Geometric dimensioning, tolerancing and inspection

The work is part of the research activities performed within the framework of the “Nemesi- New Engineering & Manufacturing Enhanced System Innovation” research and development program. The aim of the research is to evaluate the accuracy and measurement uncertainty characterizing the entire process of the digitized acquisition, scanning and measurement of surface defects on aluminum aircraft fuselage. Additionally, it aims to determine the combinations of the main process parameters that make it less sensitive, and therefore robust, to the effect of disturbing factors, such as technological imperfection and environmental variations. Special attention was put on the study of two specific types of aircraft surface defects: scratches and depressions (dents). For scratches, three different morphological configurations were studied: linear, crossed, and curved scratches. Reference depth measurement of the defects was obtained by using a digital depth micrometer (comparator), an instrument currently certified in the aeronautical field. These values were compared with the outputs measured using the 3D scanner system Atos Q – Zeiss and the related analysis software Gom Inspect Pro. The analysis of the results showed very accurate and reliable defect depth values when compared with the reference depth values obtained from the certified digital micrometer/comparator. Future developments of this research will focus on expanding the range of the analysed defect types, including further surface anomalies and complexities, as well as several materials. With regards to future trends, the integration of machine learning algorithms to enhance the predictive capabilities of defect detection and measurement processes will also be explored.

Keywords: Design of Experiments , Non-contact Reverse Engineering systems , Non-destructive inspection , Quality control , Structured light systems , Surface defects

The lack of a standardized methodology complicates accuracy assessment in computer-assisted mandibular reconstruction. Existing landmark-based methods are susceptible to operator variability, while surface-based comparisons can mask local deviations. This study validates a novel, automated protocol, the Global Positioning Layout (GPL), to quantify the 3D discrepancy between the virtual surgical plan and the postoperative outcome, by comparing its performance and reliability against Methods A and B. A retrospective cohort of 17 patients was analysed, with three operators performing all measurements on two occasions. The GPL method demonstrated complete reproducibility, with no inter- or intra-operator variability, providing a detailed, spatially-oriented assessment of deviations. In contrast, the landmark-based method showed poor reproducibility and systematic bias and was often inapplicable due to the absence of landmarks after resection. The surface-based method, while objective for its mean error metric, was operator-dependent for initial alignment and its non-directional output masked significant localized deviations. This study validates GPL as a robust and fully reproducible tool that overcomes the critical limitations of established techniques. The GPL method provides a strong foundation for a standardized protocol, essential for the reliable comparison of surgical outcomes, refinement of surgical techniques, and improvement of long-term patient outcomes.

Keywords: Accuracy assessment, Validation , Computer-Aided Manufacturing , Mandibular reconstruction, Computer-Aided Design , Prosthesis

Tracking systems are essential in various fields, such as health and manufacturing industries, enabling mapping between the real and digital worlds. Amongst others, Augmented Reality Tracking Systems (ARTS) are more recent and less explored. This work proposes a quantitative metrological methodology to evaluate ARTS tooltip tracking performance, facilitating benchmarking, parameter optimization, and system selection for specific tasks. A specific 3D-printed measuring artifact is proposed to guide tooltip positioning. Tracking accuracy and precision are estimated, highlighting the effects of influence factors. The methodology was tested with two commercial state-of-the-art ARTSs using marker-based tooltips, i.e., a Microsoft HoloLens 2 and a stereo camera system equipped with Intel RealSense SR305 cameras. Metrological characteristics are evaluated, and the Euclidean distance expanded uncertainty at a conventional 95% confidence level is estimated as 5.071mm for the HoloLens 2 and 6.800mm for the stereo system, resulting in a superior metrological performance of HoloLens 2 under the specified conditions. This study provides a standardized approach for quantitatively comparing AR tracking systems, offering valuable insights for optimizing their use in specific applications and, innovatively in the context of ARTS, associates measurement uncertainty with tracked distance values.

