Influence of different grades of CBN inserts on cutting force and surface roughness of AISI H13 die tool steel during hard turning operation
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Published version
Author(s)
Type
Journal Article
Abstract
Now-a-days, the application of hard tuning with CBN tool has been massively increased because the hard turning is a good alternative to grinding process. However, there are some issues that need to be addressed related to the CBN grades and their particular applications in the area of hard turning process. This experimental study investigated the effects of three different grades of CBN insert on the cutting forces and surface roughness. The process of hard turning was made using the AISI H13 die tool steel at containing different hardness (45 HRC, 50 HRC and 55 HRC) levels. The work material were selected on the basis of its application in the die making industries in a range of hardness of 45–55 HRC. Optimization by the central composite design approach has been used for design and analysis. The present study reported that the cutting forces and surface roughness are influenced by the alloying elements and percentage of CBN in the cutting tool material. The work material hardness, feed rate and cutting speed are found to be statistically significant on the responses. Furthermore, a comparative performance between the three different grades of CBN inserts has been shown on the cutting forces and surface roughness at different workpiece hardness. To obtain the optimum parameters from multiple responses, desirability approach has been used. The novelty/robustness of the present study is represented by its great contribution to solve practical industrial application when is developed a new process using different CBN grades for hard turning and die makers of workpiece having the hardness between 45 and 55 HRC.
Date Issued
2019-01-07
Date Acceptance
2018-12-28
Citation
Materials, 2019, 12 (1)
ISSN
1996-1944
Publisher
MDPI
Journal / Book Title
Materials
Volume
12
Issue
1
Copyright Statement
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Subjects
Science & Technology
Technology
Materials Science, Multidisciplinary
Materials Science
CBN
cutting forces
optimization
turning
surface roughness
PREDICTION MODEL
NEURAL-NETWORK
OPTIMIZATION
MACHINABILITY
TOPOGRAPHY
PARAMETERS
FINISH
WEAR
METHODOLOGY
COMPOSITE
03 Chemical Sciences
09 Engineering
Publication Status
Published
Article Number
ARTN 177