Industry 4.0 Formability Next Generation Optical Metrology for - - PowerPoint PPT Presentation

John “Yanni” Psilopoulos Technical Account Manger

Industry 4.0 Formability

Next Generation Optical Metrology for Sheet Metal Stamping Quality Control

Trilion Quality Systems

Trilion ARGUS Technology

Supporting automotive stamping operations for 20 years.

Trilion Quality Systems

Trilion team User Meetings Engineering Services Customer Training

Agenda – Industry 4.0 Formability

DIC for Material Properties

• Bulge & Nakajima Testing - FLC
• Incoming Inspection - Tensile Testing – N-value
• corrected FLC - for N- & Non-linear

Optical Forming Analysis (OFA) Patterning

• Chemical Etching vs Laser Etching
• Laser Etching
• Robotic Laser Etching

Optical Forming Analysis (OFA) Measurement

• OFA Formability
• FEA Comparison
• Automated OFA

DIC for Press Deflection

• Setup
• Reporting
• High & Low Speed testing

ARGUS

Optical Forming Analysis

TRILION ENGINEERING SERVICES

Non-contact measurements

Laser Etching

Precision ARGUS Patterning

ARGUS ScanBox

Automated ARGUS

ARAMIS HHS

Press Deflection Tests

Incoming Material FLC

ARAMIS

Formability 4.0 Metrology

Trilion is on the cutting-edge developing next generation technologies for industry. Today, Industry 4.0 Formability, providing precision measurement and automation, to assist with the lightweighting issues of stamping.

Tensile Test

Incoming Inspection for Corrected FLC

• N-Value
• Non-linear Forming

DIC for Materials Testing

Full-field 3D data with DIC Determination of material parameters Any material Strain distribution Analyze local effects

Measurement of Tensile Tests with DIC

ARAMIS for Materials Testing | GOM GmbH

DIC Measurement Project Evaluation Image acquisition DIC measurement project definition and image processing 3D measurement data post-processing Calculation of tensile test relevant material parameters ∙Young’s modulus ∙Poisson ratio ∙Rp0.2% ∙Rm, Ag ∙R-Value ∙N-Value

Calculation of Material Parameters in DIC

Analysis of sheet metal formability Material parameter curve describing the limit of forming of sheet metal materials The FLC describes the formability in the range from uni-axial to bi-axial deformation

Forming Limit Curve

ARAMIS for Materials Testing | GOM GmbH

Analysis of sheet metal formability Material parameter curve describing the limit of forming of sheet metal materials The FLC describes the formability in the range from uni-axial to bi-axial deformation 1: Uni-axial strain condition

Forming Limit Curve

ARAMIS for Materials Testing | GOM GmbH

1

Analysis of sheet metal formability Material parameter curve describing the limit of forming of sheet metal materials The FLC describes the formability in the range from uni-axial to bi-axial deformation 1: Uni-axial strain condition 2: Plain strain condition

Forming Limit Curve

ARAMIS for Materials Testing | GOM GmbH

1 2

Analysis of sheet metal formability Material parameter curve describing the limit of forming of sheet metal materials The FLC describes the formability in the range from uni-axial to bi-axial deformation 1: Uni-axial strain condition 2: Plain strain condition 3: Bi-axial strain condition

Forming Limit Curve

ARAMIS for Materials Testing | GOM GmbH

1 2 3

ARAMIS for Materials Testing | GOM GmbH

DIC Kiosk Mode runs the Incoming Material Test automatically

DIC Automated Incoming Inspection

• Performing material testing for complete knowledge of material

being used during the runs

• Automated with parametric templates for easy repeated

testing for high throughput

• Corrected FLC for N-value & Non-linear forming
• Leading to correct forming limits for current coil sample
• Leading to a more accurate tracking metric per production run
• Reducing tool changes due to wrong material information
• Understanding incoming material sample
• Reducing tool changes due to material variation
• Reducing press downtime
• Leading to better panel quality
• Leading to higher production output with less dedicated

resources

DIC for Precision Material Properties

• DIC allows the operator to automatically test material and report

to the entire team quickly and efficiently.

