scholarly journals Calibration and Characterization of a Low-Cost Wireless Sensor for Applications in CNC End Milling

2012 ◽  
Author(s):  
Andrew Harmon ◽  
Barry K. Fussell ◽  
Robert B. Jerard
Keyword(s):  
End Milling ◽  
Low Cost ◽  
Force Sensor ◽  
Industrial Applications ◽  
Milling Process ◽  
Research Progress ◽  
Machining System ◽  
Smart Machining ◽  
Band Limited ◽  
Cnc End Milling

This paper describes recent research progress at the University of New Hampshire in the area of smart machining systems. Central to creating a smart machining system is the challenge of collecting detailed information about the milling process at the tool tip. This paper discusses the design, static calibration, dynamic characterization, and implementation of a low-cost wireless force sensor for end-milling. The sensor is observed to accurately measure force when most of the cutting power is band-limited below the sensor’s natural frequency. Sensor geometry constrains the milling application to a single tooth cutter; while this constraint is impractical for industrial applications, our sensor is shown to provide useful information in a laboratory setting.

Integration of Wireless Sensors and Models for a Smart Machining System

2009 ◽  
Author(s):  
Robert B. Jerard ◽  
Barry K. Fussell ◽  
Chris A. Suprock ◽  
Yanjun Cui ◽  
Jeffrey Nichols ◽  
...  
Keyword(s):  
Low Cost ◽  
Spindle Motor ◽  
Vibration Sensor ◽  
Machining Process ◽  
Sensor Data ◽  
Research Progress ◽  
Force Model ◽  
Calibration Methods ◽  
Machining System ◽  
Smart Machining

This paper describes recent research progress at the University of New Hampshire in the area of “Smart Machining Systems (SMS)”. Our approach to SMS is to integrate models with wireless embedded sensor data to monitor and improve the machining process. This paper discusses recent progress in low-cost wireless sensor development, model calibration methods, model accuracy, and tool condition monitoring for SMS. We describe a system that can estimate tool wear using the coefficients of a tangential cutting force model. The model coefficients are estimated by online measurement of spindle motor power. We also show the use of a cutting tool embedded with a wireless vibration sensor to detect the onset of chatter in real-time.

Optimization of Process Parameters for Cutting Force for Aluminium 7010 in CNC End Milling Process

2018 ◽  
Vol 10 (6) ◽  
Author(s):  
M. Kishanth ◽  
P. Rajkamal ◽  
D. Karthikeyan ◽  
K. Anand
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Process Parameters ◽  
End Milling ◽  
Milling Process ◽  
Machining Process ◽  
Depth Of Cut ◽  
Optimization Of Process Parameters ◽  
Cnc End Milling ◽  
End Milling Process

In this paper CNC end milling process have been optimized in cutting force and surface roughness based on the three process parameters (i.e.) speed, feed rate and depth of cut. Since the end milling process is used for abrading the wear caused is very high, in order to reduce the wear caused by high cutting force and to decrease the surface roughness, the optimization is much needed for this process. Especially for materials like aluminium 7010, this kind of study is important for further improvement in machining process and also it will improve the stability of the machine.

scholarly journals Designing of milling tool spindle

2018 ◽  
Vol 53 (3) ◽  
pp. 191-198
Author(s):  
Jakeer Hussain Shaik ◽  
K Ramakotaiah
Keyword(s):  
Transfer Function ◽  
End Milling ◽  
Milling Process ◽  
Final Model ◽  
Chatter Vibrations ◽  
Milling Tool ◽  
Vibration Responses ◽  
Novel Method ◽  
Cnc End Milling ◽  
Spindle Structure

Analysis of chatter stability in an end milling process is quite cumbersome because of the inaccurate knowledge in the spindle’s geometrical design, position of the bearings and several issues related to the spindle structure. The effective position of bearings of the spindle plays a key role in investigating the self-excited chatter vibrations, which requires an accurate transfer function at the most flexibility region of the spindle tool structure. The present work focuses on the development of a novel method of measuring the spindle vibration responses experimentally using sine sweep tests for a CNC end milling machine tool. Using these model data, an analytical model of the spindle is estimated by considering the bearing span as a design variable. Trial runs are conducted until the convergence between the identified transfer function from the model and that from experiment is achieved. The final model of the spindle system is then applied with time-varying cutting forces so as to obtain the process stability.Bangladesh J. Sci. Ind. Res.53(3), 191-198, 2018

scholarly journals Non-Invasive Estimation of Machining Parameters during End-Milling Operations Based on Acoustic Emission

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5326
Author(s):  
Andrés Sio-Sever ◽  
Erardo Leal-Muñoz ◽  
Juan Manuel Lopez-Navarro ◽  
Ricardo Alzugaray-Franz ◽  
Antonio Vizan-Idoipe ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
End Milling ◽  
Low Cost ◽  
Milling Process ◽  
Machining Process ◽  
Measuring System ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Processes ◽  
Non Invasive

This work presents a non-invasive and low-cost alternative to traditional methods for measuring the performance of machining processes directly on existing machine tools. A prototype measuring system has been developed based on non-contact microphones, a custom designed signal conditioning board and signal processing techniques that take advantage of the underlying physics of the machining process. Experiments have been conducted to estimate the depth of cut during end-milling process by means of the measurement of the acoustic emission energy generated during operation. Moreover, the predicted values have been compared with well established methods based on cutting forces measured by dynamometers.

scholarly journals A Cyber-Physical System for Surface Roughness Monitoring in End-Milling

2019 ◽  
Author(s):  
Uroš Župerl ◽  
Franci Čuš
Keyword(s):  
Surface Roughness ◽  
Process Control ◽  
Neural Control ◽  
End Milling ◽  
Milling Process ◽  
Machining Parameters ◽  
Inference System ◽  
Machining System ◽  
Chip Size ◽  
Roughness Control

A cyber-psychical machining system (CPMS) is developed to realize smart end-milling process monitoring. The CPMS provides a novel way for controlling the cutting chip size and monitoring the surface roughness in milling processes through Internet of Things (IoT) applications. The two level CPMS is realized by linking the IoT machining platform for process control to the machine tool with integrated visual system (VS). The VS is employed to acquire the signals of the cutting chip size during the machining of difficult to cut materials. The machining platform performs instant chip size and surface roughness control based on advanced signal processing, edge computing, modeling and cognitive corrective process control acting. A cognitive neural control system (CNCS) is employed to control the chip size by modifying the machining parameters and consequently maintaining surface roughness constant. An adaptive neural inference system (ANFIS) is applied to precisely model and in-process predict the surface roughness. Machining tests conducted using the proposed CPMS indicate that the cutting chip size and consequently the produced surface roughness are well maintained when the cutting-depth profile of a workpiece is varying step-wise or continuously.

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