Coordinate Measuring Machine Data Research Articles

A Quality Prediction and Parameter Optimization Approach for Turbine Blade Multistage Manufacturing

As core components of an aircraft engine, turbine blades are featured by complex curved surface with strict precision requirements in multistage manufacturing processes (MMPs). Hence, reliable quality prediction and parameter optimization strategy on MMPs have long been in great demand. However, most techniques focus on the precision improving of single-stage single-product manufacturing systems; these improvements are difficult to implement in MMPs with coordinate transformations among multiple machines. In this article, we propose a noninvasive feature-based quality prediction and parameter optimization framework for high-precision MMPs. In particular, rather than retrofitting sensors onto machinery after installation, this study presents an executable and noninvasive solution by using coordinate measuring machine (CMM) data as input features for prediction. Based on features of different stages of machining, a sequential multistep deep learning architecture is developed to predict the final product quality. A preheating optimization algorithm, modified from a local gradient search method, is used for the optimization of key initial machining features, which results are further improved by the L-BFGS method, thus increasing the final production quality. To estimate the effectiveness of the proposed framework, experiments are carried out on two series of aviation turbine blades with complex curved surfaces from the Wuxi Turbine Blade Company Ltd. China. CMM data at key stages (i.e., blade root milling and comprehensive accurate milling) are used as inputs to predict the final geometrical errors. Comparison results verify that the proposed framework achieves the smallest root mean square error at 0.030 mm and 0.032 mm for two blades, respectively.

Analysis of modern fan manufacturing variations and their links to Jet-engine performance

AbstractEvery manufacturing procedure is subject to tolerance variations. Over the years, a set of key characteristic features (KCF) that can explain the effect of manufacturing variations on the aero-mechanical performance of a fan blade has been devised and monitored to ensure conformality and good performance. The KCFs are derived from a cloud of coordinate measurement machine (CMM) points and are defined on approved engineering drawings for the manufactured part. In this paper, it is demonstrated that some of the traditional, common wisdom KCFs are not adequate to explain the engine performance deviation behaviour on a test bed at the sea-level condition. On the other hand, good correlation is found by analysing a set of engineering parameters drawn from a new inverse-mapping procedure of the CMM data. It is further demonstrated that a deviation measured via CMM or 3D structured light (GOM) data in cold conditions can be translated to a variation in the hot running shape of the blade. Having identified the key blade features, a cheap alternative to modifying the manufacturing procedure is devised to recover the fan performance by optimising its leading-edge shape.

Geometri Uydurma için En İyi Eşlenik Gradyan Yönteminin Tespit Edilmesi

In this study, it is aimed to determine the optimal conjugate gradient (CG) method for the geometry fitting of 2D measured profiles. To this end, the three well-known CG methods such as the Fletcher-Reeves, Polak-Ribiere and Hestenes-Stiefel were employed. For testing those methods performances, the five primitive geometries accommodating circle, square, triangle, ellipse and rectangle were first built with a 3D printer, and then they were scanned with a coordinate measuring machine (CMM) to achieve their 2D profiles. The nonlinear least squares procedure was implemented to minimize the error between those measured data and modeled ones. An iterative line search was utilized for this task. The search direction was calculated using the above-mentioned CG methods. During the geometry fitting process, the number of function evaluations at each iteration were computed and the total number of function evaluations were set to be a performance measure of the CG method in question when it converged. By using these performance measures, the performance and data profiles were created to efficiently determine the optimal CG method. Based on performance profiles, it can be stated that the Fletcher-Reeves and Polak-Ribiere methods are the fastest ones on three test geometries out of five. In addition to that, all the CG methods were able to complete the geometry fitting of 80% of test geometries. On the other hand, by examining the data profiles, it was determined that the Polak-Ribiere and Hestenes-Stiefel methods achieve their maximum capabilities of the completing geometry fitting (i.e., 80%) with much lower number of function evaluations than the Fletcher-Reeves method. Besides, in most geometries, the Polak-Ribiere method outperformed the others, thereby it was determined to be the optimal one for the geometry fitting. As a conclusion, the reported results in this work might help the end-users who study on the CMM data processing to conduct an efficient geometry fitting.

