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A still current challenge of paramount importance for manufacturing metrology is the industry and laboratories’ increasing demand for faster inspection and verification measuring procedures to determine the conformance of products to dimensional or functional requirements. Within this context, a measuring system group that has gained great importance in the field of high precision dimensional verification are the portable coordinate measuring machines (PCMMs) such as articulated arm coordinate measuring machine (AACMM). Nevertheless, an important drawback of these type of instruments are the time-consuming, tedious, and expensive tasks inherent to their verification and kinematic parameter identification procedures. In this work, a kinematic parameter identification procedure of an AACMM by means of an indexed metrology platform is presented. Moreover, the kinematic modeling of the AACMM is developed, and the optimization of the arm kinematic parameters to minimize the measurement error is carried out in terms of eight objective functions. Finally, a comparison between the optimized parameters and the nominal parameters is discussed, showing the advantages of using the indexed metrology platform (IMP) in the optimization procedure.

This paper presents the results of investigations on the accuracy of contact point identification during coordinate measurement, which is crucial in the context of the Industry 4.0 concept. In particular, the effects of swivel length and probe declination angle during measurement were analyzed. In the experiments, deviations from the expected coordinates (0,0,0) of the contact point were analyzed for different rotational angles of the probing head. It was found that the recommended vertical positioning of the stylus at an angle of A = 0° might have introduced some insignificant errors. Increasing angle A up to 15° generated additional errors of negligible values in comparison with the measurement accuracy of the CMM. However, an increase in angle A up to 90° introduced additional errors as high as 10 μm. This contact point identification error will have a certain effect on the best fitting element and subsequent calculations and on the respective measurement results.

Attaining dimensional accuracy in CNC-machined parts is essential for high-precision manufacturing, especially when working with materials that exhibit varying mechanical and thermal characteristics. This research provides a thorough experimental comparison of manual and automated metrological systems, specifically the Digital Vernier Caliper (DVC) and Coordinate Measuring Machine (CMM), as applied to five different engineering alloys through five progressively machined axial zones. The study assesses absolute error, relative error, standard deviation, and measurement repeatability, factoring in material hardness, thermal conductivity, and surface changes due to machining. The results indicate that DVC performance is significantly affected by operator input and surface irregularities, with standard deviations reaching 0.03333 mm for Bronze C51000 and relative errors surpassing 1.02% in the initial zones. Although DVC occasionally showed lower absolute errors (e.g., 0.206 mm for Aluminum 6061), these advantages were countered by greater uncertainty and poor repeatability. In comparison, CMM demonstrated enhanced precision and consistency across all materials, with standard deviations below 0.0035 mm and relative errors being neatly within the 0.005–0.015% range, even with challenging alloys like Stainless Steel 304. Furthermore, a Principal Component Analysis (PCA) was conducted to identify underlying measurement–property relationships. The PCA highlighted clear groupings based on sensitivity to error in manual versus automated methods, facilitating predictive classification of materials according to their metrological reliability. The introduction of multivariate modeling also establishes a new framework for intelligent metrology selection based on material characteristics and machining responses. These results advocate for using CMM in applications requiring precise tolerances in the aerospace, biomedical, and high-end tooling sectors, while suggesting that DVC can serve as an auxiliary tool for less critical evaluations. This study provides practical recommendations for aligning measurement techniques with Industry 4.0’s needs for accuracy, reliability, and data-driven quality assurance.

The parts with freeform surfaces are extensively employed in the production industries. Consequently, the quality inspection of sculptured surfaces becomes increasingly important. Typically, the Coordinate Measuring Machine (CMM) is utilized for inspection of these irregular geometries because of its precision. Certainly, the complex and non-rotational geometry makes it difficult to obtain the freeform surfaces. The meticulous analysis will indeed require the explicit reconstruction of the measuring surface. In view of the fact that only a well-chosen sample of inspection points and their locations can accurately define the measurand, the development of an appropriate sampling strategy becomes crucial. This work proposes a novel adaptive sampling plan for the precise extraction of surface form. It recursively and adaptively computes the relevant sampling scheme to achieve an effective inspection using the CMM. The input to the algorithm is a random sample size depending on the inspection point spacing and measuring surface dimensions. This algorithm employs a knot vector–based segmentation, followed by curvature-based grading of the segmented patches. A newly established formulation is utilized to assign a specific sample size for each segment. The points within each patch are allocated by exploiting distinct point distribution algorithms. This algorithm intends to abbreviate the variance between the reference and generated surface obtained through the specific sampling plan. Indeed, the befitting sampling policy provides the least error between the two surfaces. The outcome in the present study demonstrates that the proposed algorithm can significantly reduce the inspection points as well as maintain the precision of surface modeling.