Keywords: Augmented reality , Design of experiments , Measurement uncertainty , Metrological characteristics , Tooltip tracking

Digital Image Correlation applied to rotating objects is a challenging task due to the extremely large displacements to be detected and to the rotation of the subsets during revolutions. For these reasons, conventional DIC algorithms are limited to about 7° rotations before losing tracking capabilities. Nevertheless, a full 360° rotation is to be tracked in practical scenarios, so that a new paradigm in optical tracking of rotating objects remains urgent. In this paper, a global DIC algorithm is proposed to overcome the limitations of conventional methods. A simple analytical representation of the roto-translation is proposed, and an optimization algorithm is developed to find the rotation angle and center to minimize the discrepancies between the reference and rotated image. The critical issue of the procedure is represented by the selection of a reliable first guess, which, due to the presence of several local minima and a really sharp global minimum, needs to be extremely accurate for the optimization to converge. To this extent, a robust procedure is proposed based on image unwrapping and spatial-FFT analysis of the unwrapped image to infer a reliable first guess to be fed to the subsequent final optimization process. The approach was validated through experimental analysis of a rotating PC fan.

Keywords: Digital Image Correlation , Image unwrapping , Optical vibration measurements , Rotating DIC

Full-field methods such as Electronic Speckle Pattern Interferometry (ESPI) and Digital Image Correlation (DIC) emerge as promising alternatives to strain rosette in the hole-drilling method, each with its own advantages and limitations. In particular, DIC stands out as a method requiring minimal (and cheap) specimen preparation; however, its sensitivity is approximately one order of magnitude lower than that of conventional strain gauge techniques. We address two fundamental questions. First, how can the inverse problem of the hole-drilling method be systematically approached outside the well-established framework of ASTM E837, which provides users with comprehensive guidance, including automated regularization procedures? Second, thanks to full-field measurement techniques, is it possible to retrieve stress distributions at a spatial resolution finer than the drilling step? We revisit the theoretical development of the inverse problem, aiming to directly identify the residual stresses from raw images, without intermediate pre-processing of the displacement fields. We introduce the L-curve method – well established in other scientific domains – as a rational tool for the choice of the regularization parameter. Finally, we show that, in principle, it would be possible to identify the entire stress distribution from a single drilling increment. We perform a deep rolling treatment on an aluminum specimen and compare the residual stresses identified using both a strain gauge rosette and DIC. We demonstrate that the proposed framework yields results comparable to those obtained using strain gauge rosettes, while minimizing user-dependent arbitrariness. Furthermore, we show that depth super-resolution of at least a factor of two is already achievable with current technological capabilities.

Keywords: Digital image correlation , Full-field , Hole-drilling , Regularization , Residual stress

Digital Image Correlation (DIC) is a widely used non-contact method for full-field displacement measurement under static and dynamic conditions. However, conventional algorithms struggle with large rotations, typically limited to 10-15°, making them unsuitable for rotating objects like wheels, turbines, or gears. Current workarounds involve using databases of static images at various angles to find a suitable reference image, but this approach lacks flexibility. This research presents a global DIC algorithm capable of tracking rotating objects without relying on image databases. A grid of points is defined on the reference image and numerically rotated around a specified center. Bicubic spline interpolation is used to estimate grey levels at non-integer positions in the deformed image. These are compared with reference values to compute an error, minimized through an optimization process based on a Gauss-Newton scheme. The method was validated on experimental images of a rotating PC fan, showing effective tracking for angles up to 90°.

Additive manufacturing (AM) enables customized, efficient restorative workflows, though the accuracy of 3D-printed restorations may be compromised by polymerization, sintering shrinkage, and post-processing. This study evaluated the geometric accuracy of 3D-printed partial restorations compared with the computer-aided design (CAD) reference. The null hypothesis stated that no significant differences would be found between Varseo Smile Crownplus (by BEGO, Italy) and IRIXMax (by DWS System, Italy) materials, which are printed and cured with different technologies. A model was prepared for an overlay and designed with a 1.5 mm uniform thickness. Restorations were produced in two groups with two different printing processes: DLP (digital light processing)-printed Varseo Smile Crownplus and SLA (stereolithography)-printed IRIXMax. Six samples per group were printed at 90° orientation and scanned. Meshes were aligned to the master geometry via pre-alignment and ICP (Iterative Closest Point) registration. Deviations were quantified in CloudCompare using mean, standard deviation (SD), and 90th percentile values. IRIXMax showed the lowest deviations from the ideal geometry, while Varseo Smile Crownplus exhibited greater variability. Pairwise comparisons found IRIXMax significantly more accurate than Varseo Smile Crownplus. Color maps confirmed material-specific deviation patterns. IRIXMax provided the highest geometric accuracy. Material-specific calibration is essential for reliable 3D-printed definitive restorations.

