MATEC Web Conf.
Volume 192, 2018The 4th International Conference on Engineering, Applied Sciences and Technology (ICEAST 2018) “Exploring Innovative Solutions for Smart Society”
|Number of page(s)||4|
|Section||Track 1: Industrial Engineering, Materials and Manufacturing|
|Published online||14 August 2018|
Estimation of residual life of a cutting tool used in a machining process
Manufacturing Technology Department, National Institute of Technical Teachers’ Training & Research, Kolkata, India
2 Education and Management Department, National Institute of Technical Teachers’ Training & Research, Kolkata, India
3 Mechanical Engineering Department, National Institute of Technical Teachers’ Training & Research, Kolkata, India
Sourath Ghosh: email@example.com
A significant part of cost of machining is associated with non-optimum use of cutting tool. Moreover cutting tool failure is responsible for almost 20% of the machining downtime. Thus, having knowledge of residual life of cutting tool is highly recommended so as to maximise the availability time and reduce the machining cost. The aim of this work is to find out residual life of a worn cutting tool which has been used for turning of Ti-6Al-4V alloy under constant cutting condition. The lognormal distribution is used to model the cutting tool life data. Remaining useful life of cutting tool is estimated using Mean Remaining Life (MRL) function. The results obtained from model are compared with the experimental results and it shows good agreement.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.