Performance evaluation of a conjugate gradient method considering step length computation techniques in geometry fitting of coordinate measuring machine data

This paper focuses on performance evaluation of Hestenes–Stiefel conjugate gradient (CG) method along with two well-known line search conditions, which are weak Wolfe conditions (WWC) and strong Wolfe conditions (SWC), and a new step length computation algorithm in geometry fitting of five primitive geometries (i.e., circle, square, equilateral triangle, ellipse and rectangle). A coordinate measuring machine (CMM) is used to acquire 2D profiles of these geometries. Total number of function evaluations, when the CG method-step length computation technique combination being used successfully completes the geometry fitting, are considered to be performance criteria of the combination. It has been seen that the step length computation techniques for the line search crucially affect the success and performance of the Hestenes–Stiefel CG method in the geometry fitting. Therefore, they require a special care for optimal computational efficiency in addition to the line search direction.

Performance Analysis of Steepest Descent-Line Search Condition Combinations in Nonlinear Least Squares Fitting of CMM Data

This paper presents a benchmarking study on the steepest descent (SD) method considering three different line search conditions including Backtracking (BC), Armijo-Backtracking (ABC) and Goldstein (GC) in nonlinear least squares fitting of measured data obtained from coordinate measuring machine (CMM). Within this scope, five primitive geometries such as circle, square, rectangle, triangle and ellipse were built via 3D printer. Those geometries were then scanned with CMM to acquire their 2D profiles to be fitted. To find best fitting parameters for each geometry, the nonlinear least squares approach along with the above-mentioned optimization method-line search condition combinations were employed. During the fitting process, the total number of function evaluations, when the combination converges to required tolerance, were used as a performance metric of the combination in question. With those data, the performance and data profiles for each combination were created to be able to carry out a reliable performance evaluation. Based on those profiles, it has been seen that the SD-ABC combination is the fastest one. In addition, it is successful on all the geometries while the others are not. For the second fastest combination, the SD-BC combination stands out. However, its successful rate is only 80%, which means it fails on a geometry. On the other hand, the SD-GC combination takes the last place in this study. All those results have shown that the line search conditions have a great contribution to the success and performance of the optimization algorithm being used. Besides, their performance may differ from problem-to-problem. The end-users should consider these facts to find best optimization method-line search condition combination for their problems.

On-machine measurement of geometrical deviations on a five-axis CNC machining centre

ABSTRACT Measurement of high precision components can be performed on-machine using a suitable measuring system or offline using a Coordinate Measuring Machine (CMM). The former approach is desirable, provided it yields reliable results. This paper presents the on-machine measurement of a high precision cylinder used in unmanned aerial vehicles (UAVs) with a contact-type CMM probe. The same component was measured offline on a CMM. The CMM data were used to verify the geometry fitting algorithms identified for the present work. The fitting algorithms were used for evaluating the required geometric deviations on the component based on on-machine measurement data. These values were compared with their corresponding values obtained from CMM software. The difference in geometric deviations obtained by the two approaches was found to be well under 5%. Hence, the proposed approach can be used for practical purposes.

Stochastic analysis and validation under aleatory and epistemic uncertainties

An uncertainty quantification and validation framework is presented to account for both aleatory and epistemic uncertainties in stochastic simulations of turbine engine components. The spatial variability of the uncertain geometric parameters obtained from coordinate measuring machine data of manufactured parts is represented as aleatory uncertainty. Porosity and defects in the manufactured parts based on micro CT-scanned images are represented as epistemic uncertainty. A stochastic upscaling method and probability box approach are integrated to propagate both the epistemic and aleatory uncertainties from fine models to coarse models to quantify the homogenized elastic modulus uncertainties. The framework is applied for a turbine blade example and validated by modal frequency experiments of the manufactured blade samples. A validation approach, called mean curve validation method, is utilized to effectively compare the p-box of the predictions with the experimental results. The application results show that the proposed framework can significantly reduce the complexity of the engineering problem as well as produce accurate results when both aleatory and epistemic uncertainties exist in the problem.

CMM‐based method for assessing the volume change of retrieved polyethylene cups in MoP total hip replacements

Wear occurring at the bearing surface and the consequent generation of wear debris has been identified as the primary cause of aseptic loosening in metal-on-polyethylene (MoP) hip joint replacements. The accurate estimation of volume change in polyethylene cups due to creep and wear is, therefore, an important step for identifying the cause of failure and improving the longevity of MoP prosthesis. The purposes of this study were to present and apply a co-ordinate measuring machine (CMM)-based method for assessing the volume change of retrieved components due to wear and creep by using a combination of CMM data and a bespoke computer programme. The method was firstly validated against the standard gravimetric technique, and then applied to four retrieved polyethylene cups for wear assessment and analysis. The results show that the volume changes calculated using the present method match well with those assessed through the gravimetric technique. The CMM-based method presented in the study is capable of effectively and reliably determining the volume change and characterising the wear patch of retrieved components from MoP hip joint replacements.

