NDLI: Performance prediction of high-pressure coolant assisted turning of Ti-6Al-4V

Content Provider	Springer Nature Link
Author	Mia, Mozammel Khan, Md Awal Dhar, Nikhil Ranjan
Copyright Year	2016
Abstract	The present study focuses on the development of predictive models of average surface roughness, chip-tool interface temperature, chip reduction coefficient, and average tool flank wear in turning of Ti-6Al-4V alloy. The cutting speed, feed rate, cutting conditions (dry and high-pressure coolant), and turning forces (cutting force and feed force) were the input variables in modeling the first three quality parameters, while in modeling tool wear, the machining time was the only variable. Notably, the machining environment influences the machining performance; yet, very few models exist wherein this variable was considered as input. Herein, soft computing-based modeling techniques such as artificial neural network (ANN) and support vector machines (SVM) were explored for roughness, temperature, and chip coefficient. The prediction capability of the formulated models was compared based on the lowest mean absolute percentage error. For surface roughness and cutting temperature, the ANN and, for chip reduction coefficient, the SVM revealed the lowest error, hence recommended. In addition, empirical models were constructed by using the experimental data of tool wear. The adequacy and good fit of tool wear models were justified by a coefficient of determination value greater than 0.99.
Starting Page	1433
Ending Page	1445
Page Count	13
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	90
Issue Number	5-8
e-ISSN	14333015
Language	English
Publisher	Springer London
Publisher Date	2016-09-23
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Artificial neural network Support vector regression High-pressure coolant Surface roughness Cutting temperature Chip reduction coefficient Industrial and Production Engineering Media Management Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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High-pressure coolant on flank and rake surfaces of tool in turning of Ti-6Al-4V: investigations on forces, temperature, and chips

High-pressure coolant on flank and rake surfaces of tool in turning of Ti-6Al-4V: investigations on surface roughness and tool wear

Mono-objective and multi-objective optimization of performance parameters in high pressure coolant assisted turning of Ti-6Al-4V

The influence of hydrogen on chip formation in cutting Ti-6Al-4V alloys

Advantages of milling and drilling Ti-6Al-4V components with high-pressure coolant

Optimization of surface roughness and cutting temperature in high-pressure coolant-assisted hard turning using Taguchi method

Tool wear and cutting forces variation in high-speed end-milling Ti-6Al-4V alloy

Assessment of the machinability of Ti-6Al-4V alloy using the wear map approach

Finite element simulation for Ti-6Al-4V alloy deformation near the exit of orthogonal cutting

Performance prediction of high-pressure coolant assisted turning of Ti-6Al-4V

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