Fu-Chuan Hsu

Dimension Error in the Presence of Process and Machine Error in End Milling

The contribution of process and machine errors to the dimension error of machined part was investigated in this study. End milling was performed in two different types of machine configuration (XFYZ and XYFZ) in order to evaluate the dimension error caused by process and spatial errors of machine tools. The spatial machine errors were obtained by the sequential diagonal method with the Doppler laser displacement meter. For the process error, a simple average force model for a single cutting point and the identified structure stiffness is used to calculate the force induced surface error along the tool axis direction. Surface error due to tool runout effect is also considered as a contributing factor to the process error. Finally, the prediction model of dimension error for end milling was established by analyzing the machine positioning error and process error. The error prediction model was confirmed by different radial depth of cut and cutting fluid supply parameters. The dimension error of machined part was measured by the coordinate measuring machine. The experimental results reveal that the proposed model is useful in predicting the dimension error in an end milling process.Copyright

A Part Error Model Considering the Machine Tool Positioning Errors and Process-Induced Errors

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.Copyright

Comparison of Relative Contributions of Process and Geometric Errors in Micro and Macro Scale Milling Using an Integrated Error Model

Error models are available for individual error sources for specific components in a machine tool. However, proper error budgeting requires an understanding of the relative importance of various error sources. This paper presents an analysis of the relative contribution of process and geometric errors on the dimensional error produced in micro scale milling. The error contributions at the micro scale are compared and contrasted with those in macro scale milling. The analysis makes use of an error model that uses homogeneous transformation matrices (HTMs) to model the effect of each error source in each component of the machine tool on the final position of the tool with respect to the workpiece. The model is developed for a generic milling machine and used to compare the relative importance of errors due to misalignment, thermal growth, tool deflection and wear of the tool on the size of the machined feature at the micro and macro scale for slot milling using standard length tools.Copyright

A RSS Method for Estimating Hole Dimension Error in a Batch Micro-EDM Process

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.Copyright