Integration of Emerging Inspection Devices with Rapid ... · Integration of Emerging Inspection Devices with Rapid Manufacturing Systems ... Integration of Emerging Inspection Devices

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TECHNION-Institute for Science and technology

Laboratory forCAD & LCE

Integration of Emerging Inspection Deviceswith

Rapid Manufacturing SystemsAnath Fischer

Laboratory for CAD & Life Cycle EngineeringFaculty of Mechanical Engineering

Technion - Israel Institute of Technology, Haifa, Israel

CIRP-2007-SPCIES-Production System EvolutionDresden, Germany, August, 2007

Integration of Emerging Inspection Deviceswith

Rapid Manufacturing SystemsAnath Fischer

Laboratory for CAD & Life Cycle EngineeringFaculty of Mechanical Engineering

Technion - Israel Institute of Technology, Haifa, Israel

CIRP-2007-SPCIES-Production System EvolutionDresden, Germany, August, 2007

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Industry Globalization ChallengesIndustry Globalization Challenges

• Globalization has forced industries to operate in a highly competitive environment.

• The challenge is to increase the volume and variety of global transactions: products, services, knowledge.

• Technological developments are need to improve production systems.

• Globalization has forced industries to operate in a highly competitive environment.

• The challenge is to increase the volume and variety of global transactions: products, services, knowledge.

• Technological developments are need to improve production systems.

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Current Status of Digital InspectionCurrent Status of Digital Inspection

• At the end of the manufacturing process, a produced part should be verified to determine whether it fits the CAD model prototype under a given tolerances.

• The importance of automatic inspection for manufacturing is growing.

• Current production demands fully automatic, fast and accurate inspection.

• At the end of the manufacturing process, a produced part should be verified to determine whether it fits the CAD model prototype under a given tolerances.

• The importance of automatic inspection for manufacturing is growing.

• Current production demands fully automatic, fast and accurate inspection.

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Scan data problemsScan data problems

Physical Physical

ObjectObject

Scanned model: Scanned model:

large‐scale, noisy, unorganized, missing

information on properties of the sampled object

Scanning

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Traditional Inspection Methodsvs. Emerging scanning technologies

Traditional Inspection Methodsvs. Emerging scanning technologies

• Existing inspection computational methods do not take diverse scan information into account.

• Therefore, traditional inspection methods are limited and do not satisfy industry demands.

• Emerging scanning technologies are capable ofcapturing diverse data regarding geometrical and physical properties of the sampled object, such as surface normals, color, material.

• Existing inspection computational methods do not take diverse scan information into account.

• Therefore, traditional inspection methods are limited and do not satisfy industry demands.

• Emerging scanning technologies are capable ofcapturing diverse data regarding geometrical and physical properties of the sampled object, such as surface normals, color, material.

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Inspection technologies andcomputational methods

Inspection technologies andcomputational methods

• Inspection technologies and computational methods are embedded and strongly interconnected components of a single process.

• Utilizing the synergy between them should have a significant impact on global inspection by accelerating digital geometric processing and improving reconstructed object accuracy.

• Inspection technologies and computational methods are embedded and strongly interconnected components of a single process.

• Utilizing the synergy between them should have a significant impact on global inspection by accelerating digital geometric processing and improving reconstructed object accuracy.

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The GoalThe Goal

Developing a new approach for

inherently handling diverse data

and

utilizing scanning technologies

for inspection.

Developing a new approach for

inherently handling diverse data

and

utilizing scanning technologies

for inspection.

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Utilizing the Diverse Data for Inspection: The Approach


Scanning process

Cloud of points

Analysis of scanned points

Calculation of normals

Sharp feature detection

Segment identification

Diverse scan data

Surface normals

Sharp feature knowledge

Segment information

Color

Material

Inspection

Data verification and HSDM reconstruction

Scan data filtering

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3D Non-Contact Measurement Technology

3D Non-Contact Measurement Technology

• Recent advances in computer vision and optics have led to development of emerging non-contact scanning devices.