Background Quality control (QC) methods for computed tomography (CT) systems used in treatment planning have not been updated since the release of the Task Group (TG) 66 report by the American Association of Physicists in Medicine (AAPM) in 2003. Conventional QC methods for CT systems fail to fulfill the requirements of high‐precision radiation therapy. Moreover, because the geometric accuracy of CT systems can affect the accuracy of radiation therapy, which is particularly critical in high‐precision radiation therapy, a highly accurate QC method is required. Purpose This study aimed to develop a high‐accuracy QC method for CT system couch tops suitable for high‐precision radiation therapy by utilizing a wide‐area three‐dimensional (3D) coordinate measuring machine (3D‐CMM), a type of laser tracker. Methods We used a 3D‐CMM, which includes a wireless probe and a camera unit, focusing on a SOMATOM go.Open Pro CT system. The system was set up in accordance with the reference method outlined in the AAPM TG66 report guidelines. The initial phase verified the accuracy of 3D‐CMM measurement within a CT room using a micrometer. Subsequently, a novel continuous measurement method was developed to enable the real‐time tracking of the couch‐top displacement during travel. This new method was evaluated against the standard manual measurement method. Measurements were performed at 0.1 s intervals at various index positions on the couch top, with and without added weight to simulate the presence of a patient. The gathered data were analyzed to assess the couch‐top displacement, horizontality and orthogonality relative to the imaging plane, providing a comprehensive evaluation of the stability and alignment of the couch top. Results The difference between the micrometer and measured shifts peaked at 0.08 mm. The continuous measurements agreed with the standard measurements within one standard deviation of the three measurements. The maximum displacements of the couch top were 5.23 and 2.00 mm in the vertical axis, with and without a weight load, respectively. There were differences in the displacement at each measurement point. In the lateral axis, the maximum displacements were 2.05 and 2.09 mm with and without a weight load, respectively. The maximum displacement in the imaging plane was observed at approximately half the distance traveled by the couch top. As the couch top traveled, the horizontal angle in the imaging plane of the couch top varied from 0.06° to 0.07° and 0.25° without a weight load and from 0.09° to 0.21° and 0.34° with a weight. The orthogonal angles of the couch top varied from 0.07° to 0.08° and 0.14° without a weight load and from 0.05° to 0.23° and 0.46° with a weight. Conclusions The developed QC method for the couch tops of CT systems can evaluate the displacement of the couch top and its horizontality and orthogonality to the imaging plane with detailed submillimeter and subdegree accuracy levels. The high‐accuracy QC of CT systems can improve the accuracy of irradiation in radiation therapy.

Thin-walled structures are used in many industries. The need to use such elements is dictated by the desire to reduce the weight of the finished product, as well as to reduce its cost. The most common method of machining such elements is the use of milling, which makes it possible to make a product of almost any shape. However, several undesirable phenomena occur during the milling of thin-walled structures. The main phenomenon is a deformation of the thin wall resulting from its reduced stiffness. Therefore, it is necessary to control the dimensional and shape accuracy of finished products, which is carried out using various measuring instruments. The development of newer measuring methods such as optical methods is being observed. One of the newer measuring machines is the 3D optical scanner. In the present experiment, thin-walled samples in horizontal orientation of Ti6Al4V titanium alloy were machined under controlled cutting conditions. During machining, the cutting speed and feed rate were assumed constant, while the input factors were the tool and cutting strategy. This paper presents graphs of deviations in the determined cross-section planes of thin-walled structures using a 3D optical scanner and a coordinate measuring machine. A correlation was made between the results obtained from the measurement by the optical method and those determined by the contact method. A maximum discrepancy of about 8% was observed between the methods used.