• The parametric functions allow for the operator to run sample

after sample without recreating the reports each time. The reporting template is saved and reused having all of the necessary data previously created.

• The automated kiosk mode is used in correlation in running

consecutive samples. Then the reports are automatically generated and exported to the entire team. The ability of gathering actual material data of incoming coils allow for the build facilities and production facilities to be proactive instead

• f reactive during tool runs. Thus leading to less overall downtime.

DIC and Industry 4.0

Sheet Metal Etching for Optical Formability Analysis

ARGUS – Optical Forming Analysis

Measuring Principle – Optical Forming Analysis Patterning

Apply regular dot pattern before forming ∙ Electro-chemical etching ∙Hazardous chemicals ∙Variable Accuracy ∙ Laser marking ∙Precise, on any material ∙Automated

ARGUS – Optical Forming Analysis

Computation of 3D coordinates of all dots with at least three camera positions Results for all measuring points ∙3D coordinates ∙Major and minor strain ∙Material thickness reduction Forming limit diagram Validation and optimization of numerical forming simulations

Measuring Principle

OFA Laser Etching: Autonomous Panel Marking for Precision Measurements

Aim of the Solution: The autonomous laser etching robot provides perfectly marked panels, automatically, for optical formability measurements. This method substantially reduces labor requirements and training, while providing enhanced safety, for personnel and the environment. Expected Results: The results of this autonomous laser etching method will produce an accurately placed perfect dot/line pattern, for the entire panel,

• r for specific areas of concern. This pattern will have the proper

contrast and is material independent, without the use of toxic chemicals.

Epsilon X directional strain accuracy is at +/-0.2% (Epsilon X is strain from left to right)

Epsilon X Epsilon Y

Epsilon Y directional strain accuracy is at +/-0.2% (Epsilon Y is strain from top to bottom)

• The Laser Etching Process took 6.5min/grid
• Each Grid is 12in square
• Etching Error 2-5x better than manually

OFA Laser Etching: Difficult Automotive Part

Major Strain Minor Strain Thickness Reduction

OFA Laser Etching: Difficult Automotive Part

Perfect Laser Etch, with substantially better results than manual chemical etching.

OFA Laser Etching Robot

• Cost Saving by allowing the laser to perform the precision etching,

perfectly every time, for any material.

• Saving $250k/year
• No more wasted manhours etching questionable quality grids
• Cost saving on material
• Cutting material waste from badly etched panels
• Better knowledge of binder pull-in for better material utilization.
• Increased accuracy of critical lightweighting panels
• More accurately etched panels allowing for more accurate

formability results

• More accurate designs on non-linear strain paths.
• Fixing non-linear forming errors
• Reducing downstream splits
• Reducing vehicle structural recalls
• Reducing warranty issues
• Happy Customers … Happy Corporation
• The cost savings are measurable on a per unit, man hour, and hourly

Machine/Assembly Line downtime.

• “Green” environmentally friendly
• No Hazardous Chemicals needed
• Etching area can be easily placed or moved to anywhere in the plant

Autonomous Laser Etching Robot – Industry 4.0 Formability

• Autonomous Laser Etching unit allows the ability to create

repeatable and accurate pattens for OFA (Optical Forming Analysis).

• OFA patterns that have the least amount of noise will give the use

the most accurate results needed to make more informed decisions.

• Autonomous Laser Etching now allows the a “set it and forget it”

setup.

• The user places the unit down and allows it to perform the
• peration
• Repeatable accurate pattern is created each time.
• This leads to less material waste, less tool downtime and better
• verall data of the formability process.
• A library of patterns with settings is created and called upon

each time a panel needs to be checked.

