This paper investigated the scribing process characteristics of the hard and brittle materials including single crystal silicon, STV glass, and sapphire substrate. Under various cutting angles, major process characteristics are examined including the groove geometry, specific cutting energy, and critical depth of cut at the onset of ductile-to-brittle cutting transition. As the cutting depth increases, groove geometry clearly reveals the ductile-to-brittle transition from the plastic deformation to a brittle fracture state. The material size effect in the ductile region as well as the transition in scribing behavior is well reflected by change in the specific cutting energy. Further, it is shown that the change of specific cutting energy as a function of the cutting depth can serve as a criterion for estimating the critical depth of cut. Such estimated critical depth of cut is confirmed by measurement from a 3D confocal microscope. The critical depths of cut for these hard materials are found to be between 0.1μm and 0.5μm depending on the materials and cutting angles.

Achieving a long wheel service life and an acceptable level of edge chipping in the groove grinding of single crystal silicon, such as in the die-sawing process, often requires timeconsuming trials for proper setting of important process parameters, including wheel selection, feed, speed, and cutting depth. To better understand the effect of various process parameters on edge chipping and wheel performance, this paper proposes a new process variable, the cutting depth ratio (CDR), to characterize the operating conditions of the groove grinding process. Combining the kinematic features of the grinding process and the material fracture criterion, the CDR, defined as the ratio of the maximum uncut chip thickness to the critical depth of cut of silicon, is employed to investigate the effect of uncut chip thickness on groove edge chipping and wheel performance. The magnitude of edge chipping is shown to steadily increase with increasing CDR, indicating increasing brittle behaviour of the material removal process as the uncut chip thickness increases. By using grinding ratio to correlate with wheel performance, it is shown that the grinding ratio first increases with increasing CDR, and reaches a peak value approximately at a CDR value of 1 before falling off at higher uncut chip thickness. The stochastic nature of the chip thickness is used to explain the finding that the best wheel performance occurs around unity CDR.

In an attempt to estimate the spread of errors in an EDM hole making process, a new Root-Sum-Square (RSS) method is proposed to combine the dimensional spread of a batch of electrodes with the over-cut variation in the micro-EDM process. Two sources of errors are commonly associated with an EDM process and contribute to the dimensional accuracy of the EDMed hole: the dimensional variation of the electrodes and the process over-cut error and its variation. Especially in a micro-EDM process, it is often difficult and time-consuming to measure the geometric dimension and tolerance of either a batch of electrodes or holes of small dimensions. By quantitatively establishing the relationship among the spreads in geometric errors of the electrodes and holes and the process capability, this new method provides an analytical tool in predicting hole error and allows allocating the tolerance budget when selecting the appropriate electrode making process, the EDM machine and process parameters. A series of experiments are carried out to establish and verify the RSS method. Given a set of EDM parameters and a batch of electrodes, the process error in the average over-cut and its spread is first obtained by the RSS method. The process error is then verified by separate experiments with electrodes of fixed dimension under the same EDM conditions. The validity of RSS method is further confirmed by experiments under different electrode dimensions. The RSS method is shown to well represent the contribution of both electrode and process errors to the statistical characteristics of the hole dimension. The establishment of this statistical error model should facilitate the design and control of hole quality by balancing the requirements for the dimensional accuracy of the electrodes and the process accuracy in a batch production environment.

Parts geometrical and dimensional error for a machining process can be attributed to several factors, including tool wear, thermal deformation, the machine tool positioning error and force-induced process error. Although the latter two factors are often more significant, their effect on the parts accuracy is more elusive and difficult to predict due to their inherent statistical dispersion property. It is therefore the subject of this investigation to quantitatively relate the parts error to machine tool spatial error and process-induced errors. Through root mean square calculation, a part error model is established by combining the machine tool positioning error, work vibration and tool vibration. The part error model considers two ranges of surface error consisting of surface roughness and cutting depth error of a machined plate. Using milling process as an example, the part error is predicted and compared with measurement result. The validity of this model is verified through a series of milling experiments under various cutting conditions.