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Research Papers

A Novel Approach for the Inspection of Flexible Parts Without the Use of Special Fixtures

[+] Author and Article Information
Gad N. Abenhaim1

Department of Mechanical Engineering, Université de Sherbrooke, Sherbrooke, QC, J1K 2R1, Canadagad-noriel.abenhaim@usherbrooke.ca

Antoine S. Tahan

Department of Mechanical Engineering, École de Technologie Supérieure (ÉTS), Montreal, QC, H3C 1K3, Canadaantoine.tahan@etsmtl.ca

Alain Desrochers

Department of Mechanical Engineering, Université de Sherbrooke, Sherbrooke, QC, J1K 2R1, Canadaalain.desrochers@usherbrooke.ca

Roland Maranzana

Department of Mechanical Engineering, École de Technologie Supérieure (ÉTS), Montreal, QC, H3C 1K3, Canadaroland.maranzana@etsmtl.ca

The term deviations is preferred to defects since the latter is dependent on the assigned tolerance.

Three well-positioned clamps were used during the simulation in order to ensure the deformation of the part.

1

Corresponding author.

J. Manuf. Sci. Eng 133(1), 011009 (Feb 01, 2011) (11 pages) doi:10.1115/1.4003335 History: Received January 07, 2010; Revised November 30, 2010; Published February 01, 2011

In a free state, flexible parts may have different shapes compared to their computer-aided design (CAD) model. Such parts may likewise undergo large deformations depending on their space orientation. These conditions severely restrict the feasibility of inspecting flexible parts without restricting the deformations of the part and therefore require dedicated and expensive tools such as a conformation jig or a fixture to maintain the integrity of the part. To address these challenges, this paper proposes a new inspection method, the iterative displacement inspection (IDI) algorithm, that evaluates profile variations without the need for specialized fixtures. This study examines 32 models of simulated manufactured parts to show that the IDI algorithm can iteratively deform the meshed CAD model until it resembles the scanned manufactured part, which enables their comparison. The method deforms the mesh in such a manner so as to ensure its smoothness. This way, neither surface defects nor the measurement noise of the scanned parts are concealed during the matching process. As a result, the case studies illustrate that the method’s error essentially only represents the scanned part’s measurement noise. The inspection results, therefore, solely reflect the effect of variations from the manufacturing process itself and not the deformation of the part.

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Copyright © 2011 by American Society of Mechanical Engineers
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Figures

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Figure 1

Illustration of a dent shaped deviation characteristics; area AD and peak deviation HD

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Figure 2

Deformation required by the CAD model to reflect a scanned part without profile deviation

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Figure 3

Substitution of each target point ci with ci′

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Figure 4

Construction of a deformed meshed CAD model (S′) closer to the scanned part (P) even though points c7 and c8 are in a zone with a profile deviation

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Figure 5

Schematic diagram of (a) a part without a zone with profile deviations and (b) a part with a zone with profile deviations (points c8 and c9)

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Figure 6

Neighborhood of node 742: (a) level 1 and (b) level 2

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Figure 7

Flow chart of the identification method

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Figure 8

Flow chart of the IDI algorithm

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Figure 9

Descriptions of the case studies: (a) quasi-constant surface, (b) U-shape surface, and (c) freeform surface. Points PDCSi, with i=1,2,3, indicate the 3-2-1 fixing layout used to build the simulated manufactured part. They are also used as landmark points in the pre-alignment step.

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Figure 10

Convergence of the average corrected distance

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Figure 11

IDI method’s accuracy compared with the peak profile and the maximum deformation imposed on the simulated scanned part

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Figure 12

Overview of the IDI method accuracy by dividing the accuracy found for nodes in zones with and without known profile deviations: ((a)–(c)) Nodes in zones without known profile deviations. ((d)–(f)) Nodes in zones with known profile deviations for the quasi-constant surface, the U-shape surface, and the freeform surface, respectively.

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Figure 13

Distribution of the IDI method accuracy compared with the distribution of the noise added during the simulation of the scanned part: (a) the quasi-constant surface, (b) the U-shape surface, and (c) the freeform surface

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Figure 14

Illustration of the normal vector at a point

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