A graph-based data structure for assembly dimensional variation control at a preliminary phase of product design

Wang, H.; Juan, Yang; Ceglarek, Darek

doi:10.1080/09511920902942855

Cited by 9 publications

(3 citation statements)

References 19 publications

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“…In spite of the great need for tracking solutions in manufacturing environments, it seems that most of the quality assurance processes that require controlling and supervising the whole production chain to timely detect human errors and defective materials need to be further automatized. The major reason is that little attention has been paid to this problem due to technical limitations, and as result, there are not too many solutions in the manufacturing domain, but just a few works have been proposed to date [9,20,24,25] We can go even a step further beyond to see that the problem can be aggravated, even in the case of passing all quality assurance controls. The reason is that products can be rejected by end-users or other manufacturers if unknown problems appear.…”

Section: State-of-the-artmentioning

confidence: 99%

General Model for Tracking Manufacturing Products Using Graph Databases

Martinez‐Gil

Stumptner²,

Lettner

et al. 2020

Lecture Notes in Business Information Processing

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One of the major problems in the manufacturing industry consists of the fact that, when manufacturing a product, many parts from different lots are supplied and mixed to a certain degree during an indeterminate number of stages, what makes it very difficult to trace each of these parts from its origin to its presence in a final product. In order to overcome this limitation, we have worked towards the design of a general solution aiming to improve the traceability of the products from several manufacturers. This solution is based on the exploitation of graph databases which allows us to significantly reduce response times compared to traditional relational systems.

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Section: State-of-the-artmentioning

confidence: 99%

General Model for Tracking Manufacturing Products Using Graph Databases

Martinez‐Gil

Stumptner²,

Lettner

et al. 2020

Lecture Notes in Business Information Processing

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“…Some researchers have focused on the methodology of auto-generating variation propagation model. Wang et al (2009aWang et al ( , 2009bWang et al ( , 2012 developed an hierarchical data structure and an analyzing method for variation propagation at a preliminary phase of the product design. More recently, Du et al (2015), Liu et al (2015) and Cai et al (2015) proposed variation analysis methods based on SSM.…”

Section: Literature Reviewmentioning

confidence: 99%

Dimensional variation propagation modeling and analysis for single-station assembly based on multiple constraints graph

Tang

et al. 2016

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“…The rigid body kinematics stackup error was analyzed by using the stream of variation model the part geometric errors were simulated by statistical modal analysis and specified tolerances; these two errors are integrated in rigid assembly processes for covariance matrix construction. Wang et al (2009) presented a beam‐based product and process model which shares the same data structure of the B‐Rep CAD models (2009), and determined the influence of part deformation on variation propagation to generate a vector‐based variation propagation model for multi‐station sheet metal assemblies (2009). Kong et al (2009) developed a variation propagation model, which can be applied for analysis of various tolerances such as size tolerance, bonus tolerance, floating tolerance, etc.…”

Section: Introductionmentioning

confidence: 99%

Modeling and analyzing of variation propagation in aeronautical thin‐walled structures automated riveting

Cheng

Wang²,

Yuan³

et al. 2012

Assembly Automation

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -Assembly variations, which will propagate along the assembly process, are inevitable and difficult to analyze in Aeronautical Thin-Walled Structures (ATWS) assembly. The purpose of this paper is to present a new method for analyzing the variation propagation of ATWS with automated riveting. Design/methodology/approach -The paper addresses the variation propagation model and method by first, forming a novel Stage-State model to represent the process of automated riveting. Second, the effect of positioning error on assembly variation is defined as propagation variation (PV), and propagation matrix of key characteristic points (KCP) is discussed. Third, the effect between the variations in each stage is defined as expansion variation (EV). According to the analysis of mismatch error and the reference transformation, the expansion matrix is formed. Findings -The model can solve the variation propagation problem of ATWS with automated riveting efficiently, which is shown as an example of this paper. Practical implications -The variation obtained by the model and method presented in this paper is in conformity with the variation measured in experiments. Originality/value -The propagation variation and expansion variation is proposed for the first time, and variations are studied according to novel propagation matrix and expansion matrix.

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A graph-based data structure for assembly dimensional variation control at a preliminary phase of product design

Cited by 9 publications

References 19 publications

General Model for Tracking Manufacturing Products Using Graph Databases

General Model for Tracking Manufacturing Products Using Graph Databases

Dimensional variation propagation modeling and analysis for single-station assembly based on multiple constraints graph

Modeling and analyzing of variation propagation in aeronautical thin‐walled structures automated riveting

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