Rapid Response Diagnosis of Multi-stage Assembly Process with Compliant non-ideal Parts using Self-evolving Measurement System

Franciosa, Pasquale; Palit, Arnab; Vitolo, Ferdinando; Ceglarek, Darek

doi:10.1016/j.procir.2017.01.035

Cited by 18 publications

(10 citation statements)

References 11 publications

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“…4. Flowchat of the proposed method application to automotive body assembly systems [11]. The proposed approach allows to take into account the feasibility of the robot configurations from the very early stage of the optimization workflow.…”

Section: Introductionmentioning

confidence: 99%

A Generalised Multi-Attribute Task Sequencing Approach for Robotics Optical Inspection Systems

Vitolo

Franciosa

Ceglarek

et al. 2019

2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT)

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Section: Introductionmentioning

confidence: 99%

A Generalised Multi-Attribute Task Sequencing Approach for Robotics Optical Inspection Systems

Vitolo

Franciosa

Ceglarek

et al. 2019

2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT)

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“…First, the assembly process generally includes many assembly stages. The output geometry of one stage is the input of the next stage, and thus, the assembly geometry is modified from station to station [3,4] due to the succession of assembly operations [5]. In addition, the flexibility of aeronautical components makes their inspection arduous because of the deformations induced by the gravity load and by fixturing conditions [6].…”

Section: Introductionmentioning

confidence: 99%

“…These conditions are reproduced thanks to modular equipment. Another approach, described by P. Franciosa et al [4], consists of coupling a prediction of the defect patterns of a component with a measurement step to find the real causes of these defects at different stages of the assembly process. These methods require the configuration of use to be reproduced, which turns out to be expensive in the context of large aeronautics components.…”

Section: Introductionmentioning

confidence: 99%

Free-State Shape of Aeronautical Components for Assembly Simulation

Gringoz

Thiébaut

Lartigue

et al. 2019

Advances on Mechanics, Design Engineering and Manufacturing II

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This paper deals with a method to extract the free-state shape of aeronautical assembly components from part measurements independently of the assembly configuration of use. Knowledge of the free-state shapes enables to assess the geometrical conformity of an assembly through the assembly simulation using Finite Element Method (FEM). The component is measured, using optical means in a given configuration for which the setup is well-known. A coarse cleaning is thus applied on the measured data to obtain manipulative data in the CAD model frame. Meanwhile, displacements due to the measuring setup and to gravity are evaluated from the nominal geometry using FEM. Finally, the free-state shape, as a finite element mesh, is achieved by moving the nominal mesh nodes by a distance equal to the measured defect minus the evaluated displacement. The approach is applied to an aeronautical component.

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“…Previously, some attempts have been made to extend defect models to estimate reliability. At first, a simple time-independent Poisson reliability was obtained assuming directly that the number of nonfatal defects corresponded to the fatal defects following a Poisson distribution [ 13 , 14 , 15 ]. All models implicitly assumed that the number of fatal defects is independent of the number of the latent defects in a device.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Evaluation in Multistage Assembly Process Based on Enhanced OOPN

Huang

Dai

Mou

et al. 2018

Entropy

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This study investigated the uncertainty of the multistage assembly process from the viewpoint of a stream of defects in the product assembly process. The vulnerable spots were analyzed and the fluctuations were controlled during this process. An uncertainty evaluation model was developed for the assembly process on the basis of an object-oriented Petri net (OOPN) by replacing its transition function with a fitted defect changing function. The definition of entropy in physics was applied to characterize the uncertainty of the model in evaluating the assembly process. The uncertainty was then measured as the entropy of the semi-Markov chain, which could be used to calculate the uncertainty of a specific subset of places, as well as the entire process. The OOPN model could correspond to the Markov process because its reachable token can be directly mapped to the Markov process. Using the steady-state probability combined with the uncertainty evaluation, the vulnerable spots in the assembly process were identified and a scanning test program was proposed to improve the quality of the assembly process. Finally, this work analyzed the assembly process on the basis of the uncertainty of the assembly structure and the variables of the assembly process. Finally, the case of a certain product assembly process was analyzed to test the advantages of this method.

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Rapid Response Diagnosis of Multi-stage Assembly Process with Compliant non-ideal Parts using Self-evolving Measurement System

Cited by 18 publications

References 11 publications

A Generalised Multi-Attribute Task Sequencing Approach for Robotics Optical Inspection Systems

A Generalised Multi-Attribute Task Sequencing Approach for Robotics Optical Inspection Systems

Free-State Shape of Aeronautical Components for Assembly Simulation

Uncertainty Evaluation in Multistage Assembly Process Based on Enhanced OOPN

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