Digital Product Lifecycle Management

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Rapid Deployment of Remote Laser Welding (RLW) Processes in Automotive Assembly Systems Simulation Tools developed, verified and validated using Automotive Door Assembly (Assembly process with Compliant Non-ideal parts)

Professor Darek Ceglarek and Dr. Pasquale Franciosa International Digital Laboratory, WMG, University of Warwick, UK E-mail: {d.j.Ceglarek, p.franciosa}@warwick.ac.uk; Websites: http://www2.warwick.ac.uk/fac/sci/wmg/research/manufacturing/ (Digital Lifecycle Management Group) Websites: http://RLWnavigator.eu/ (RLW Navigator Programme)

More on the developed Simulation Tools for Assembly process with Complaint parts: http://rlwnavigator.eu/tools/ March 26, 2015 © 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB1

Remote Laser Welding (RLW) Key Enabling Technologies: Simulation Tools developed

The RLW Navigator Project will provide a software toolkit to facilitate the process planning, design, implementation and optimisation in the application of Remote Laser Welding technology in Body In White sheet metal joining

© 2009

2 Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB2

Remote Laser Welding (RLW) Key Enabling Technologies: Simulation Tools developed

Simulated RLW Process

Verified RLW Process

The Path to “Right-First-Time” © 2009

3 Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB3

Remote Laser Welding (RLW) Key Enabling Technologies: Simulation Tools developed  GUI based Process Estimator  R & M based Process Simulator  Reduced time to deliver Process Concept  Early Process and Robot Path Planning Feasibility  OLP for Remote Laser Welding  Workstation Layout  Robot/Fixture Calibration  Reduced Robot Programming in Commissioning/Launch phase

 Virtual “walk-through” of process based on fixture and robot optimisation

 Energy Consumption based on actual Robot Path and Process content

 Process Monitoring for Comau SmartLaser  Process Monitoring software to predict weld performance  Laser Parameter Optimiser to improve Weld Quality  Reduced Weld Quality Loops in Commissioning/Launch phase

 Early interaction with Product Design to generate feasible stitch matrix and 3D clamp design  Laser Parameter Process Window for all stack-ups related to weld performance  Reduced fixture clamp adjustment in Commissioning/Launch phase

The Path to “Right-First-Time” © 2009

4 Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB4

Remote Laser Welding (RLW) Key Enabling Technologies: Simulation Tools developed

Simulated RLW Process

 Virtual “walk-through” of process based on fixture and robot optimisation

© 2009

The Path to “Right-First-Time”

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB5

Remote laser Welding (RLW) Door assembly process “Right-First-Time: 100% simulated RLW assembly process

Simulated RLW Process

Verified RLW Process

Simulations Tools developed for RLW Process

© 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB6

Remote Laser Welding (RLW) Key Enabling Technologies: Demonstrator

The main purpose of the Demonstrator is to provide a industry compatible platform to verify and validate the experimental methods and tools to current industrial

standards and to apply these methods and tools to the Pilot Build of an existing industrial case study and demonstrate Application Readiness (TRL 6) TRL 1-2

TRL 3-4

TRL 5-6

TRL 7-9

The Path to “Right-First-Time” © 2009

7 Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB7

Remote Laser Welding (RLW) Key Enabling Technologies: Demonstrator Key Enabling Technologies: Demonstrator – Front Automotive Door Assembly

© 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB8

Remote Laser Welding (RLW) Key Enabling Technologies: Demonstrator Key Enabling Technologies: Demonstrator – Simulation and Physical Testbed

Comau SmartLaser

IPG 4kW Fibre Laser

Inspection Fixtures

PRIMES Power/Focus Meter

Metrology

PRECITEC Process Monitoring

Metallography

Strength Testing Welding Fixture

Dimpling Fixture

© 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB9

Remote Laser Welding (RLW) Key Enabling Technologies: Simulation Tools  GUI based Process Estimator  R & M based Process Simulator  Reduced time to deliver Process Concept  Virtual “walk-through” of process based on fixture and robot optimisation

 Early Process and Robot Path Planning Feasibility  OLP for Remote Laser Welding  Workstation Layout  Robot/Fixture Calibration  Reduced Robot Programming in Commissioning/Launch phase