In modern manufacturing, there is an increasing demand for reliable in-process measurement methods directly on large CNC machine tools, eliminating the need to transport workpieces to metrological laboratories. This study assesses the capability and applicability of an articulated arm coordinate measuring machine and a machine tool touch-trigger probe when measuring to a specified tolerance of 0.05 mm in a production environment. Experiments were conducted using the KOBA calibration standard and included measurements with and without applying the articulated arm coordinate measuring machine leapfrog method. The results were evaluated according to ISO 22514-7:2021 and ISO 14253-1:2017, which establish criteria for measurement system capability. The findings revealed that neither measurement system met the capability requirements of ISO 22514-7:2021, particularly due to unsatisfactory QMS and CMS values. However, under ISO 14253-1:2017, both systems were deemed conditionally suitable for verifying conformity to the specifications, with the articulated arm coordinate measuring machine showing lower applicability when using the leapfrog method. This research supports the idea that unreasonable demands for compliance with current standards may lead to questioning of the systems that previously met older standards. The study contributes to the ongoing discussion on integrating advanced metrological tools into the manufacturing process and underscores the need for careful evaluation to ensure the capability and reliability of measurement systems in industrial practice.

Coordinate measuring machines (CMMs) are the standard displacement systems used for measurements in dimensional metrology. Since measurement with a touch probe mounted on a CMM provides high accuracy, repeatability, and reliability, it has been widely used for mechanical part inspection in manufacturing. The inspection process requires the use of several sensor orientations and optimal positioning of the part in order to measure all features. Recently, the field of probing path planning has become a huge and active research field. In this paper, various techniques aimed at generating the probe paths for part inspection are reviewed. Multiple issues related to the positioning of the part to maximise accessibility, analysis of probe accessibility to measure all inspection features, optimisation of the measurement sequence, distribution of measurement points, and collision avoidance are mentioned. The common research approaches and potential algorithms in this field are also discussed in this paper.

Coordinate measuring machines (CMMs) are being subjected to an increasing number of intelligent requirements due to mass manufacturing in the industry. It is important to plan the 3D measuring path for a CMM to meet the requirements of multi-objective measurements. A stable and fast three-dimensional (3D) path planning algorithm is desirable to improve the detection efficiency of a CMM. This paper establishes a 3D ant colony map for the measurement space. Then, an improved ant colony algorithm that can converge to the optimal path more rapidly than the standard ant colony algorithm is proposed. Finally, a new path re-optimization algorithm (RE-OP) and the new space collision detection algorithm are proposed. The simulation experiments show that the improved ant colony algorithm can steadily and rapidly obtain the optimal security path and can improve the detection efficiency of CMMs.

Coordinate measuring machines (CMMs) are utilized to acquire coordinate data from manufactured surfaces for inspection reasons. These data are employed to gauge the geometric form errors associated with the surface. An optimization procedure of fitting a substitute surface to the measured points is applied to assess the form error. Since the traditional least-squares approach is susceptible to overestimation, it leads to unreasonable rejections. This paper implements a modified differential evolution (DE) algorithm to estimate the minimum zone femoral head sphericity. In this algorithm, opposition-based learning is considered for population initialization, and an adaptive scheme is enacted for scaling factor and crossover probability. The coefficients of the correlation factor and the uncertainty propagation are also measured so that the result’s uncertainty can be determined. Undoubtedly, the credibility and plausibility of inspection outcomes are strengthened by evaluating measurement uncertainty. Several data sets are used to corroborate the outcome of the DE algorithm. CMM validation shows that the modified DE algorithm can measure sphericity with high precision and consistency. This algorithm allows for an adequate initial solution and adaptability to address a wide range of industrial problems. It ensures a proper balance between exploitation and exploration capabilities. Thus, the suggested methodology, based on the computational results, is feasible for the online deployment of the sphericity evaluation. The adopted DE strategy is simple to use, has few controlling variables, and is computationally less expensive. It guarantees a robust solution and can be used to compute different form errors.