• Non-contact scanners are capable of sampling a very dense cloud of points from a part’s surface in seconds.

• The following emerging non-contact technologies are described:

o Laser scannerso Lasers based on Conoscopic Holography technologyo 3D cameras

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3D Non-Contact Technology:Laser Scanners

3D Non-Contact Technology:Laser Scanners

• Laser scanner uses stereoscopic technique(Cyberware, Nextech).

• The distance of a sampled point is computed by means of a directional light source and a video camera.

• The CCD camera’s 2D array captures the image of the surface profile along the laser sampling.

• The disadvantage is that the camera collects a small percentage of the reflected energy and therefore additional processing is needed.

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NEXTEC- Digital CMMbased on laser scanning technology

NEXTEC- Digital CMMbased on laser scanning technology

ProductLaser 3D scanning for quality control, inspection and reverse engineering applications.

Specifications• Automatic Alignment Time: 50 sec• Total Machine Accuracy: 14 µm (2 sigma) • Data capture rate: 50 points per sec

Advantages• Fully compatible with traditional CMM equipment • Highly reliable measurements• High flexibility

ProductLaser 3D scanning for quality control, inspection and reverse engineering applications.

Specifications• Automatic Alignment Time: 50 sec• Total Machine Accuracy: 14 µm (2 sigma) • Data capture rate: 50 points per sec

Advantages• Fully compatible with traditional CMM equipment • Highly reliable measurements• High flexibility

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NEXTEC- Digital CMMadapts globalization strategy

NEXTEC- Digital CMMadapts globalization strategy

Nextec- Laser scanner

CMMs- Coord3, Brown&Sharp, Mitutoyo

Blades Technology -Pratt & Whitney and Rolls Royce

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NEXTEC- Digital CMMNEXTEC- Digital CMM

Product Laser 3D scanning for quality control and reverse engineering applications.Typical Applications

• Injection molding• Stamping• Inspection & RE • Dimensional verification

Product Laser 3D scanning for quality control and reverse engineering applications.Typical Applications

• Injection molding• Stamping• Inspection & RE • Dimensional verification

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3D Non-Contact Technology:Conoscopic Holography Technology

3D Non-Contact Technology:Conoscopic Holography Technology

• Conoscopic holography is a polarized interference process based on crystal optics.

• The measurement process retrieves the distance of the light sampled point from a fixed reference plane.

• Advantages:•Accuracy measurement is in microns.•CH can handle large measurement angles.•CH measures metals with high accuracy.

• Disadvantage:•CH process is slow (minutes) with respect to 3D cameras.

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OPTIMET- Laser ScannerOPTIMET- Laser Scanner

ProductHigh precision , 3-D measurement sensors, based on conoscopic holography technology

Specifications • Accuracy absolute : 2 - 35 µm• Angle of reading up to 85 degrees• Reading speed: 800 points per sec

Advantages• Very high accuracy• Measurement from extremely acute angles• Robust to variety of surface properties


Specifications • Accuracy absolute : 2 - 35 µm• Angle of reading up to 85 degrees• Reading speed: 800 points per sec

Advantages• Very high accuracy• Measurement from extremely acute angles• Robust to variety of surface properties

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OPTIMET- Laser ScannerOPTIMET- Laser Scanner


Typical Applications• Quality control• Jewelry• Laser drillings • In-process inspection


Typical Applications• Quality control• Jewelry• Laser drillings • In-process inspection

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3D Non-Contact Technology:3D Cameras

3D Non-Contact Technology:3D Cameras

• 3D photography is based on reconstructing 3D data from 2D images, taken from different points of view.

• Matching problem: for a given sampled point, its projected point should be identified in each image.

• To this end, a pattern is projected on the part where the same pattern points are identified in each image (Cognitens).