 Energy Consumption based on actual Robot Path and Process content

 Process Monitoring for Comau SmartLaser  Process Monitoring software to predict weld performance  Laser Parameter Optimiser to improve Weld Quality  Reduced Weld Quality Loops in Commissioning/Launch phase

 Early interaction with Product Design to generate feasible stitch matrix and 3D clamp design  Laser Parameter Process Window for all stack-ups related to weld performance  Reduced fixture clamp adjustment in Commissioning/Launch phase

The Path to “Right-First-Time”

© 2009

10 Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB10

Remote Laser Welding (RLW) – NPI Process RLW Process Development Workflow Traditional BIW NPI Process Process Feasibility

System Configurato r

System & Workstation Design

System Configurato r

Eco-Advisor

Digital Visualisatio n

Process Control

Workstation Planner & OLP

Workstation Planner & OLP

Process Optimiser

Process Optimiser

Process Control

RLW Navigator – Toolkit © 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB11

Remote laser Welding (RLW) assembly process Simulation Tools: System Configurator

RLW System Configurator © 2009

Simulation Tool: Assembly Layout & Process Estimator Simulation Tool: System Configurator Optimizer 12 Contact: THE DIGITAL LAB12 Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

RLW System Configurator Simulation Tool: Assembly Layout & Process Estimator Brochure –http://rlwnavigator.eu/media/14764/assembly_layout_and_process_estimator.pdf Animation - https://www.youtube.com/watch?v=yILu8-VqM3U

What is it? •

Integrated environment based on a GUI for fast evaluation of layout feasibility

What does it do? • • • •

Quick design and editing of Assembly Layouts Automatic generation of Task Sequencing table Fast evaluation of main design KPIs Displays layout, task sequencing and KPIs at a glance

Benefits • • • • • • •

Strong reduction of time for line feasibility analysis Improved feseability evaluation Easier management of all data needed for line design within the same GUI Faster real time evaluation of design KPIs Fully customizable resources and costs database Easy management of design constraints Functionalities for faster reporting

© 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB13

RLW System Configurator Simulation Tool: Assembly Layout & Process Estimator – V&V JLR door test case has been implemented in order to verify the reliability of the tool in terms of GUI stability and results accuracy 20 entities, 57 operations and 9 stations have been defined in order to study the test case



Time to design the line ≈ 4h



Time for station definition ≈ 0.5h

STATION 1



© 2009

Results

Components 100 R1 Handling+Welding robot TurnTable Safety light OP1-Operator

Components Smart Laser-Lase welding robot TurnTable STATION 4 Clamping Fixture Complex-AUTO FIXTURE_AUTO CLAMPS (RLW) Power Motor 100R1-Handling+Welding robot Laser Source

REFERENCE VALUES FROM INDUSTRIAL CASE LAYER 0 RESULTS DELTA ERROR [%] WeightingFactor p with W.F. r WeightingFactor p with W.F. r WeightingFactor p with W.F. 0.216 0.0002233944 0.2557544757 0.232 0.0002389758 0.2557544757 7.4 7.0 0.080 0.0000200978 0.2508340231 0.080 0.0000200777 0.2508340231 0.0 -0.1 1.000 0.0000491639 0.4637076783 1.000 0.0000491587 0.4637076784 0.0 0.0 0.688 0.0017286432 1.0000000000 0.668 0.0017243108 1 -2.9 -0.3

r 0.0 0.0 0.0 0.0

WeightingFactor 0.757 0.090 0.072 1.000 0.072 1.000

r 0.0 0.0 0.0 0.0 0.0 0.0

p with W.F. 0.0020539980 0.0000226326 0.0000647030 0.0001176987 0.0000745393 0.0027027027

r WeightingFactor 0.2853585713 0.766 0.2508340231 0.090 0.3338695284 0.072 0.4523977350 1.000 0.2557544757 0.072 0.2000000000 1.000

p with W.F. 0.0020588673 0.0000226100 0.0000645295 0.0001176681 0.0000742391 0.0026666667

r WeightingFactor 0.2853585713 1.2 0.2508340231 0.0 0.3338695284 0.0 0.4523977350 0.0 0.2557544757 0.0 0.2000000000 0.0

