Of all the processes used to shape metals, it is machining in which the conditions of operation are most varied. Good dimensional accuracy and surface quality from machining processes should be maintained such that the product's function and customer's satisfaction are assured. On the other hand, advanced ceramics have emerged as an important class of materials with uses in a variety of high performance applications such as aerospace, engines, and cutting tools. Many of these applications require the machining of ceramic component surfaces with tight dimensional accuracy and surface finish.

Among the many of possible causes which can tarnish the machined surface quality, the most important ones, such as tool vibration and elastoplastic deformation, are identified. This research is, therefore, focused on the analyses of these identified factors in order to have a better understanding of their roles in the surface texture formation process during machining, which in turn can improve the efficiency and quality of machining processes.

The irregularities of a machined surface due to random tool vibration are investigated through a Markov-chain based stochastic approach. The dynamic characteristics of the metal cutting processes, especially the variation of material properties such as the microhardness, are modeled as a Markov- chain type random tool motion during machining.

An updated Langrange method is applied for the analysis of elastoplastic deformation observed on machined surfaces. A three dimensional finite element model is built to simulate a single-point metal cutting process. The results of the analysis could be applied as surface texture modification model to enhance the accuracy of the prediction of a machined surface texture.

By combining the aforementioned analytical work, a computer-based surface topography simulator, which can predict the surface topography formed under a given machining process, is developed. Experimental work is also performed to verify the results predicted by the simulator.

The study of machining of advanced ceramics (such as aluminum oxide and DICOR) is focused on the fundamental material removal mechanisms during machining. Based on the study, a cost- effective, chemical-assisted novel machining process is proposed to improve the surface quality.