Abstract: Prediction of machining process capability in the design stage plays a key role to reach the precision design and manufacturing of mechanical products. Inaccuracies in machining process lead to errors in position and orientation of machined features on the part, and strongly affect the process capability in the final quality of the product. In this paper, an efficient systematic approach is given to investigate the machining errors to predict the manufacturing errors of the parts and capability prediction of corresponding machining processes. A mathematical formulation of fixture locators modeling is presented to establish the relationship between the part errors and the related sources. Based on this method, the final machining errors of the part can be accurately estimated by relating them to the combined dimensional and geometric tolerances of the workpiece – fixture system. This method is developed for uncertainty analysis based on the Worst Case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the Monte Carlo simulation results.
Abstract: Manufacturing tolerancing is intended to determine
the intermediate geometrical and dimensional states of the part
during its manufacturing process. These manufacturing dimensions
also serve to satisfy not only the functional requirements given in
the definition drawing, but also the manufacturing constraints, for
example geometrical defects of the machine, vibration and the
wear of the cutting tool. In this paper, an experimental study on the
influence of the wear of the cutting tool (systematic dispersions) is
explored. This study was carried out on three stages .The first stage
allows machining without elimination of dispersions (random,
systematic) so the tolerances of manufacture according to total
dispersions. In the second stage, the results of the first stage are
filtered in such way to obtain the tolerances according to random
dispersions. Finally, from the two previous stages, the systematic
dispersions are generated. The objective of this study is to model
by the least squares method the error of manufacture based on
systematic dispersion. Finally, an approach of optimization of the
manufacturing tolerances was developed for machining on a CNC
machine tool