AbstractDuring manufacturing processes, workpiece temperature may vary due to factors arising from the process such as tool/workpiece friction. Workpiece temperature may also vary due to the environmental conditions and these variations can affect the dimensional accuracy of the manufactured workpiece. The surface temperature of a part being manufactured can vary significantly from the core temperature, especially during dry cutting processes or when the environmental conditions are changing rapidly. It is known that the expansion of a part is controlled by its average temperature and can be influenced more by the core temperature of the part than the surface temperature due to the relative material
volumes. Therefore, to effectively control or compensate for the effects of temperature variation as it relates to material expansion, there is a need to measure the core temperature of the workpiece accurately. Due to the harsh nature of many manufacturing environments, the required accuracy and resolution for temperature measurement in precision manufacturing are rarely achieved.
The aim of this research is to measure core temperature of workpieces during manufacturing processes with accuracy and resolution based on industry requirements. The main research objectives include simulating the chosen temperature measurement method to determine its suitability, designing a system for core temperature measurement, and using the designed system for core temperature measurement during a manufacturing process.
In this thesis, after reviewing the different temperature measurement methods with greater emphasis on those applicable to the manufacturing process, the ultrasonic thermometry was chosen for further study. The speed of sound in any medium depends on the temperature of the medium. Hence, if the length and time of travel of an ultrasonic wave can be measured, the speed, and consequently the temperature, can be measured. Since the ultrasonic method gives the average of the travel path, the core temperature can be obtained.
To verify these theories and determine the cost-effective technique of ultrasonic measurement for the present task, the MATLAB k-Wave toolbox was used for simulating the two main techniques of ultrasonic measurement – the pulse-echo and phase-shift methods. Using steel as the medium of propagation, the simulation results showed that both techniques can be used for the present task. However, further analysis of the results showed that the phase-shift technique could be the costeffective option. Therefore, the phase-shift technique was chosen for the bench tests. Controlled heating of a steel test part was performed using a liquid bath calibrator and a reference temperature sensor for accurate comparison. The results showed that the measured temperature values using the phase-shift ultrasonic method agree with the reference PT100 measurements with the required resolution and accuracy. The phase-shift card used in this method is a cost-effective solution that eliminates the need for the expensive pulser-receivers used for the ultrasonic pulse-echo method.
Thereafter, the setup was used on a computer numeric control machine while incrementally introducing different levels of uncertainty to the manufacturing process. The results show that the phase-shift ultrasonic thermometry method measures workpiece temperature during subtractive manufacturing processes with accuracy of ±1 ℃. The setup was also used on a coordinate measuring machine during dimensional inspection. This test was set up to compare the calculated expansion based on core and surface temperature measurements with the measured expansion. The results show that the surface temperature-based expansion error is approximately 0.5 µm more than that of the core temperature. Finally, the created setup was used on an aluminium workpiece. The temperature measurement has error values within ±0.45 ℃ when compared with the reference PT100 readings with standard deviation of 0.1 ℃.
This is the first time that ultrasonic thermometry has been used to measure temperature of metal components being machined and is a novel solution to the significant challenges of part temperature measurement during machining.
|Date of Award||2023|
|Supervisor||Simon Fletcher (Main Supervisor), Andrew Longstaff (Co-Supervisor) & Naeem Mian (Co-Supervisor)|