SUMMARY

Single point machining processes such as turning and boring are used extensively in manufacturing applications, including gas turbine rotor and stator production. Though analytical methods exist to describe process parameters such as cutting forces and dynamic instability in such processes, machining is a highly complex nonlinear process and therefore such methods cannot account for process uncertainties. Therefore, the machining process requires on-line system monitoring in addition to physics-based modelling to maximize production and minimize costs.

For this thesis, a low-cost, high fidelity measurement system consisting of a thin film Polyvinylidene Fluoride (PVDF) piezoelectric strain rosette and data logging electronics has been designed and evaluated for monitoring the dynamic cutting forces and torque in turning and boring processes. In addition, the PVDF measurement system is evaluated towards on-line recognition of dynamic instability, known as chatter, that occurs during the single-point cutting process. The performance of several chatter detection algorithms applied to turning force and boring torque data is evaluated with a focus on embedded electronic automation.