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The lack of geometric and dimensional accuracy of parts produced by additive manufacturing (AM) is directly related to the machine, material and process used. This paper aims to propose a method for the analysis and compensation of machine-related geometric errors applicable to any AM machine, regardless of the manufacturing process and technology used.

For this purpose, an error calculation model inspired by those used in computerized numerical control machines and coordinate measuring machines was developed. The error functions of the model were determined from the position deviations of a set of virtual points that are not sensitive to material and process errors. These points were obtained from the measurement of an ad hoc designed and manufactured master artefact. To validate the model, off-line compensation was applied to both the original designed artefact and an example part.

The geometric deviations in both cases were significantly smaller than those found before applying the geometric compensation. Dimensional enhancements were also achieved on the example part by using a correction parameter available in the three-dimensional printing software, whose value was adjusted from the measurement of the geometrically compensated master artefact.

The errors that persist in the part derive from both material and process. Compensation for these type of errors requires a detailed analysis of the influencing parameters, which will be the subject of future research.

The use of the virtual-point-based error model increases the quality of additively manufactured parts and can be used in any AM system.

The purpose of this paper is to propose a method for selecting the position and attitude trajectory of error measurement to improve the kinematic calibration efficiency of a one translational and two rotational (1T2R) parallel power head and to improve the error compensation effect by improving the properties of the error identification matrix.

First, a general mapping model between the endpoint synthesis error is established and each geometric error source. Second, a model for optimizing the position and attitude trajectory of error measurement based on sensitivity analysis results is proposed, providing a basis for optimizing the error measurement trajectory of the mechanism in the working space. Finally, distance error measurement information and principal component analysis (PCA) ideas are used to construct an error identification matrix. The robustness and compensation effect of the identification algorithm were verified by simulation and through experiments.

Through sensitivity analysis, it is found that the distribution of the sensitivity coefficient of each error source in the plane of the workspace can approximately represent its distribution in the workspace, and when the end of the mechanism moves in a circle with a large nutation angle, the comprehensive influence coefficient of each sensitivity is the largest. Residual analysis shows that the robustness of the identification algorithm with the idea of PCA is improved. Through experiments, it is found that the compensation effect is improved.

A model for optimizing the position and attitude trajectory of error measurement is proposed, which can effectively improve the error measurement efficiency of the 1T2R parallel mechanism. In addition, the PCA idea is introduced. A least-squares PCA error identification algorithm that improves the robustness of the identification algorithm by improving the property of the identification matrix is proposed, and the compensation effect is improved. This method has been verified by experiments on 1T2R parallel mechanism and can be extended to other similar parallel mechanisms.

Both geometric and non-geometric parameters have noticeable influence on the absolute positional accuracy of 6-dof articulated industrial robot. This paper aims to enhance it and improve the applicability in the field of flexible assembling processing and parts fabrication by developing a more practical parameter identification model.

The model is developed by considering both geometric parameters and joint stiffness; geometric parameters contain 27 parameters and the parallelism problem between axes 2 and 3 is involved by introducing a new parameter. The joint stiffness, as the non-geometric parameter considered in this paper, is considered by regarding the industrial robot as a rigid linkage and flexible joint model and adds six parameters. The model is formulated as the form of error via linearization.

The performance of the proposed model is validated by an experiment which is developed on KUKA KR500-3 robot. An experiment is implemented by measuring 20 positions in the work space of this robot, obtaining least-square solution of measured positions by the software MATLAB and comparing the result with the solution without considering joint stiffness. It illustrates that the identification model considering both joint stiffness and geometric parameters can modify the theoretical position of robots more accurately, where the error is within 0.5 mm in this case, and the volatility is also reduced.

A new parameter identification model is proposed and verified. According to the experimental result, the absolute positional accuracy can be remarkably enhanced and the stability of the results can be improved, which provide more accurate parameter identification for calibration and further application.