Keywords: 3D printing , dental restorations , deviation analysis geometric accuracy , internal gap , marginal fit , resin-based composites , trueness

This work presents a computational framework for tolerance chain analysis based on multivariate statistical modelling accommodating both prescribed moments and correlations. The proposed method generates multivariate datasets matching either measured or proposed component characteristics, enabling realistic statistical virtual assembly. By using a transformed multi-variate Normal distribution, it is possible to represent the mean, variance, skewness, kurtosis, and covariance structure of the real parts\' geometric variability. This allows tolerance propagation analysis that reflects actual manufacturing variability. Applications include predictive assembly simulations, functional tolerance optimization, and data-driven design verification in industrial contexts.

Keywords: Design optimization , Tolerance Stack-Up with covariance , Tolerancing

This study presents a systematic evaluation of the dimensional accuracy and process capability of fused deposition modeling (FDM) additive manufacturing, with emphasis on the influence of process-induced thermal and kinematic effects on dimensional performance. Two geometries made of polylactic acid (PLA) were considered: a staircase specimen to assess process capability and directional effects, and a geometric benchmark test artifact (GBTA) to evaluate dimensional reliability across representative features. Measurements were performed using a digital caliper for the staircase model and a coordinate measuring machine (CMM) for the GBTA. Under manufacturer-recommended, unoptimized printing conditions, staircase analysis showed that the investigated FDM system achieved process performance indices (Pm and Pmk) ≥ 1.33 at a 95% confidence level. Dimensional stability varied across the build chamber due to spatially nonuniform cooling conditions, with statistically significant position-dependent deviations observed particularly along the build direction. Larger features exhibited higher relative precision. Achievable ISO 286-1 International Tolerance grades ranged from IT9 to IT14. GBTA results confirmed systematic undersizing of cylindrical and curved features. Absolute dimensional deviations remained approximately constant across nominal sizes, whereas percentage errors increased for smaller features due to scale effects. Despite these variations, the geometric form was preserved, demonstrating high repeatability. The proposed capability-based evaluation framework provides a structured approach to quantifying dimensional reliability in polymer-based material extrusion processes for functional components.

Keywords: additive manufacturing , dimensional accuracy , dimensional tolerances , fused deposition modeling , process capability

The escalating demand for miniaturization in electronics necessitates advanced laser micromachining for precise micro-via fabrication in PTFE-based PCBs. This study addresses challenges in controlling CO2 laser kerf depth in PTFE, a material known for properties that complicate material removal. Employing a two-level full factorial Design of Experiments, the effects of number of loops, aperture, and pulse duration were systematically investigated. This analysis revealed that while pulse duration statistically impacted ablation depth, the number of loops was operationally most critical due to its direct proportionality with kerf depth in PTFE, leveraging its low thermal conductivity. Aperture, defining the laser spot size, was often constrained by PCB geometric specifications. The predictive models developed demonstrated robust generalizability across different PTFE-based laminates. Validation of the production of PCBs achieved a 100% success rate in meeting geometric tolerances and surface integrity. This DoE-based framework establishes a process window, significantly reducing parameter identification time and scrap, thereby enhancing manufacturing yield.