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

p with W.F. 0.2 -0.1 -0.3 0.0 -0.4 -1.3

DIGITAL LAB14

Remote laser Welding (RLW) assembly process Simulation Tools: System Configurator

RLW System Configurator © 2009

Simulation Tool: Assembly Layout & Process Estimator Simulation Tool: System Configurator Optimizer 15 Contact:

THE DIGITAL LAB15

Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

RLW System Configurator Simulation Tool: System Configurator Optimizer Brochure – http://rlwnavigator.eu/media/14769/brochures_system_configuration.pdf Animation - https://www.youtube.com/watch?v=agPYrjw-yR0

What is it? •

System-level configuration optimiser, integrated with performance evaluation modules

What does it do? • •

• • •

Precise calculation of system performance, considering resource reliability and buffers. Multi-objective optimisation on:  Production and inventory costs.  Line actual productivity (i.e., OEE and JPH).  Energy consumption.  Cycle times. Generation of a set of optimised candidate solutions (Pareto frontier) Robustness and sensitivity analysis Discrete Event Simulation for candidate solutions

Benefits • • • • •

SUMMARY OF CONFIGURATIONS PRODUCTIVITY

Fast configuration evaluation, to study more potential configuration in less time Actual and detailed line OEE and JPH estimation Connection with reliability databases Detailed and customizable output visualiser Robustness levels for each optimal configuration

© 2009

JLR

TH [PART/MIN] 0,455 ABL(TOT) [PARTS] 3,309 WIP[PARTS] 7,407 JPH[PARTS/HOUR] 27,300 ENERGY N SPOTS 95 N STICH 0 E PART 427500 E HOUR 11678445 WELDING COST CW PART [EU/PART] 1,188 CW HOUR [EU/HOUR] 32,440 INVENTORY COST Ci [EU/HOUR] 0,059 ENERGY COST Ce [EU/HOUR] 0,648 TOTAL COST [EU/HOUR] 33,148 TOTAL COST [EU/part] 1,213 N° ROBOTS 28

REC 1 REV 1 0,4567 1,4897 5,6 27,402

REC 1 REV 2 0,4555 1,4005 5,5 27,33

0,455 1,505 5,6 27,3

REC 3 REV 1 0,457 1,487 5,6 27,42

REC 3 REV 2 0,4563 1,3833 5,49 27,378

0,4606 3,2862 7,4316 27,636

13 59 176500 4836453

13 59 176500 4823745

13 59 176500 4818450

13 59 176500 4839630

13 59 176500 4832217

14 56 175000 4836300

0,863 23,651

0,861 23,531

0,858 23,418

0,858 23,521

0,858 23,485

0,835 23,075

0,0448

0,044

0,045

0,045

0,044

0,0594528

0,268 23,965 0,875 17

0,268 23,843 0,872 16

0,267 23,731 0,869 19

0,269 23,835 0,869 17

0,268 23,797 0,869 16

0,268 23,403 0,847 17

REC 2

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

REC 4

DIGITAL LAB16

RLW System Configurator Simulation Tool: System Level-Configurator



What does it do? • • • • •

Component database

Reliability database

Early-stage design of assembly systems in a designoriented Graphical User Interface Integrated definition of task sequencing and layout Precise calculation of system performance over a large number of alternative configurations Multi-objective optimisation on costs, productivity and number of resources Robustness analysis and Discrete Event Simulation for candidate solutions

Transfer functions

Configuration optimiser

Stations modelling

Optimal system configuration

Integrated platform for system concept generation and configuration optimisation

Assembly Layout and Concept Generator

User input GUI

What is it?