Exploring Registration of Optical, CMM and XCT for Verification of Supplemental Surfaces to Define AM Lattices: Application to Cylindrical and Spherical Surfaces

Abstract The use of lattice structures produced using additive manufacturing (AM) is of great interest to the aerospace and medical industries because of their potential for strength/weight optimization. However, their use is often limited due to challenges in qualification. Recent standards proposed for the definition and verification of lattice structures created using AM attempt to address these gaps. In this work, a lattice component is designed using a repeated unit cell and theoretical supplemental surfaces (TSS), brought forth in ASME Y14.46, are used to define the bounding geometry of the component. Two planes and a sphere are used to define a datum hierarchy that will be used to qualify the component. A measurand is defined by a spherical TSS and is later used to evaluate the quality of datum registration. The component is produced using a laser powder bed fusion process and then measured using focus variation microscopy, X-Ray computed tomography, and a coordinate measuring machine (CMM). The three data sources are then registered using a refined sampling registration based on the CMM points. The effect of CMM data acquisition strategy on the quality of the registration is then examined. Results show that CMM planning based on optical measurements of the component, as opposed to the designed geometry, show significant improvement in the quality of registration. This work highlights the importance of sampling location in tactile measurements of components produced using additive manufacturing and recommends that definition of inspection locations/methods be integrated into the design cycle of AM parts.

360-deg shape measurement system based on three-dimensional orientation target

We present a system for 360-deg shape measurement based on three-dimensional (3-D) orientation target. The measurement system mainly includes a CCD camera, digital light projector, 3-D orientation target, and the measured object. The global coordinates for all chessboard corners of the target are calculated based on close-range photogrammetry, for which the relative orientation between camera stations is discussed in detail. According to the homography matrix between the checkerboard and its image plane, the position and orientation of the measuring camera relative to the target are determined. A dot-matrix structured light is designed and projected onto the measured object surface. In each image of the structured light deformed by the object shape, the pixel coordinates of the dot-centers are accurately calculated by the ellipse-fitting algorithm, and then they are all sorted in the same order by the beads-stringing matching method. In the experiment, the designated front, rear, left, and right surfaces of a reference object are measured, and their separate point clouds are automatically stitched together by the 3-D orientation target. Compared with coordinate measurement machine data, the accuracy of the system is demonstrated; the maximum deviations are +1.257 / − 0.977 mm, and the standard deviation is 0.124 mm.

Assessment and implementation of Global offset compensation method

Nowadays, the demand of tighter tolerance components requires more accurate machine tools with volumetric compensation. In mass production, post-machining inspection of the workpiece on a coordinate measuring machine (CMM) of all or just some control features of the parts provides statistical quality control information for all the parts and the variability of the manufacturing process. The paper explains the precision enhancement of machine tools according to Global offset, including parameter error modeling, identification and compensation. The method is utilizing the part quality CMM data to determine the specific compensation parameters that are used in the machine tool controller to minimize the machine tool errors. The aim of this method is to explain the compensation of multiple sources of errors including those affected by the rigid body behavior and the deformation due to dynamic forces, thermos-mechanical changes and backlash (that are repeatable from part-to-part) in a machine tool. Part deformation due to cutting and/or clamping forces that are repeatable can be also compensated. The 3D weighted least square fit is explained to determine the compensation parameters. It makes compensation easy and convenient using part measurement data. Simple scenarios are used to illustrate the capabilities of the Global offset compensation method based on a very simple part.