• The advantage is that a large number of measurements can be produced in one shot.

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COGNITENS- 3D CameraCOGNITENS- 3D Camera

Product 3D camera for fast measurement of manufactured parts in plant floor environmentSpecifications

• Image acquisition: <0.001 sec• 3x1.3 mega pixel CCD cameras• Overall system accuracy: 100µm (3 sigma)

Typical Applications• automotive industry• aerospace industry

Advantages• Very high speed of measurement• Wide area measurement at one shot

Product 3D camera for fast measurement of manufactured parts in plant floor environmentSpecifications

• Image acquisition: <0.001 sec• 3x1.3 mega pixel CCD cameras• Overall system accuracy: 100µm (3 sigma)

Typical Applications• automotive industry• aerospace industry

Advantages• Very high speed of measurement• Wide area measurement at one shot

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Distribution of 3D scanning Technologies-Universities & Research Institutes

Distribution of 3D scanning Technologies-Universities & Research Institutes

Data acquisition technologies

72.73%

63.64%

27.27%

45.45%

9.09%

18.18%

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

CMM LaserScanners

2D Cameras 3D Cameras CT/MRIScanners

Other

Labs [%]

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Distribution of 3D Scanning Technologies- Hi-Tech Industry

Distribution of 3D Scanning Technologies- Hi-Tech Industry

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Distribution of Diverse Data Utilization-Hi-Tech Industry

Distribution of Diverse Data Utilization-Hi-Tech Industry

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Traditional Shape Retrieval MethodsTraditional Shape Retrieval Methods

• Most commercial methods that deal with shape retrieval do not utilize emerging technologies.

• They use only the 3D coordinates of the sampled object, while ignoring other diverse data provided by non-contact technology.

• As a result the digital geometric process becomes very difficult because it must extract implicit or missing information from the 3D coordinates.

• Moreover, it retrieves the object shape without preserving sharp features and smoothness, or detecting a functional surface.

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Shape Retrieval ProblemsShape Retrieval Problems

• Non-detection of sharp features

• Reconstructing inefficient mesh

• Ignoring mesh physical-based properties

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Using Diverse Scan DataUsing Diverse Scan Data

• Potential of emerging scan technologies is not utilized. • New methods needed to provide synergy between RT developers and

users.

Information on sharp features of the sampled objects

Surface normals associated with sampled points

Surface curvature associated with sampled points

Coordinatesof sampled points

Coordinates of sampled points

RT usersInspection developers

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The GoalThe Goal

Developing new reconstruction methodsthat

utilizes diverse scan data

Developing new reconstruction methodsthat

utilizes diverse scan data

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Scanning process

Cloud of points

Analysis of scanned points

Calculation of normals

Sharp feature detection

Segment identification

Diverse scan data

Surface normals

Sharp feature knowledge

Segment information

Color

Material

Inspection

Data verification and HSDM reconstruction

Scan data filtering

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Utilizing the Diverse Data for Inspection: The Grid-based Approach (2)

Utilizing the Diverse Data for Inspection: The Grid-based Approach (2)

Diverse scan data

Classify scan pointsto voxels

Inspection process and shape retrieval

For each voxel set of points

Apply 3D GBF filterto calculate

representative surface point

New reduced points

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2D Bilateral Filter2D Bilateral Filter

[ ] [ ]( , ) ( , )1n c n

nc f d n c g J J JJ

kδ

∈ Ω

⋅ ⋅= ∑

cc

n

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Stage 2: Applying3D Geometric Bilateral Filter (3D GBF)

for Data Fusion

Stage 2: Applying3D Geometric Bilateral Filter (3D GBF)

for Data Fusion

• 3D GBF calculates Representative Surface Point (RSP), which replaces the voxel set of points.

• The proposed 3D GBF is based on 2D bilateral filter technique.

• 3D GBF belongs to edge-preserving filters.

