Date of Award

Spring 2012

Project Type


Program or Major

Mechanical Engineering

Degree Name

Master of Science

First Advisor

Barry K Fussell


Accurate estimation of cutting coefficients is extremely important in end milling process modeling, and it forms the basis of a smart machining system that can be used for process planning and monitoring. Specific applications include feedrate selection based on force constraints and monitoring of tool wear [1, 2].

This thesis investigates five different methods to calibrate the cutting force model coefficients in end milling processes and compares them in terms of cost, efficiency, compliance, accuracy, repeatability and applicability. The five methods are based on: 1. spindle motor power, 2. Kistler average force, 3. Kistler force profile, 4. Smart Tool average force and 5. Smart Tool force profile. Three different sensors are used in the calibration processes: 1. a spindle motor power sensor purchased from Load Control Inc, 2. a Kistler dynamometer which measures the workpiece reaction force in the X and Y directions and 3. a wireless Smart Tool which measures tangential and radial cutting forces on the tool. For the power sensor, only average power is available to calibrate the cutting coefficients, while for the Kistler dynamometer and the Smart Tool, both average force and force profiles are used to calibrate the cutting coefficients.

Applicability and limitations of each calibration method are discussed, and general conclusions are made for on-line calibration.