Method for Quantitative 3D Evaluation of Defects in CFRP Using Active Lock-in Thermography

To guarantee an economic application of carbon fibre reinforced plastics (CFRP) throughout the entire product life cycle, the long term operational reliability and reparability of the products must be assured. The typical repair process starts with the defect detection and the defect evaluation. Based on the size and position of the defects the mechanical properties are evaluated and the most efficient repair process is selected. Therefore, the accuracy of the defect detection is essential for an economic repair process.One approach to detect defects in CFRP is the active lock-in thermography, which is an imaging non-destructive testing method. The application of image processing algorithms on phase images enables automated defect detection in CFRP components. The determination of the depth position of defects is still a challenge since the phase images contain a superposition of different depth layers.This paper introduces a method to quantitatively evaluate the 3D defect geometry from a stack of thermography images captured with different excitation frequencies. The phase images of blind bore holes are analysed. Digital evaluation criteria, e.g. area, enveloping circle and position, are defined. Algorithms for image correction, feature extraction and image analysis are implemented for automated defect detection.The stack of thermography images captured with different excitation frequencies is used to estimate the defect's depth range. With the given thermal diffusivity and the excitation frequency the depth information is calculated. The results are visualized three-dimensionally. The method is validated by the comparison of the experimental results with calibrated coordinate measuring machine data.

Laser Tracker Kinematic Error Model Formulation and Subsequent Verification under Real Working Conditions

A kinematic model of the Laser Tracker (LT) based on the Denavit-Hartenberg method has been developed. In this model, error matrices have been included with error parameters for linear and rotary joints. The calibration method is based on the measurement of a mesh of reflectors measured by a LT from different positions. Error parameters are calculated knowing that distances between every pair of reflectors is the same regardless the LT position. The absence of nominal data prevents us from knowing the calibration behaviour and its suitability. Although synthetic data tests show a good accuracy improvement, it is not possible to know if this will work with under real working conditions. An experiment has been made to check the calibration procedure. A set of 17 reflectors have been placed on a Coordinate Measuring Machine (CMM) and have been measured by a LT from 5 different positions. Reflector positions have also been measured with the CMM to calculate the initial errors. With LT measurements we calculate the error parameters. LT measurements are recalculated considering the kinematic error model and compared with the CMM measurements to get the residual error. Two errors have been calculated; distances error between reflectors and their position error compared with CMM data.

Accuracy of methods for calculating volumetric wear from coordinate measuring machine data of retrieved metal-on-metal hip joint implants

This study compared the accuracy and sensitivity of several numerical methods employing spherical or plane triangles for calculating the volumetric wear of retrieved metal-on-metal hip joint implants from coordinate measuring machine measurements. Five methods, one using spherical triangles and four using plane triangles to represent the bearing and the best-fit surfaces, were assessed and compared on a perfect hemisphere model and a hemi-ellipsoid model (i.e. unworn models), computer-generated wear models and wear-tested femoral balls, with point spacings of 0.5, 1, 2 and 3 mm. The results showed that the algorithm (Method 1) employing spherical triangles to represent the bearing surface and to scale the mesh to the best-fit surfaces produced adequate accuracy for the wear volume with point spacings of 0.5, 1, 2 and 3 mm. The algorithms (Methods 2-4) using plane triangles to represent the bearing surface and to scale the mesh to the best-fit surface also produced accuracies that were comparable to that with spherical triangles. In contrast, if the bearing surface was represented with a mesh of plane triangles and the best-fit surface was taken as a smooth surface without discretization (Method 5), the algorithm produced much lower accuracy with a point spacing of 0.5 mm than Methods 1-4 with a point spacing of 3 mm.

The use of Raman spectroscopy in the analysis of UHMWPE uni-condylar bearing systems after run on a force and displacement control knee simulators

The complications associated with prosthetic failure and revision surgery still constitute the main clinical problem. The objective of wear evaluation is to determine the wear rate and its dependence on the test conditions. To obtain realistic results, a wear test can be performed to reproduce in vivo working conditions and compare the wear characteristics of various total knee prostheses designs.Two knee wear simulators with different input control mechanisms, displacement and force controlled, were used to assess the wear behavior of ultra-high molecular weight polyethylene uni-condylar knee prostheses. The differences in wear behavior were assessed using a state-of-art coordinate measuring machine; Raman spectroscopy was used to evaluate the possible crystallinity changes on the uni-condylar menisci induced by mechanical stress. These results were compared with available uni-condylar retrievals.Scratches were visible along the anterior-posterior direction emphasizing that the motion was constant during the movements under the displacement control simulation. On the contrary, different kinematics schemes were observed under the force controlled simulation. The structural Raman markers showed a good correlation with the coordinate measuring machine data, and in particular with the depth of the concavity formed upon in vitro testing or in vivo service. With regards to the in vitro tested components, the specimens tested under force controlled simulator, which underwent a higher volumetric loss, showed a higher increase of the amorphous content. At a molecular level, the wear mechanism did not appear significantly different for the three sets of specimens, with the exception of the amorphous content which, upon wear, increased in the in vitro tested components, while decreased in the retrievals.