Autonomous Laser Etching Robot and Industry 4.0

Optical Forming Analysis

ARGUS – Optical Forming Analysis

Optical Forming Analysis - Process

ARGUS – Optical Forming Analysis

Optical Forming Analysis - Result

Optical Forming Analysis Applications

Monitoring of Process Stability in series production

ARGUS – Optical Forming Analysis

Verification of Numerical Simulations

Import of FEA data 3D coordinate system alignment ∙ Best-fit ∙ Manual registration

ARGUS – Optical Forming Analysis

Verification of Numerical Simulations

Import of FEA data 3D coordinate system alignment ∙ Best-fit ∙ Manual registration Calculation of surface (geometry) deviations

ARGUS – Optical Forming Analysis

Import of FEA data 3D coordinate system alignment ∙ Best-fit ∙ Manual registration Calculation of surface (geometry) deviations Mapping of the FEA points to the measurement points

Verification of Numerical Simulations

ARGUS – Optical Forming Analysis

Verification of Numerical Simulations

Import of FEA data 3D coordinate system alignment ∙ Best-fit ∙ Manual registration Calculation of surface (geometry) deviations Mapping of the FEA points to the measurement points Calculation of differences between FEA and measurement

ARGUS – Optical Forming Analysis

Verification of Numerical Simulations

Simulation verification ∙ Verification of boundary conditions ∙ Knowledge building and transfer ∙ Optimization of simulation processes

ARGUS – Optical Forming Analysis

Verification of Numerical Simulations — Comparison of Equivalent Strain (before Trimming Process)

FEA data Measuring data Comparison

ARGUS – Optical Forming Analysis

Verification of Numerical Simulations — Comparison of Material Thickness (before Trimming Process)

FEA data Measuring data Comparison

ARGUS – Optical Forming Analysis

Verification of Numerical Simulations — Comparison of Equivalent Strain (after Trimming Process)

FEA data Measuring data Comparison

ARGUS – Optical Forming Analysis

Verification of Numerical Simulations — Geometric Boundaries

Measuring data FEA data

Measured and simulated strain differ due to varying material intake ∙ Different blank sizes, no access to beading ∙ Different friction behavior

Comparison

ARGUS – Optical Forming Analysis

Verification of Numerical Simulations — Influence of Draw Beads

Missing draw beads in simulation data Assumption of equivalent forces to simplify the draw bead simulation Major strain deviation between simulation and measurement

Measuring data FEA data Comparison

Optical Forming Analysis Applications

Tool Optimization

ARGUS – Optical Forming Analysis

Tool Optimization

Before tool optimization After tool optimization

Optical Forming Analysis Applications

Monitoring of Process Stability in series production

ARGUS – Optical Forming Analysis

Monitoring of Process Stability

On-site monitoring of process, tools and materials Inspection and acceptance of prototype tools before series production Detection of changes throughout production

ARGUS – Optical Forming Analysis

Monitoring of Process Stability

Before trimming process After trimming process

Critical area

Critical area near forming limit curve before trimming process Part vulnerable to process and material volatility Even though the critical area is

• utside of part boundaries, it

influences the overall quality of the part

Automated Optical Forming Analysis

ARGUS – Optical Forming Analysis

Automated Optical Forming Analysis: Industry 4.0 Formability

ARGUS – Optical Forming Analysis

Automated Optical Forming Analysis: Industry 4.0 Formability

Automated Optical Forming Analysis

• Cost Saving on man hours by allowing the ScanBox to perform shot

process automatically and perfectly every time.

• Simple Training
• Saving $250k/year (Based on one employee per year)
• No more wasted man hours taking repeated bad shots
• Automation recorded once per panel, then repeated automatically

for subsequent measurements of same panels. (time saving)

• Cost saving on material
• Cutting material waste from badly etched panels
• Leading to precision first run formability measurements
• More accurate formability results
• Leading to the ability for tracking panel to panel metric through

build, production and life of tool

• Leading to better decision making of the quality team moving

forward using complete panel knowledge

• Leading to less downstream splits
• Less vehicle structural recalls
• Less warranty issues
• The cost savings are measurable on a per unit, man hour, and hourly

Machine/Assembly Line downtime.

Automated Optical Forming Analysis: Industry 4.0 Formability

Precision FEA Modeling – Including Non-linear Forming

• Better Computer Models make better Parts.
• Stamping design of lighter materials requires higher precision
• Non-linear forming now has a much larger influence
• Cost saving on reduced problems
• Better designed parts: Form correctly the first time
• Better designed parts: Make better parts
• The cost savings are measurable on a per unit, man hour, and

hourly Machine/Assembly Line downtime.