Keywords: CO2 laser micromachining , Design of Experiments , kerf depth , PCB , predictive model , process optimization , PTFE

Additive Manufacturing enables the production of complex and customized structures but achieving consistent geometric fidelity and dimensional control remains challenging. Variations in form and feature orientation can compromise functional performance, making it essential to understand how process and material parameters affect geometric deviations and support robust qualification. This research investigates the effects of infill density, scale, and material type on geometric variations in Fused Filament Fabrication parts. Two shapes (prismatic and solid-of-revolution) were designed, with geometric variations grouped by feature orientation (vertical, horizontal, and inclined). The experimental plan considers three infill density levels (25%, 50%, 75%), three scale factors (1:1, 1.5:1, 2:1), and four materials (PET-G, PET-G CF, Nylon, Nylon CF), for a total of 120 samples, whose actual geometries were reconstructed via laser scanning, providing the basis for evaluations of data through numerical analysis. The results revealed that input parameters affect geometric accuracy, negatively impacting inclined features with increasing scale, while improving some horizontal features with increasing infill density. Materials, particularly carbon fiber reinforced, help reduce deviations, particularly in vertical geometric features. The study emphasizes the importance of selecting appropriate input variable settings and material types to achieve the desired accuracy, providing a tolerance catalogue within a specified range for designers and engineers to define tolerances for 3D-printed parts.

Keywords: Experimental plan , Fiber reinforced polymers , Fused filament fabrication , Geometric dimensioning and tolerancing , Tolerance catalogue

This study investigates the origin of distortion during sintering of 316 L stainless steel components produced by binder jetting, focusing on friction between the sample and the support surface and on density inhomogeneity in the green state. A design of experiments (DoE) approach evaluates the influence of key printing parameters on the sintering behavior of two geometries with different through-hole sizes. Dimensional measurements, and density profiling, are performed in both green and sintered states. Sintering simulations use the Skorokhod-Olevsky viscous sintering (SOVS) model and include experimentally measured density gradients and frictional effects. Results show that green density varies significantly (52% to 58%) depending on printing parameters, especially binder saturation, and exhibits directional dependence. These variations lead to measurable distortions during sintering. Simulations that include both friction and density gradients match experimental deformations with deviations below 4%. A compensation strategy that places parts on co-sintered 316 L support plates with interposed refractory particles reduces distortion to <1.5%. This work demonstrates the combined role of friction and density gradients in sintering distortion and presents a practical method to improve dimensional accuracy in binder jetting.

Keywords: Additive manufacturing , Dimensional accuracy and precision , Distortion , friction , Metal binder jetting , Shrinkage on sintering

This paper addresses the crucial aspect of position error modeling and compensation in industrial servomechanisms with the aim to achieve accurate control and high-performance operation in industrial robots and automated production systems. The inherent complexity and nonlinear behavior of these modules, usually consisting of a servomotor and a speed reducer, often challenge traditional analytical modeling approaches. In response, the study extensively explores the design and implementation of Machine Learning (ML) algorithms to obtain a comprehensive model of the Transmission Error (TE) in rotating vector reducers, which is a main source of robot motion accuracy errors. The ML models are trained with experimental data obtained from a special purpose test rig, where the reducer is tested under different combinations of input speed, applied load and oil temperature. In the second part of the work, the resulting predictive model, tailored to capture the intricate dynamics of the analyzed reducer, is imported into a programmable logic controller to enable online compensation strategies during the execution of custom motion profiles. Experimental tests are conducted using two distinct motion profiles: one generated with a cycloidal law, typical of industrial machinery, and the other extrapolated from the joints of an industrial robot during a pick-and-place task. The results demonstrate the effectiveness of the proposed approach, enabling accurate prediction and substantial reductions (over 90%) in the overall reducer TE through the implemented predictive model.

