the current study, parametric optimization and predictive model were carried out for the flank wear of TiSiN...

Full description

Saved in:
Bibliographic Details
Main Author: M., Kaladhar (Author)
Format: Book
Published: Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM), 2020.
Subjects:
Online Access:Link Metadata
Tags: Add Tag
No Tags, Be the first to tag this record!

MARC

LEADER 00000 am a22000003u 4500
001 repouitm_36588
042 |a dc 
100 1 0 |a M., Kaladhar  |e author 
245 0 0 |a Parametric optimization and modeling for flank wear of TiSiN-TiAlN Nanolaminate Cutting Insert / M. Kaladhar 
260 |b Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM),   |c 2020. 
500 |a https://ir.uitm.edu.my/id/eprint/36588/1/36588.pdf 
520 |a Selection of machining parameters and better prediction for cutting tool flank wear is indispensable in hard machining as flank wear is directly influences the quality of machined surface. In the current study, parametric optimization and predictive model were carried out for the flank wear of TiSiN-TiAlN nanolaminate cutting insert in hard turning of 58 HRC AISI 1045 medium carbon steel which is an unexplored area. Taguchi's method was employed for parametric optimization and predictive model was established for flank wear by response surface methodology (RSM) based regression analysis. Cutting speed: 40m/min, feed rate: 0.3 mm/rev and depth of cut: 75 μm generates optimum value of flank wear 0.07 mm. In conclusion, verification test was carried out to validate the optimal set of parameters and the result was shown a great reduction of 81.42% in the flank wear. The predictive model elaborated for flank wear was dependable and helps to make better prediction to the manufacturing industries within specified range of the experimentation. 
546 |a en 
690 |a TJ Mechanical engineering and machinery 
655 7 |a Article  |2 local 
655 7 |a PeerReviewed  |2 local 
787 0 |n https://ir.uitm.edu.my/id/eprint/36588/ 
787 0 |n https://jmeche.uitm.edu.my/ 
856 4 1 |u https://ir.uitm.edu.my/id/eprint/36588/  |z Link Metadata