• More accurate parts result
• Leading to less downstream problems
• Less vehicle structural recalls
• Less warranty issues
• Happy customers

OFA / Precision FEA Modeling – Industry 4.0 Formability

• OFA has automated the sheet metal formability for

manufacturing.

• OFA shows the entire panels response to the forming

process.

• No more single point analysis as in traditional CGA
• Automated reporting process from panel to panel using

parametric functionality.

• A simple “update” to the previous report and the

current report is completed.

• These reports can then be automatically shared to

the entire quality team.

• Comparisons to other data sets
• Previous OFA (Major, Minor, Thickness Reduction)
• CAD models for shape
• FEA data (Theoretical to Actual)
• Easy and automatic metric reporting

Having these reports quickly and efficiently

• ffers the confidence of knowing the exact state of the tool

and the panel at that specific run and press setup.

OFA / Automated OFA and Industry 4.0

Automated OFA now allows the operator to perform the same measurements as manual OFA, but simply by pulling up a program and letting the machine run.

• The Automated OFA unit records the original path taken to

shoot the first panel and saves it. This program can then be rerun for future measurements.

• This process allows the operator to perform other job

functions.

• Once the program is complete is automatically computes

the data and is ready for reporting. As mentioned above, using the automated reporting function, the operator only needs to hit update and then send out the completed reports.

• The addition of automated OFA will give facilities the ability

to create databases of previously measures panels and using current workforce for multiple tasks while attaining highly accurate date at a lower cost.

Digital Image Cerrelation (DIC) for Press Deflection

• Understanding press performance during operation

ARGUS – Optical Forming Analysis

DIC for Press Deflection -

System/Set-up -

• Precision Sticker Targets
• Stereo Image DIC System
• Calibrated FOV (Field Of View)

Results -

• In and Out of plane vector displacements during

press activity

ARGUS – Optical Forming Analysis

DIC for Press Deflection -

ARGUS – Optical Forming Analysis

DIC for Press Deflection -

ARGUS – Optical Forming Analysis

DIC for Press Deflection -

ARGUS – Optical Forming Analysis

DIC for Press Deflection -

DIC for Press Deflection

• Measuring relative displacements of Press and Tool

components

• Comparision to base-line operation

Purpose

• Understanding Press performance during operation
• Station to Station performance validation
• Material effect on Tool and Press, particulrly HS & UHS
• Recording die recipe and tracking as an ongoing metric

for better panel quality

• Knowing which variable is causing the issue and

addressing it correctly Cost saving

• Preventative maintenance
• Understanding Press issues or Tool issues.
• Rapidly solving problems

ARGUS – Optical Forming Analysis

DIC for Press Deflection and Industry 4.0

There are many variables that go into manufacturing. Starting from the material testing, we see that more information that is highly accurate on a regular basis is key. This information should also extend to the machinery and the tools that create the

• panels. In most cases we find that though all things are pointing

to good panel data, the panels still fail.

• DIC is now being applied for monitoring presses in real time.
• During the run the DIC system can see all vectors of deflection.
• The system can also be setup to automatically report back to a

remote station in case of errors.

• The press can be initially measured to develop a tolerance

profile, then all subsequent tools can be set to a tolerance of safety.

• This can be monitored in real time during the scheduled run for

quick response.

Conclusion

DIC for Material Properties

• Bulge & Nakajima Testing - FLC
• Incoming Inspection - Tensile Testing – N-value
• corrected FLC - for N- & Non-linear

OFA Patterning for Sheet Metal Formability

• Chemical Etching
• Laser Etching – Industry 4.0 Formability

OFA Measurement

• OFA Formability
• FEA Comparison
• Automated Optical Forming Analysis

DIC for Press Deflection

• Setup
• Reporting
• High & Low Speed testing

Trilion Quality Systems

Trilion Industry 4.0 Technology

PA Office

Philadelphia

PA Office

Philadelphia

MI Office

Detroit

MI Office

Detroit

WA Office

Seattle

WA Office

Seattle

CA Office

Los Angeles

CA Office

Los Angeles

Supporting automotive stamping operations for over 20 years.

Trilion Quality Systems 651 Park Ave, King of Prussia, PA 19406 (215) 710-3000 info@trilion.com