Localization accuracy is a key concern in the design of a fixture to specify a locating scheme and tolerance allocation. This paper presents an analysis describing the impact of localization source errors on the potential datum‐related geometric errors of machined features. The analysis reveals the error sensitivity and error characteristics of critical points of multiple manufacturing features. It shows the importance to consider the overall error among the multiple critical points in fixture layout design. This paper also suggests an optimal approach to the locator configuration design for reducing geometric variations at the critical points of machined features.

The purpose of this study is to improve the position and posture accuracy of posture alignment mechanism. The automatic drilling and riveting machine is an important equipment for aircraft assembly. The alignment accuracy of position and posture of the bracket type posture alignment mechanism has a great influence on the operation effect of the machine. Therefore, it is necessary to carry out the kinematic calibration.

Based on analysis of elastic deformation of the bracket and geometric errors of the posture alignment mechanism, an improved method of kinematic calibration was proposed. The position and posture errors of bracket caused by geometric errors were separated from those caused by gravity. The method of reduction of dimensions was applied to deal with the error coefficient matrix in error identification, and it did not change the coefficient of the error terms. The target position and its posture were corrected to improve the error compensation accuracy. Furthermore, numerical simulation and experimental verification were carried out.

The simulation and experimental results show that considering the influence of the elastic deformation of the bracket on the calibration effect, the error identification accuracy and compensation accuracy can be improved. The maximum value of position error is reduced from 5.33 mm to 1.60 × 10⁻¹ mm and the maximum value of posture error is reduced from 1.07 × 10⁻³ rad to 6.02 × 10⁻⁴ rad, which is superior to the accuracy without considering the gravity factor.

This paper presents a calibration method considering the effects of geometric errors and gravity. By separating position and posture errors caused by different factors and correcting the target position and its posture, the results of the calibration method are greatly improved. The proposed method might be applied to any parallel mechanism based on the positioner.

The purpose of this paper is to model how geometric errors of a machined surface (or manufacturing errors) are related to locators’ error, workpiece form error and machine tool volumetric error. A kinematic model is presented that puts into relationship the locator error, the workpiece form deviations and the machine tool volumetric error.

The paper presents a general and systematic approach for geometric error modelling in drilling because of the geometric errors of locators positioning, of workpiece datum surface and of machine tool. The model can be implemented in four steps: (1) calculation of the deviation in the workpiece reference frame because of deviations of locator positions; (2) evaluation of the deviation in the workpiece reference frame owing to form deviations in the datum surfaces of the workpiece; (3) formulation of the volumetric error of the machine tool; and (4) combination of those three models.

The advantage of this approach lies in that it enables the source errors affecting the drilling accuracy to be explicitly separated, thereby providing designers and/or field engineers with an informative guideline for accuracy improvement through suitable measures, i.e. component tolerancing in design, machining and so on. Two typical drilling operations are taken as examples to illustrate the generality and effectiveness of this approach.

Some source errors, such as the dynamic behaviour of the machine tool, are not taken into consideration, which will be modelled in practical applications.

The proposed kinematic model may be set by means of experimental tests, concerning the industrial specific application, to identify the values of the model parameters, such as standard deviation of the machine tool axes positioning and rotational errors. Then, it may be easily used to foresee the location deviation of a single or a pattern of holes.

The approaches present in the literature aim to model only one or at most two sources of machining error, such as fixturing, machine tool or workpiece datum. This paper goes beyond the state of the art because it considers the locator errors together with the form deviation on the datum surface into contact with the locators and, then, the volumetric error of the machine tool.