Design input: o Product information o Basic features o Basic KPIs o Resources

Benefits • •

• • •

Faster and integrated system design procedure Fast configuration evaluation to study more potential configuration in less time (1000 configurations, 30 minutes) Actual and detailed line OEE and JPH estimation Connection with reliability and component databases Detailed and customizable output visualiser

© 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB17

RLW System Configurator Simulation Tool: System Level-Configurator Optimizer – V&V

Validation on JLR industry case  System Configurator has been used for the optimization of JLR industry case, consisting in 4 different reconfigurations with hybrid RSW+RLW technologies:  Process speed (+400%)  Overall costs (-30%)  Energy (-60%)  Floor space (-50%)  Number of robots (-40%)

Comparison between analytical and DES Simulation  Provide an estimation of the error incurred by the designer when using the analytical method  Maximum error on throughput: 0,4%  Maximum error on WIP: 1,6%

Validation on other industrial cases 

Test System Configurator to be tailored on specific application and layout:  Case 1: machining and assembly of vehicle engines  Case 2: body-in-white assembly Number of stations

Group of operations

Intermediate buffers

Failure modes

Configurations

Computational time

Case 1

23

23

22

147

1500

3 hours

Case 2

3

24

2

18

100

7 minutes

© 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB18

Remote laser Welding (RLW) assembly process Simulation Tools: Workstation Planning and OLP

RLW Workstation Design & OLP © 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB19

Remote laser Welding (RLW) Door assembly process Simulation Tools: Workstation Planning and OLP Brochure – http://rlwnavigator.eu/media/14774/fixture_analyser_and_optimiser.pdf Animation - https://www.youtube.com/watch?v=8BECihm9f5w

What is it? •

A software toolbox that supports the detailed configuration, optimization, automated off-line programming and simulation of RLW workstations.

What does it do? • •

• • • •

Accessibility analysis, feedback to fixture and product design Integrated welding task sequencing and robot path planning for minimizing cycletime Collision detection and avoidance Detailed workstation design Automated off-line robot code generation Simulation of the RLW workstation

Benefits • • • •

Significantly reduced robot programming effort and time First-time-right implementation due to complete calibrated digital model Shortened ramp-up process and accelerated time-to-market Increased throughput and reduced energy demand

© 2009

Contact: 20UKTHE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick,

DIGITAL LAB20

Remote laser Welding (RLW) Door assembly process Simulation Tool: Workstation Planning and OLP – V&V

Computational tests • • •

Real product (LR door) and robot (Comau C4G) ~90 problem instances Benchmarking against single published method

Test results • •

Cycle-time improvement up to 200% No zig-zaging

Successful physical tests at WMG 1. 2. 3. 4. 5. 6.

© 2009

Building the model of the workcell Placement of the fixtures Calibration Simulation Automatic OLP generation Code execution and measurements

Contact: 21UKTHE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick,

DIGITAL LAB21

Remote laser Welding (RLW) assembly process Simulation Tools: RLW Process Optimizer

RLW Process Optimizer Simulation Tool: Part Variation Modeler Simulation Tool: Fixture Layout Analyzer and Optimizer Simulation Tool: Laser Process Optimizer © 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB22

RLW Process Optimizer Simulation Tool: Part Variation Modeler Brochure – http://rlwnavigator.eu/media/14794/part_variation_modeller.pdf Animation - https://www.youtube.com/watch?v=8BECihm9f5w

What is it? •

Software package for virtual modelling of deformation patterns of sheet-metal part/assembly

What does it do? • • •

Generates virtual part or assembly based on part CAD and/or measurement data Variation Simulation Analysis for deformable parts Statistical Process Control (SPC) for surface measurements (cloud of points data) used in stamping process or/and assembly

Benefits • • •

Deviation [mm]

Facilitates design optimisation for improved part and assembly performance Provides an analysis tool for surface measurements (cloud of points data) used in stamping process or/and assembly Facilitates root cause analysis in stamping and assembly processes

© 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

Deviation [mm]

Deviation [mm]

DIGITAL LAB23

RLW process Optimizer Simulation Tool: Fixture Layout Analyzer and Optimizer Brochure – http://rlwnavigator.eu/media/14774/fixture_analyser_and_optimiser.pdf Animation - https://www.youtube.com/watch?v=8BECihm9f5w

What is it? •

Determine clamp location to optimise part to part fit-up geometry

What does it do? • •



Definition and application of design locator strategy Optimisation of clamp position to satisfy joint fitup geometry Optimisation of clamp position to satisfy assembly dimensional quality

• • • • • •

Improved interaction between product and process engineering Reduced engineering implementation cost Reduced fixture design time and engineering design changes Reduction of fixture content and complexity Reduction of installation, commissioning and launch time Improved assembly quality

