Cutting tool wear is known to affect tool life, surface quality, overall production time and cost.  Also carrying on the process with a dull tool may damage the workpiece material fabricated.
On the other hand it is unnecessary to change the cutting tool if it is still able to continue with cutting   operation. Therefore tool wear detection is one of the major concerns for increasing the productivity, decreasing the operation cost and has the potential to play a critical role in ensuring the dimensional accuracy of the work piece and prevention of damage to cutting equipment.

It could also help in automating cutting processes. There are several offline and online techniques to monitor tool conditions but are either costly (like dynamometers ) or unreliable for industrial and shop floor application (like vibration or acoustic measures). Therefore the  intent of this project is to implement  findings (of references mentioned) with regard to current-force calibration and the effectiveness of current sensing as a substitute for the use of expensive dynamometers.

This project combines the research of both the references and try to implement a low cost online tool wear detection solution using simple and cost effective techniques .It can be obtained by  two steps. First, Cutting Force Data Acquisition through Motor Current Sensing. The method utilizes a combination of axis motor current sensing using Hall-effect sensors and then calibration of the current data to the cutting force data obtained using any reliable force measuring device, dynamometer in this case (calibration is a onetime process and therefore dynamometer cost does not add to final product). Secondly, Tool Wear condition monitoring using current sensor based cutting force. Functional dependency of the feed cutting force on tool wear and cutting parameters are expressed in the form of a difference equating relating variation in the feed cutting force to tool wear rate. The computerized system automatically compares successive feed cutting force estimates and determines the onset of accelerated tool wear in order to issue a request for tool replacement. The technique can be used for fabricating monitoring devices for different types of shop floor applications and therefore has a wide scope.


Development of Autonomous Machining Database at the Machine Level (Part 1)

– Cutting Force Data Acquisition through Motor Current Sensing

M.K. Cheng, P.K. Venuvinod

Department of Manufacturing Engineering and Engineering Management, City University of Hong

Kong, 81 Tat Chee Avenue, Hong Kong

Current-Sensor-Based Feed Cutting Force Intelligent Estimation and Tool Wear Condition Monitoring.

-Xiaoli Li, Alexandar Djordjevich, and Patri K. Venuvinod.


Shaper on which cutting  tool wear was tested.

External Circuitary of the shaper’s motor. One of the motor’s phase is connected to hall effect current  sensor (yellow wire).


Calibration of the current data to the cutting force data obtained, using  dynamometer.

Arduino Mega and Hall-effect sensor for collecting experimental data. Yellow wire is connected to one phase of the motor and black wire is connected to the mains.


Matlab plot of experimental results. The graph peak shows the cutting tool wear.