Paper Info
Title
Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140.
Abstract
Optimization of tool life is required to tune the machining parameters and achieve the desired surface roughness of the machined components in a wide range of engineering applications. There are many machining input variables which can influence surface roughness and tool life during any machining process, such as cutting speed, feed rate and depth of cut. These parameters can be optimized to reduce surface roughness and increase tool life. The present study investigates the optimization of five different sensorial criteria, additional to tool wear (V-B) and surface roughness (Ra), via the Tool Condition Monitoring System (TCMS) for the first time in the open literature. Based on the Taguchi L(9)orthogonal design principle, the basic machining parameters cutting speed (v(c)), feed rate (f) and depth of cut (a(p)) were adopted for the turning of AISI 5140 steel. For this purpose, an optimization approach was used implementing five different sensors, namely dynamometer, vibration, AE (Acoustic Emission), temperature and motor current sensors, to a lathe. In this context,V-B,Raand sensorial data were evaluated to observe the effects of machining parameters. After that, an RSM (Response Surface Methodology)-based optimization approach was applied to the measured variables. Cutting force (97.8%) represented the most reliable sensor data, followed by theAE(95.7%), temperature (92.9%), vibration (81.3%) and current (74.6%) sensors, respectively. RSM provided the optimum cutting conditions (atv(c)= 150 m/min,f= 0.09 mm/rev,a(p)= 1 mm) to obtain the best results forV(B),Raand the sensorial data, with a high success rate (82.5%).
Year
DOI
Venue
2020
10.3390/s20164377
SENSORS
Keywords
DocType
Volume
Tool Condition Monitoring,flank wear,surface roughness,cutting force,vibration,acoustic emission,temperature,motor current
Journal
20
Issue
ISSN
Citations 
16
1424-8220
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Mustafa Kuntoğlu100.34
Abdullah Aslan200.34
Hacı Sağlam300.34
Danil Yurievich Pimenov422.42
Khaled Giasin521.74
Tadeusz Mikolajczyk610.70