© 2009

Gap [m m ]

Benefits

Sam pling point

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB24

RLW process Optimizer Simulation Tool: Laser Process Optimizer Brochure – http://rlwnavigator.eu/media/14784/laser_parameters_optimiser.pdf Animation - https://www.youtube.com/watch?v=8BECihm9f5w

What is it? •

Determine optimum parameter selection

laser

welding/dimpling

What does it do? Definition of optimum process parameters (i.e., power, speed), based on defined output criteria:

• •

Maximum joint quality Minimum cycle time Minimum power demand

Automatic identification of feasible process windows Allow process optimisation loop with robot simulation and path planning

Gap [mm] 0.05

0.1

0.2

0.3

1.0

2.0

3.0

4.0

Gap [m m ]

• • •

Speed [m/min]



Sam pling point

Benefits • •

• • •

Improved joint quality Facilitate parameter selection based on process performance Reduced engineering implementation cost Reduced number of process parameter adjustements Reduction of installation, commissiong and launch time

© 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB25

RLW process Optimizer RLW Navigator Test Case Verification & Validation

Result % (Right-First Time)

Measurable result

Tool

(Right-First Time in Design Phase)

Fixture Layout Analyser & Optimiser

Percentage of stitches* with satisfactory gap (based on predicted clamp location)

Laser Process Parameter Optimiser

Coupon trials: percentage of welding trials* with predicted error below 10% Door assembly: percentage of satisfactory stitches** (based on predicted parameters)

Coupon trials

Door assembly

NA

(65/72) - 90%

(245/250) - 98%

(61/72) - 85%

*Number of coupon trials = 250 - **Total number of stitches on door assembly = 72

Stack-up 1 1.40

1.20

1.20

1.00

1.00

0.80 0.60

0.40

0.40 0.20

0.00

TC

BC

Penetration

B-width

Stack-up 2 Predicted KPI

Predicted KPI

1.20

KPI value [mm]

KPI value [mm]

1.40 1.00

0.80 0.60 0.40 0.20 0.00

© 2009

S-value

TC

S-value

TC

BC

B-width

Stack-up 4

Experimental KPI (average)

1.60

Penetration

Stack-up 3

0.60

0.00

S-value

Experimental KPI (average)

0.80

0.20

Penetration

Stack-up 1

Stack-up 3 Predicted KPI

Experimental KPI (average)

KPI value [mm]

KPI value [mm]

Predicted KPI

BC

B-width

Experimental KPI (average)

1.60 1.40 1.20 1.00 0.80 0.60 0.40 0.20 0.00

Stack-up 4 Penetration

S-value

TC

BC

B-width

Stack-up 2

26 THE DIGITAL LAB

RLW Process Optimizer Simulation Tool: Laser Process Optimizer – V&V Result % (‘Right-First Time’)

Measurable result

Tool

(‘Right-First-Time’ in Design Phase)

Fixture Layout Analyser & Optimiser

Percentage of stitches* with satisfactory gap (based on predicted clamp location)

Laser Process Parameter Optimiser

Coupon trials: percentage of welding trials* with predicted error below 10% Door assembly: percentage of satisfactory stitches** (based on predicted parameters)

Coupon trials

Door assembly

NA

(65/72) - 90%

(245/250) - 98%

(61/72) - 85%

*Number of coupon trials = 250 - **Total number of stitches on door assembly = 72

Stack-up 1 1.40

1.20

1.20

1.00

1.00

0.80 0.60

0.40

0.40

0.00

0.00

TC

BC

Penetration

B-width

Stack-up 2 Predicted KPI

Predicted KPI

1.20

KPI value [mm]

KPI value [mm]

1.40 1.00

0.80 0.60 0.40 0.20 0.00

© 2009

S-value

TC

S-value

TC

BC

B-width

Stack-up 4

Experimental KPI (average)

1.60

Penetration

Stack-up 3

0.60

0.20

S-value

Experimental KPI (average)

0.80

0.20

Penetration

Stack-up 1

Stack-up 3 Predicted KPI

Experimental KPI (average)

KPI value [mm]

KPI value [mm]