Keywords: Compensation approach , Machine learning , Predictive modeling , Servomechanism , Test rig , Transmission error

Background and objective: Accurately measuring cervical vertebrae dimensions is crucial for diagnosing conditions, planning surgeries, and studying morphological variations related to gender, age, and ethnicity. However, traditional manual measurement methods, due to their labour-intensive nature, time-consuming process, and susceptibility to operator variability, often fall short in providing the objectivity required for reliable measurements. This study addresses these limitations by introducing a novel computer-based method for automatically identifying the dimensional features of human cervical vertebrae, leveraging 3D geometric models obtained from CT or 3D scanning. Methods: The proposed approach involves defining a local coordinate system and establishing a set of rules and parameters to evaluate the typical dimensional features of the vertebral body, foramen, and spinous process in the sagittal and coronal planes of the high-density point cloud of the cervical vertebra model. This system provides a consistent measurement reference frame, improving the method's reliability and objectivity. Based on this reference system, the method automates the traditional standard protocol, typically performed manually by radiologists, through an algorithmic approach. Results: The performance of the computer-based method was compared with the traditional manual approach using a dataset of nine complete cervical tracts. Manual measurements were conducted following a defined protocol. The manual method demonstrated poor repeatability and reproducibility, with substantial differences between the minimum and maximum values for the measured features in intra- and inter-operator evaluations. In contrast, the measurements obtained with the proposed computer-based method were consistent and repeatable. Conclusions: The proposed computer-based method provides a more reliable and objective approach for measuring the dimensional features of cervical vertebrae. It establishes a procedural standard for deducing the morphological characteristics of cervical vertebrae, with significant implications for clinical applications, such as surgical planning and diagnosis, as well as for forensic anthropology and spinal anatomy research. Further refinement and validation of the algorithmic rules and investigations into the influence of morphological abnormalities are necessary to improve the method's accuracy.

Keywords: Biomedical engineering , Cervical vertebrae , CT measures standardization

Quality control is considered one of the most important tasks by manufacturing industries, as being able to guarantee certain quality levels is necessary in order to meet customer expectations, reduce waste and costs. Requiring an inspection for each of the products manufactured, being able to have a tool capable of automating the detection of possible defects would simplify this procedure, making it faster and more optimised. This is the specific case of the company Esaote, which carries out accurate quality control for each of its ultrasound probes. In particular, concerning the inspection of the shell, that is currently carried out manually by the staff. To create a tool capable of automating this inspection, a defect detection algorithm based on machine learning is proposed. The algorithm processes the images according to a patch-based strategy, following three steps: splits the image in patches, classifies and localizes the defects in the patches, and finally combines the results to obtain the complete list of all the defects present. Performance was analysed for different configurations related to the three steps, with particular emphasis on the percentage of overlap between patches, the total number of patches to be analysed, and the voting algorithm used to combine results between several patches. The best configuration identified an accuracy of 83.63%, an f-score of 89.87%, a precision of 81.60%, a recall of 88.97%, an AP of 77.63% and finally an AUC of 83.48%.

Keywords: Artificial Intelligence , Computer vision , Convolutional neural network , Image Processing , Visual inspection

Digital workflows have revolutionized dentistry, especially when it comes to fabrication of complete dentures through Computer-Aided Design and Computer-Aided Manufacturing (CAD-CAM) procedures. Digital articulators manage to simulate mandibular movements and are emerging as alternatives to mechanical articulators like the Gerber semi-adjustable model. Despite being a promising tool, digital articulators require refinement in order to grant consistent functionality and effective occlusal balance. The aim of this research is to present a semi-automated MATLAB tool designed to compare trajectories from different articulator types—digital versus analog—used in dental practice. Validation of the MATLAB tool compared to existing data demonstrates its reliability and effectiveness. Sensitivity analyses assess the tool's robustness under various settings. Results suggest optimal input parameters and settings ensuring precision. Future developments may include integrating anatomically-based reference systems and advanced metrics for rotational analysis of condylar path elements (CPEs), thereby enhancing digital dentistry potentialities. Ultimately, the semi-automated MATLAB tool represents a significant step towards improving dental occlusal analysis, bridging the gap between analog and digital methodologies and enabling comparison among these tools.