• 3D GBF utilizes diverse scan data and surface normal information to prevent smoothing across edges.

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3D Geometric Bilateral Filter(3D GBF)

3D Geometric Bilateral Filter(3D GBF)

( , ) ( , ) ( , ) ( , )1i j i j

j ij j ij j ij j ij j ij jp V p Vj

s f d p c g Lp Ls p k f d p c g Lp Lsk

δ δ∈ ∈

⎡ ⎤ ⎡ ⎤ ⎡ ⎤ ⎡ ⎤⋅ ⋅ = ⋅⎣ ⎦ ⎣ ⎦ ⎣ ⎦ ⎣ ⎦= ∑ ∑

sj – RSP point of voxel Vj.

f [ ] – closeness weight function.

g [ ] – similarity weight function.

d(pij , cj) – similarity of positions (Euclidian distance) between point pijand centroid cj .

δ(Lpij ,Lsj) – similarity of property L between points pij and sj .

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3D Geometric Multilateral Filter(3D GMF)

3D Geometric Multilateral Filter(3D GMF)

1 1 2 2

1 1 2 2

( , ) ( , ) ( , ) ( , )

( , ) ( , ) ( , ) ( , )

1i j

i j

n nj ij j ij j ij j ij j ij

p Vj

n nj ij j ij j ij j ij j

p V

s f d p c g Lp Ls g L p Ls g L p Ls p

k f d p c g Lp Ls g L p Ls g L p Ls

kδ δ δ

δ δ δ

∈

∈

⎡ ⎤ ⎡ ⎤ ⎡ ⎤⎡ ⎤⋅ ⋅⎣ ⎦ ⎣ ⎦ ⎣ ⎦ ⎣ ⎦

⎡ ⎤ ⎡ ⎤ ⎡ ⎤⎡ ⎤= ⋅ ⋅⎣ ⎦ ⎣ ⎦ ⎣ ⎦ ⎣ ⎦

= ∑

∑

…

…

δ(Lnpij ,Lnsj) – similarity of property Ln between points pij and sj .

3D GBF can be extended to use several types of diverse data.

Several properties L1, L2, …, Ln can be involved in the filtering process

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The proposed 3D GMF approach advantages

The proposed 3D GMF approach advantages

• Removes noise

• Preserving the underlying sampled surface including fine details and sharp features

• Reduces data, leading to further fast data processing or surface reconstruction

• Is robust, can handle complex topology

• Is fast

• Is simple to implement

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Diverse data based methodDiverse data based method

ExamplesExamples

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HSDM ReconstructionHSDM Reconstruction

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Neural-Network Grid-based Re-meshingfor micro-MRI Technology

Neural-Network Grid-based Re-meshingfor micro-MRI Technology

Rapid Prototyping models of bone micro-structure: (a) specimen from lumbar spine; (b) specimen from femoral bone

Micro-structures re-meshing using Neural Network: (a) Original mesh with 47%

failure -angles test;

(b) Re-meshed micro-structure results with only 22% failure in the same test

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Complexity analysisComplexity analysis

O(n)O(n)Mesh generation

O(n)O(dn)Connectivity graph construction

O(n)O(n)Scan data filtering

O(dn)O(dn)HSDM construction

SpaceTimeStage

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Summary & ConclusionsSummary & Conclusions

• The non-contact scanning technology can significantly improve automatic inspection in real time for rapid manufacturing (RM).

• Therefore, this technology enhances globalization.

• Hi-tech industries and RM use non-contact laser scanners, but do not utilize diverse data.

• A complete system that consists of non-contact technology and a robust surface reconstruction method is needed.

• In this talk we described diverse data based reconstruction methods that can be well integrated, in real time, with the non-contact technology.

Thank youThank you

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Integration of Emerging Inspection Devices with Rapid ... · Integration of Emerging Inspection Devices with Rapid Manufacturing Systems ... Integration of Emerging Inspection Devices