This paper describes a methodology for uncertainty assessment for Coordinate Measuring Machine measurement of complex real work pieces from industry. The study applied two approaches (in scanning mode only) for estimating the measurement uncertainty with the support of Taguchi plan in the experiment containing five factors: scanning speed, sample density, probe configuration, scanning direction, and position of measuring object. In the first approach the uncertainty was estimated by measuring the basic geometric objects (primitives like sphere and torus) representing the decomposition of complex surfaces and in the second one a complex surface was treated as an unknown quantity. Calculated uncertainty Type A for both measurement tasks was in the range from 0.65 μm to 6.47 μm. Evaluation of the uncertainty Type B covered specifications of the machine and standard uncertainties derived from temperature effects. Total u_B component was found to be in order of 0.4 μm. Future research will be directed towards the development and application of simulation methods

This review paper provides a comprehensive overview of selected 3D surface texture parameters defined by ISO 25178-2, with a focus on their metrological aspects in high-resolution measurements using atomic force microscopy (AFM). The parameters Sa, Sz, Sq, Sdq, and Sdr are analyzed in terms of their practical application, sensitivity to measurement conditions, and role in assessing surface functionality. Through a review of the literature and simulations of surface profiles with controlled geometric variations, the study demonstrates how the selected parameters respond to changes in step pitch, step width, slope, and lateral calibration errors. Experimental AFM measurements performed on a certified step height standard further illustrate the impact of calibration on the quality of measurement results. Special emphasis is placed on the importance of evaluating measurement uncertainty. The results confirm the need for rigorous instrument calibration and uncertainty assessment to ensure reliable and comparable surface characterization across different instruments and laboratories.

Experimental research of cutting force components during dry face milling operations are presented in the paper. The study was provided when milling of ductile cast iron alloyed with copper and its austempered ductile iron after the proper austempering process. In the study, virtual instrumentation designed for cutting forces components monitoring was used. During the research, orthogonal cutting forces components versus time were monitored and relationship of cutting forces components versus speed, feed and depth of cut were determined by artificial neural network and response surface methodology. An analysis was made regarding the consistency of the measured cutting forces and the values obtained from the model supported by an artificial neural network for the investigated interval of the cutting regime. Based on the results, an analysis of the feasibility of the application of austempered ductile iron in the industrial sector with the aspect of machinability as well as the application of the models based on artificial intelligence, was given. At the end of the presentation, the influence of the aforementioned cutting regimes on cutting force components is presented as well.