CAD/Tolerancing integration: Mechanical assembly with form defects

Jbira, Ibtissem; Tlija, Mehdi; Louhichi, Borhen; Tahan, Antoine

doi:10.1016/j.advengsoft.2017.07.010

Cited by 28 publications

(13 citation statements)

References 18 publications

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“…Some in-depth understanding and mathematic models regarding the pattern of scanned surfaces are presented in representative researches [55]- [59]. Treated as one of the main causes of form defects, manufacturing signatures of machined surfaces has great influence on assembly [60], [61], and should be considered in scale reduction. Also, some common thresholdbased feature indicators (such as curvature) are not suitable for metrics formulation because they are not varying gradually but abruptly, which would decrease estimation accuracy and the loss of surface details.…”

Section: Fig1 Application Framework Of Automatic Assembly Line Basedmentioning

confidence: 99%

Fast Assembly Tolerance Inspection Method Using Feature-Based Adaptive Scale Reduction in Automatic Assembly Line

Qiu

Zhang

et al. 2020

IEEE Access

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Enormous computation and long data processing time of the online tolerance inspection procedure has been a bottleneck in reducing the production cycle time of automatic assembly line. To reduce time consumption while maintaining accuracy, a fast assembly tolerance inspection method is proposed in this paper using scale-reduced models. First, the general part surface, input by a laser-scanned dense point cloud, is segmented through feature-based clustering. Shape variation estimation are designed to determine reduction ratios between clusters adaptively. Then, assembly simulation method is further advanced to utilize coarse point models with imbalanced density. Finally, numerical experiments are designed to estimate both static and dynamic assembly tolerances as results of tolerance inspection. A case study on a motion component of a rail material transporter shows that the proposed method could reduce 81% of the data processing time compared to traditional practice. The precision loss has minor influence on the inspection results because spatial positioning error is no more than 6% of tolerance interval and 18% of scanning resolution. Moreover, the proposed method has a comprehensive advantage of time and accuracy than two conventional point cloud simplification techniques based on iterative and clustering methods.

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Section: Fig1 Application Framework Of Automatic Assembly Line Basedmentioning

confidence: 99%

Fast Assembly Tolerance Inspection Method Using Feature-Based Adaptive Scale Reduction in Automatic Assembly Line

Qiu

Zhang

et al. 2020

IEEE Access

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“…is used to describe the accumulation of deviations in the assembly. Several DVPMs are developed during past decades, including matrix model [2], [3], Jacobian-Torsor model [4], [5], T-Map model [6], [7], DLM model [8], [9], stream-of-variation (SOV) model [10]- [12] and skin shapes mode [13]- [15]. A summary of the literature is presented as follows:…”

Section: Introductionmentioning

confidence: 99%

Dimensional Variation Analysis for Rigid Part Assembly With an Improvement of Monte Carlo Simulation

Tang

Zhang

2020

IEEE Access

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Dimensional variation has significant effect on the quality of product. Recently, Monte Carlo (MC) simulation is widely used in dimensional variation analysis, with high accuracy and adaptability, but there is the problem of low computational efficiency. Aiming to address this problem, an improvement of MC simulation is proposed through a two-phases solution. In the first phase, surrogate model is used to approximate the locating constraint equations for a 3D part, which reduces the nonlinear coupling between dimensional deviations and avoids large-scale solution of nonlinear equations in dimensional variation analysis on the condition of ensuring the accuracy. In the second phase, random samples used in MC simulation are replaced by low discrepancy sequences, which enable the samples to have better homogeneity and representativeness and reduce the number of samples required in the dimensional variation analysis. Finally, two examples are used to demonstrate the effectiveness of the method, and the results show that the two-phases solution has advantages both in the accuracy and efficiency.

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“…e recent publication of ISO 14405-1: 2016 determines size as a fundamental geometric descriptor. It also defines a new set of modifier tools for size [1,2]; Jbira et al [3] proposed a methodology to evaluate the algorithmic error of modifiers in the ISO 14405-1 [4] standard. ey demonstrated that the noise measurement affects the ISO 14405-1 modifier.…”

Section: Introductionmentioning

confidence: 99%

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

Jbira

Tahan

Bonsaint³

et al. 2019

Journal of Control Science and Engineering

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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.

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CAD/Tolerancing integration: Mechanical assembly with form defects

Cited by 28 publications

References 18 publications

Fast Assembly Tolerance Inspection Method Using Feature-Based Adaptive Scale Reduction in Automatic Assembly Line

Fast Assembly Tolerance Inspection Method Using Feature-Based Adaptive Scale Reduction in Automatic Assembly Line

Dimensional Variation Analysis for Rigid Part Assembly With an Improvement of Monte Carlo Simulation

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

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