The paper presents the problem of assessing the accuracy of reconstructing free-form surfaces in the CMM/CAD/CAM/CNC systems. The system structure comprises a coordinate measuring machine (CMM) PMM 12106 equipped with a contact scanning probe, a 3-axis Arrow 500 Vertical Machining Center, QUINDOS software and Catia software. For the purpose of surface digitalization, a radius correction algorithm was developed. The surface reconstructing errors for the presented system were assessed and analysed with respect to offset points. The accuracy assessment exhibit error values in the reconstruction of a free-form surface in a range of ± 0.02 mm, which, as it is shown by the analysis, result from a systematic error.
This paper concerns the issues of measurement techniques, analysis and assessment of the machined surface geometric structure. The aim of this work was to show the application of surface analysis in diagnosing the causes of discrepancies occurring in the manufacturing process, which may result from ill-matched (poorly fitting) process parameters. An appropriate system of control and interpretation of results may allow early reaction to unfavorable trends (for example blunting of the tool) and prevention of undesirable defects. The subject of research was a waste basket used in the construction of retaining sewer systems. In this paper, the quality of the waste basket as well as its manufacturing process were analyzed and assessed. The research was carried out with the use of three measurement stands, i.e. optical microscopy (OM), scanning electron microscopy (SEM) and white light interferometer (WLI). The surface analysis proved to be important from the viewpoint of outlining the production process as well as improving the product quality. The software used for topographical analysis appeared to be significant for the success of the analysis, providing notable economic effects, namely the lack of defects.
The paper provides statistical analysis of the photographs of four various granular materials (peas, pellets, triticale, wood chips). For analysis, the (parametric) ANOVA and the (nonparametric) Kruskal-Wallis tests were applied. Additionally, the (parametric) two-sample t-test and (non-parametric) Wilcoxon Rank-Sum Test for pairwise comparisons were performed. In each case, the Bonferroni correction was used. The analysis shows a statistical evidence of the presence of differences between the respective average discrete pixel intensity distributions (PID), induced by the histograms in each group of photos, which cannot be explained only by the existing differences among single granules of different materials. The proposed approach may contribute to the development of a fast inspection method for comparison and discrimination of granular materials differing from the reference material, in the production process.