Effect of probe size and measurement strategies on assessment of freeform profile deviations using coordinate measuring machine

Freeform profiles and surfaces have wider engineering applications. Designers use B-splines, Non-Uniform Rational B-splines, etc. to represent the freeform profiles in CAD, while the manufacturers employ machines with controllers based on approximating functions or splines that can cause deviations in manufactured parts. Deviations also creep in during the manufacturing operations. Therefore the manufactured freeform profiles have to be verified for conformance to design specification. Different points on the profile are probed using a coordinate measuring machine (CMM) and a substitute profile is established from the CMM data for comparison with design profile. The sample points are distributed according to different strategies. In the present work, two new strategies of distributing the points on the basis of curve length and dominant points are proposed considering the geometrical nature of the profiles. Metrological aspects such as probe contact and margins to be provided at the ends have also been included. The results are discussed in terms of form deviation with reference to substitute profile and positional deviation between design and substitute profiles, and compared with results of the strategies suggested in the literature.

An iterative neighborhood search approach for minimum zone circularity evaluation from coordinate measuring machine data

An iterative neighborhood search approach (INSA) was proposed to precisely evaluate the circularity error under minimum zone conditions without directly solving nonlinear equations from coordinate measurement machine (CMM) data. The method starts with calculating the initial location and radius of an initial circular search scope. The location is the center of the circle based on an approximate least-squares method of all measurement data points uniformly sampled around the circle, and the radius is the circularity error value by using the approximate center as the datum center of two concentric circles enclosing all measurement data points. Then the circular search scope was divided according to some concentric circles and radials with some radius and angle step lengths. Intersections of the circles and radials were candidate centers for circularity evaluation under the minimum zone criteria. An optimal center with minimum circularity error value was picked out as a new location of the search scope. The distance from the old location was the radius of the new search scope. Further it was divided and the intersections were evaluated until the optimal solution was met. Some examples in the literature were used to verify the validity of this method. The results are the same as or better than those minimum zone solutions adopted from previous work, and computation time is no more than 0.07 s implementing on an IBM ThinkPad R40 laptop for all examples. The computation and comparison show that the proposed INSA is a precise, fast, convergent and simple approach which solved circularity evaluation problems effectively.

Reduced-Order Model of a Bladed Rotor With Geometric Mistuning

This paper deals with the development of an accurate reduced-order model of a bladed disk with geometric mistuning. The method is based on vibratory modes of various tuned systems and proper orthogonal decomposition of coordinate measurement machine data on blade geometries. Results for an academic rotor are presented to establish the validity of the technique.

Gaussian process method for form error assessment using coordinate measurements

A Gaussian process method for modeling and assessing form errors is presented. The Gaussian process method decomposes a geometric feature into three components: designed geometric form, systematic manufacturing errors and random manufacturing errors. It models the systematic manufacturing errors as a spatial model using a Gaussian correlation function and models the random manufacturing errors as independent identically distributed noises. Based on a handful of coordinate measurements, the Gaussian process model reconstructs the part surface and assesses the form error better than traditional methods. The Gaussian process method also provides an empirical distribution of the form error, allowing engineers to quantify the decision risk on part acceptance. This method works for generic geometric features. The method is implemented on two common features: a straight and a round feature. Simulated datasets as well as actual coordinate measuring machine data are used to demonstrate the improvement achieved by the proposed method over the traditional approaches.

Application of wavelet analysis to BIW assembly quality evaluation

The exact evaluation of Body-in-White (BIW) assembly quality is an important problem in the process control of BIW assembly quality. The Coordinate Measuring Machine (CMM) has been widely used in the BIW assembly industry. The process of BIW assembly is a non stationary time series. Leap, linear and periodical trends are three mean shifts of CMM data. This paper introduces one simple and applicable method to evaluate the BIW assembly quality with CMM data. Wavelet analysis is employed to separate the trend and variation in CMM data. The practical cases analysed by wavelet analysis prove the effectiveness of using variation to evaluate the BIW assembly quality. The data splitting error is estimated with Monte Carlo simulation.