Machining is an important fabrication process in manufacturing industry and is achieved using various cutting tools. Apart from its intended applications the machined components may have to meet the ergonomics need. Understanding of the process parameters involved in machining of the finished product is made easy by mathematical modeling, relating the cause and action. Investigations were carried out to improvise the cutting tool life using numerical & finite element models to link process variables in machining to process outcomes such as tool life, surface roughness & wear resistance. The present work makes an attempt to carry out empirical modeling of the machining aspects of Inconel 718 & Ti-6Al-4V alloys with indexable carbide inserts. The effective contribution of input parameters over the process outcome was determined using statistical tool Minitab - 17.
Skip Nav Destination
Article navigation
16 February 2021
ADVANCED TRENDS IN MECHANICAL AND AEROSPACE ENGINEERING: ATMA-2019
7–9 November 2019
Bangalore, India
Research Article|
February 16 2021
Mathematical modeling for machining of Inconel 718 & titanium 64 alloys
V. Bharathi;
V. Bharathi
a)
Department of Mechanical Engg, BMS College of Engg
, Bengaluru, Karnataka, India
a)Corresponding author e-mail: [email protected]
Search for other works by this author on:
A. R. Anilchandra;
A. R. Anilchandra
Department of Mechanical Engg, BMS College of Engg
, Bengaluru, Karnataka, India
Search for other works by this author on:
Lochan Upadhayay;
Lochan Upadhayay
Department of Mechanical Engg, BMS College of Engg
, Bengaluru, Karnataka, India
Search for other works by this author on:
Sagar Pandit;
Sagar Pandit
Department of Mechanical Engg, BMS College of Engg
, Bengaluru, Karnataka, India
Search for other works by this author on:
Pranish Bhuju
Pranish Bhuju
Department of Mechanical Engg, BMS College of Engg
, Bengaluru, Karnataka, India
Search for other works by this author on:
a)Corresponding author e-mail: [email protected]
AIP Conf. Proc. 2316, 030008 (2021)
Citation
V. Bharathi, A. R. Anilchandra, Lochan Upadhayay, Sagar Pandit, Pranish Bhuju; Mathematical modeling for machining of Inconel 718 & titanium 64 alloys. AIP Conf. Proc. 16 February 2021; 2316 (1): 030008. https://doi.org/10.1063/5.0036449
Download citation file:
Pay-Per-View Access
$40.00
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Citing articles via
Inkjet- and flextrail-printing of silicon polymer-based inks for local passivating contacts
Zohreh Kiaee, Andreas Lösel, et al.
Effect of coupling agent type on the self-cleaning and anti-reflective behaviour of advance nanocoating for PV panels application
Taha Tareq Mohammed, Hadia Kadhim Judran, et al.
Design of a 100 MW solar power plant on wetland in Bangladesh
Apu Kowsar, Sumon Chandra Debnath, et al.
Related Content
Surface roughness optimization on steel fiber reinforced geopolymer fly ash by CNC milling operation
AIP Conf. Proc. (July 2019)
Electrolytic in-process dressing grinding – A review
AIP Conf. Proc. (February 2021)
Experimental evaluation of cryogenic cooling’s influence on surface roughness in monel milling
AIP Conf. Proc. (August 2024)
Optimization of metal removal rate, surface roughness and hardness using the Taguchi method in CNC turning machine
AIP Conf. Proc. (September 2023)
Effect of spindle speed and depth of cut on AISI 1045 material roughness on turning process
AIP Conf. Proc. (March 2023)