Keywords: Complete dentures , Dental articulators , Intermaxillary record , Kinematic comparison , Pathway reconstruction

Purpose: This paper aims to present a methodology for evaluating the path accuracy of industrial robots using the telescoping ballbar measurement technology. The goal is to improve accuracy assessments in precision-driven manufacturing processes. Design/methodology/approach: A single telescoping ballbar is used to assess the circle contouring performance of a KUKA KR210 R2700 prime robot. Experiments involve system setup, data collection and analysis in Matlab to derive performance metrics such as radial deviation, circularity and path accuracy error. This study investigates the impact of varying the operational conditions, including speed, payload and robot configuration, on these indexes through statistical analysis, and examines the relationship between joint errors and path deviations. Findings: The results indicate that the robot behavior is influenced by the operating conditions, with notable error spikes at joint reversal positions due to factors such as joint backlash and transmission errors. This study evaluates various performance indexes from different standards, ISO 230 and ISO 9283, and identifies key operating parameters influencing each index. The findings suggest effective strategies for error compensation and performance enhancement. Originality/value: This paper offers a novel approach to path accuracy verification and error source identification in industrial robots. It proposes methods to rapidly assess the correlation between performance and operating conditions, offering insights for better calibration and control strategies, especially in high-precision tasks.

Keywords: Backlash , Ballbar , Experimental assessment , Industrial robots , Path accuracy

The Geometric Product Specification (GPS) and Geometric Dimensioning and Tolerancing (GD&T) languages are the most powerful tools available for linking an ideal design to imperfectly manufactured parts that are never assembled with absolute accuracy. In the design of mechanical systems, the GPS and GD&T methods provide a symbolic language that allows for the complete, clear, and unambiguous definition of permissible variations from ideal geometries to ensure functionality and assemblability. This study proposes a methodology for assigning functional tolerances for the manufacture and assembly of hinges with pins supported by close-range bushings. A test machine was developed to measure the resistant torque in these types of hinges and an easy experimental procedure was used to measure and verify the cylindricity tolerance of the hinge bushings. This allowed a Design for Tolerancing (DfT) approach based on a correlation between the resistant torque values and dimensional and geometric errors. The proposed approach proved to be effective in establishing a relationship between shape, position and orientation errors and the functionality of the hinge.

Keywords: Design for Tolerancing (DfT) , Dimensional Management (DM) , Functional assembly design , Geometric Dimensioning and Tolerancing (GD&T) , Resistant torque

Considering the importance of the recent renewed interest in geometric specification management in industry and academia, along with the evolving landscape of educational models post-COVID-19, the authors aimed to investigate, through a literature review, the status of educational practices on these topics. In particular, the presence of educational initiatives dedicated to geometric and functional product specifications in mechanical or industrial engineering programs was investigated, with a specific focus on standards such as ISO GPS and ASME GD&T outside the Italian context. An analysis was then conducted to identify common teaching strategies and the development of specific tools to improve the understanding of these complex topics. The review of education and training experiences revealed significant trends and insights for future training efforts. In particular, the prevalence of active learning practices emerged, and detailed course descriptions demonstrate the effectiveness of hands-on approaches, often supplemented by specific tools, in facilitating student understanding.

Keywords: Active Learning , Engineering Education , GD&T , ISO GPS , Technical Drawing

In many areas of engineering, there is a growing need for accuracy and reliability of assembled systems. To ensure this accuracy, and to ensure the correct function of the part within the assembly, both dimensional and geometric tolerances must be correctly set at the design stage. An important tool, now irreplaceable in any CAD software, is the Geometric dimensioning and tolerancing (GD&T) control, which through algorithms can assign geometric and dimensional tolerances. In this manuscript authors present an original procedure for measuring and verifying the cylindricity tolerance of hinge bushings. A millesimal bore gauges was used to measure the internal diameter at different angular positions in each bushings' sections. Starting from these measurements, the cylindricity of the inner surface of the bushing is evaluated through the least square cylinder (LSC) method. The angular deviation of the bushing axis is then evaluated based on the cylindricity assessment. The procedure allows to easily check, during assembly operations, whether the objects to be assembled are within tolerance without the need to resort to the most expensive and complex procedure through Coordinate Measuring Machines (CMM). Operation could be carried out on an assembly line by an operator using a pre-set spreadsheet.

Keywords: Angularity , Automotive Hinge , Circularity , Coaxiality , Cylindricity , Dimensions and Geometric Tolerances , Friction torque