## Materials and Methods
\begin{table}
\begin{tabular}{c c} \hline \hline
**Type** & **Description** \\ \hline \multirow{4}{*}{Size} & In the case of item \#4.0 (\(\mathcal{O}\)40), the hole was machined by slightly modifying the circular path. In the case of items \#5.0 (\(\mathcal{O}\)8), \#7.0 (\(\mathcal{O}\)20) and \#10.0 (\(\mathcal{O}\)14), a drill bit was used for drilling the holes. \\  & For the slab feature (item \#8.0), size defects were created in CATIA® V5 by slightly modifying the distance between the corresponding parallel planes. \\ \hline \multirow{4}{*}{Form} & No flatness and straightness defects were created for plane surfaces (item \#1.0) and cylindrical features. In the case of item \#4.0 (\(\mathcal{O}\)40), cylindricity defects were created while machining the hole by slightly modifying the circular path. \\ \hline \multirow{2}{*}{Orientation} & Orientation defects were created in CATIA® V5 by rotating the plane surfaces (items \#2.0 and \#3.0). \\ \hline \multirow{2}{*}{Location} & Location defects were created in CATIA® V5 by imposing translations and rotations of the axes of cylindrical features (e.g., items \# 4.1, 5.1, 5.2, 7.1, 7.2, 10.1, and 10.2) and slab features (item \#8.1). \\ \hline \multirow{2}{*}{Profile} & Profile defects were created in CATIA® V5 by imposing translations and rotations along the three axes of the surface (items \#9.0 and \#9.1). \\ \cline{1-1}  & For item \#9.2, no profile defects were created. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Creation of the defects (all dimensions are in mm). Figure 3: The proposed GD&T-based artifacts. The measurements were performed from November 2013 to December 2017. Different institutes and industrial partners (eight industries, three schools, and three companies in the field of dimensional metrology) were asked to measure artifacts #2 to #5 without any particular focus. The aim was to analyze the ordinary measurement performance of each institute. Each artifact received a unique code for each partner (only the coordinator maintained the part-operator-equipment traceability). The circulation of the artifacts was arranged in a circular path, with the evaluation kit forwarded to the next participant and the results sent to the coordinator. Each partner carried out measurements with their own CMM system, which included calibrated equipment, specific software, and an appraiser. The data were collected through a dynamic pdf form. In this form, each inspection item was mentioned and the operator was asked to: (1) accept or refuse the item and (2) mention the measured value. An online database was connected to this form for fully automatic and secure data collection. Based on [9,18], the general mathematical model for determining the CMM task-oriented uncertainty is presented in Equation (3):  
\[U_{c}\cong\pm\mathrm{k}\sqrt{u_{E}^{2}+u_{EV}^{2}+u_{AV}^{2}} \tag{3}\]  
where \(u_{E}\) is the uncertainty caused by bias and linearity (the equipment variation as provided by the manufacturers); \(u_{EV}\) is the uncertainty caused by repeatability as defined in MSA [11]; \(u_{AV}\) is the uncertainty caused by reproducibility as defined in MSA [12] (this includes the software used and the measurement strategy); \(U_{c}\) is the expanded combined uncertainty with a coverage factor \(k\) (obtained from Student's critical value table); and \(U_{c}\) represents the total error of the inspection process. Some assumptions were made:  
1. All measurements were done in a controlled environment (metrology laboratory or facilities). Therefore, compared to amplitude defects, uncertainty induced by environmental conditions could be considered negligible in this study. 2. The uncertainty of the equipment (hardware), including the bias, linearity (\(u_{E}\)), and repeatability (\(u_{EV}\)), was much smaller than the amplitude of the induced defects (\(u_{E}\) and \(u_{EV}<<\)_Defect_).