Abstract
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.
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. M., Kaladhar kaladhar2k@gmail.com |
Subjects: | T Technology > TJ Mechanical engineering and machinery |
Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Mechanical Engineering |
Journal or Publication Title: | Journal of Mechanical Engineering (JMechE) |
UiTM Journal Collections: | UiTM Journal > Journal of Mechanical Engineering (JMechE) |
ISSN: | 1823-5514 ; 2550-164X |
Volume: | 17 |
Number: | 3 |
Page Range: | pp. 69-84 |
Keywords: | Flank wear; Taguchi method; RSM based Modeling; optimization; Nanolaminate cutting insert |
Date: | 2020 |
URI: | https://ir.uitm.edu.my/id/eprint/36588 |