Interlaboratory Empirical Reproducibility Study Based on a GD&T Benchmark

The ASME Y14.5 geometric dimensioning and tolerancing (GD&T) and ISO-GPS (geometrical product specifications) standards define tolerances that can be added to components to achieve the necessary functionality and performance. The zone that each feature must lie within is defined in each tolerance. Measurement processes, including planning, programming, data collection (with contact or without contact), and data processing, check the compliance of the part with these specifications (tolerances). Over the last two decades, many works have been realized by the metrology community to investigate the accuracy, the measuring methods, and, specifically, the measurement errors of fixed and portable coordinate measuring machines (CMMs). A review of the literature showed the progression of CMMs in terms of accuracy and repeatability. However, discrepancies were observed between measurements using different CMMs or operators. This paper proposed a GD&T-based benchmark for the evaluation of the performance of different CMM operators in computer-aided inspection (CAI), considering different criteria related to the dimensional and geometrical features. An artifact was designed using basic geometries (cylinder and plane) and free-form surfaces. The results obtained from the interlaboratory comparison study showed significant performance variability for complex GD&T, such as in the composite profile and localization. This, in turn, emphasized the importance of GD&T training and certification in order to ensure a uniform understanding among different operators, combined with a fully automated inspection code generator for GD&T purposes.

Reproducibility Experimentation among Computer-Aided Inspection Software from a Single Point Cloud

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.

Computer-Aided Inspection Planning: A Multisensor High-Level Inspection Planning Strategy

Computer-aided inspection planning (CAIP) has gained significant research attention in the last years. So far, most CAIP systems have focused on the use of a touch probe mounted on a coordinate measuring machine (CMM). This article investigates multisensor measurement aiming to perform automatic and efficient inspection plans. High-level inspection planning, which deals with sequencing of measuring operations, is the main concern of inspection planning. This paper presents an automatic approach to generate inspection sequences by combining laser sensor and touch probe, and by giving preference to the measurement using the laser sensor if quality requirements are satisfied. The proposed approach consists of three steps. In the first step, recognition of inspection data from the computer-aided design (CAD) part model is carried out based on the concept of inspection feature (IF), and the extracted information is stored in a database. In the second step, a list of privileged scanner orientations is proposed by analyzing the accessibility of both sensors. In the third step, a sequence of operations is generated iteratively. For a given scanner orientation, the ability of the laser sensor is assessed according to an original process based on fuzzy logic model. If the laser sensor does not meet the ability requirements, touch probe ability is assessed. The proposed approach is implemented and tested on a part defined by its CAD model and specifications.

Assessment of the Robustness of a Fixtureless Inspection Method for Nonrigid Parts Based on a Verification and Validation Approach

The increasing practical use of computer-aided inspection (CAI) methods requires assessment of their robustness in different contexts. This can be done by quantitatively comparing estimated CAI results with actual measurements. The objective is comparing the magnitude and dimensions of defects as estimated by CAI with those of the nominal defects. This assessment is referred to as setting up a validation metric. In this work, a new validation metric is proposed in the case of a fixtureless inspection method for nonrigid parts. It is based on using a nonparametric statistical hypothesis test, namely the Kolmogorov–Smirnov (K–S) test. This metric is applied to an automatic fixtureless CAI method for nonrigid parts developed by our team. This fixtureless CAI method is based on calculating and filtering sample points that are used in a finite element nonrigid registration (FENR). Robustness of our CAI method is validated for the assessment of maximum amplitude, area, and distance distribution of defects. Typical parts from the aerospace industry are used for this validation and various levels of synthetic measurement noise are added to the scanned point cloud of these parts to assess the effect of noise on inspection results.

CAD-basierter Workflow für den semi-automatischen Entwurf optischer Inspektionssysteme

ZusammenfassungWährend Computer-assistierte Inspektionsplanung (Computer Aided Inspection Planning, CAIP) für mechanische Inspektionsaufgaben Stand der Technik ist, findet sie im Bereich von Entwurf und Umsetzung von Systemen der industriellen Bildverarbeitung (IBV) noch keine breite Anwendung. Dieser Beitrag stellt ein Konzept und die beispielhafte Implementierung vor, wie durch Anreicherung von STEP-CAD-Daten mit Oberflächeneigenschaften von Bauteilen und der Einbettung von Toleranzangaben die Ausgangsbasis für eine semi-automatische Erstellung und Optimierung von Konfigurationsvorschlägen für Bildverarbeitungssysteme in Interaktion mit einem Systemexperten erreicht wird.