Due to machine tool imprecisions during manufacturing, the actual product cannot be the same as the nominal model. The product’s geometric variations influence the geometrical requirements of functionality and assembly [6, 8]; this remains a problem of industrial performance and plays a major role in the quality and cost of products; hence the need for a reliable strategy to evaluate errors in the final inspection of part quality. Among all the geometric characteristics, the circular characteristic is very common on most parts. Therefore, the measurement and evaluation of circularity with a high degree of accuracy is of utmost importance. Size, form and orientation are the basic descriptors of the geometric quality of the objects. The recent publication of ISO 14405-1: 2016 defines the size as the fundamental geometric descriptor; it described a new set of specification tools for the size of part characteristics that directly apply to the ideal geometry of the component [13]. These tools present new challenges for an inspector using a coordinate metrology system. The study of the influence of form defects on the identification of dimensional and geometrical requirements seems necessary. This paper studies four modifiers ISO 14405-1:2016 (Minimum circumscribed size (GN), Maximum recorded size (GX), least squares size Minimum (GG) and Minimum area (MZ)) will be studied. This paper presents simple and effective algorithms for evaluating the circularity error of a large number of points using four specification modifiers of ISO 14405-1:2016, and a study on the influence of measurement system strategies on different algorithms for the evaluation of these new specifications. An analysis software was developed to compare the sensitivity of different parameters (number of points, noise amplitude and circularity defect) on ISO 14405-1:2016 modifiers.
The ISO GPS and ASME Y14.5 standards have defined dimensional and geometrical tolerance as a way to express the limits of surface part variations with respect to nominal model surfaces. A quality-control process using a measuring device verifies the conformity of the parts to these tolerances. To convert the control measurement points as captured by a device such as a coordinate measurement machine (CMM) or noncontact scan, it is necessary to select the appropriate algorithm (e.g., least square size and maximum inscribed size) and to include the working hypotheses (e.g., treatment of outliers, noise filtering, and missing data). This means that the operator conducting the analysis must decide on which algorithm to use. Through a literature review of current software programs and algorithms, many inaccuracies were found. A benchmark was therefore developed to compare the algorithm performance of three computer-aided inspection (CAI) software programs. From the same point cloud and on the same specifications (requirements and tolerances), three CAI options have been tested with several dimensional and geometrical features.
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