This paper develops the statistical error analysis model for assembling, to derive measures of controlling the geometric variations in assembly with multiple assembly stations, and to provide a statistical tolerance prediction/distribution toolkit integrated with CAD system for responding quickly to market opportunities with reduced manufacturing costs and improved quality. First the homogeneous transformation is used to describe the location and orientation of assembly features, parts and other related surfaces. The desired location and orientation, and the related fixturing configuration (including locator position and orientation) are automatically extracted from CAD models. The location and orientation errors are represented with differential transformations. The statistical error prediction model is formulated and the related algorithms integrated with the CAD system so that the complex geometric information can be directly accessed. In the prediction model, the manufacturing process (joining) error, induced by heat deformation in welding, is taken into account.

This paper aims to provide an experimental evaluation of geometric errors on the edges of parts manufactured by the fused deposition modeling (FDM) process.

An experimental plan was conducted by building parts in ABS thermoplastic resin on a commercially available machine with given combinations of the three geometric variables (inclination, included and incidence angle) defined in the first part of the paper. Edges on built parts were inspected on a two-dimensional non-contact profilometer to measure position and form errors.

The analysis of measurement results revealed that the edge-related variables have significant influences on the geometric errors. The interpretation of error variations with respect to the different angles confirmed the actual occurrence of the previously discussed error causes. As an additional result, quantitative predictions of the errors were provided as a function of angle values.

The experimental results refer to fixed process settings (material, FDM machine, layer thickness, build parameters, scan strategies).

The two-part paper is apparently the first to have studied the edges of additively manufactured parts with respect to geometric accuracy, a widely studied topic for surface features.

The purpose of this paper is to develop a means of the kinematic calibration of a parallel manipulator with full-circle rotation.

An error-mapping model based on the space vector chain is formulated and parameter identification is proposed based on double ball-bar (DBB) measurements. The measurement trajectory is determined by the motion characteristics of this mechanism and whether the error sources can be identified. Error compensation is proposed by modifying the inputs, and a two-step kinematic calibration method is implemented.

The simulation and experiment results show that this kinematic calibration method is effective. The DBB length errors and the position errors in the end-effector of the parallel manipulator with full-circle rotation are greatly reduced after error compensation.

By establishing the mapping relationship between measured error data and geometric error sources, the error parameters of this mechanism are identified; thus, the pose errors are unnecessary to be measured directly. The effectiveness of the kinematic calibration method is verified by computer simulation and experiment. This proposed calibration method can help the novel parallel manipulator with full-circle rotation and other similar parallel mechanisms to improve their accuracy.

Geometric structure error of parabolic trough concentrator (PTC) frame affects the installation accuracy of mirrors and absorber tubes and thus decreases the solar energy concentrating efficiency. Until now, there is no effective method to instruct the assembly and regulation of PTC frames. This paper aims to propose a vision guided method for fast and accurate regulation of mirror and absorber supports to improve the geometric quality of PTC frames.

The PTC frame support regulating system consists of a general-purpose online photogrammetry system, frame support measurement adaptors and data analyzing software. First, the positions and angles of all the supports are measured in real time by the online photogrammetric system. Then, the measured positions and angles are aligned to the design reference frame through the transformation calculated by an absorber position constrained nonlinear optimization so as to get the geometric errors and regulating amounts. Finally, a graduated pseudo-color-based visualization method is proposed to assist the manual or automated regulation of PTC frame supports in site.

The proposed method does not need to construct a reference system nor specify the rotation attitude of the PTC frame, and it is capable of conducting efficient and accurate regulation on PTC frame assembly line. The method is applied to manual regulation of a light type PTC frame structure. After regulation, the maximum position and angle errors of supports are reduced to less than 0.15 mm and 0.15° respectively and the intercept factor is increased to 97%, which meets the requirement for a qualified PTC concentrator.

To the authors’ knowledge, this paper is the first to propose a vision guided assembly or regulation method for PTC frame structures. The research uses online photogrammetry system to provide real-time geometric quality information feedback, elaborates the data analysis algorithm and provides the visualization method for accurate and efficient in site regulation. Furthermore, this paper also provides theories, methods and experiences for other applications that use vision guidance for attitude regulation and digital flexible assembly of large equipment.