Predicted KPI

BC

B-width

Experimental KPI (average)

1.60 1.40 1.20 1.00 0.80 0.60 0.40 0.20 0.00

Stack-up 4 Penetration

S-value

TC

BC

Stack-up 2

B-width

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB27

Remote laser Welding (RLW) assembly process Simulation Tools: RLW Process Control

RLW Process Control In-Process Monitoring System @ SmartLaser Simulation Tool: In-Process Weld Quality Evaluator © 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB28

RLW Process Control In-Process Monitoring System @ SmartLaser Brochure – http://rlwnavigator.eu/media/14789/part_monitoring_and_control.pdf Animation - https://www.youtube.com/watch?v=4NMKViGRFYI Concept Design

What is it? •

Sensor hardware integrated into the Comau SmartLaser robot as first in-axis solution (the 1st in-process monitoring for COMAU SmartLaser System)

What does it do? • •

Integrates state-of-the-art sensor technology into the Comau SmartLaser robot Enables the in-process and in-situ acquisition of the desired quality information to evaluate the current quality status

Installation

Benefits •

• •

The current system can be used at the commissioning and production stage of NPI for statistical process control, Root cause analysis (RCA), and process adjustment Retrofit of all existing Comau SmartLaser robots Fully implemented sensor technology for Process monitoring/ control enables continuous compliance to the specific quality standards and improve decision making processes Back reflection

© 2009

Plasma

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

Temperature

DIGITAL LAB29

RLW Process Control Simulation Tool: In-Process Weld Quality Evaluator Brochure – http://rlwnavigator.eu/media/14779/kpi_evaluator.pdf Animation - https://www.youtube.com/watch?v=4NMKViGRFYI What is it? Data Monitoring • Software package for estimation of joint performance (i.e.,

penetration and s-value) using in-line process monitoring data

What does it do?



• •

It takes the most relevant KPIs in remote laser welding and relates them with the signals extracted from the processing area Direct output of weld quality reduces operator’s interpretation errors Closed-loop process adjustment based directly on weld quality is achievable Welding process parameters can be optimised for a specific performance output

Model Development Rep. 1

Gap [mm]

0.05

0.1

0.15

0.2

0.25

0.3

0.4

1.0

Speed [m/min]



2.0

3.0

4.0

No WELD

Benefits • • • •

In-process weld analysis reduces NDT and destructive testing Use of analytical mathematical model automatically linking monitoring data to joint performance Facilitate Statistical Process Control and root cause of joint failure Capability for in-line closed loop process control and adjustment

© 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB30

RLW Process Control Simulation Tool: In-Process Weld Quality Evaluator – V&V Tool

Measurable

Result %

Process Monitoring

Installation of in-axis monitoring system for COMAU SmartLaser

Installed & Tested

Weld Quality Performance Evaluator

Percentage of welding trials* with predicted error below 10%

(56/60) - 93%

*Total number of welding trials = 60

Main achievements • •

Predicted S-value (Average)

Measured S-value (Average)

Good agreement between predicted and measured KPIs S-value has high correlation to signal data (plasma, temperature and backradiation) 16.00%

2.2 speed=2m/min

speed=3m/min

14.00%

speed=4m/min

12.00%

1.8 1.6 1.4

speed=1m/min

Error [%]

KPI value [mm]

2

10.00% 8.00% 6.00% 4.00% 2.00%

1.2 1

© 2009

0.00%

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB31

Remote laser Welding (RLW) Door assembly process Emerging simulation principle

Emerging Principles RESILIENCE

2: Emerging Processes 2: Emerging Processes

2: Emerging Processes

Needed for Zero-defect (Beyond Robustness)

3: Rapid Embodiment of KETs

© 2009

Examples from the RLW Navigator (1) From process SIMULATIONS of IDEAL part SIMULATIONS of Non-ideal parts (2) From TOOLING design for a SINGLE part  TOLING design for BATCH of parts (3) From OFF-LINE MONITORING  IN-PROCESS MONITORING (4) From MONITORING  ROOT CAUSE ANALYSIS + CORRECTION

Laser trajectory optimization In-process Joint Quality Off-line Program for RLW Tooling optimization Laser process optim. Monitoring & Adjustment VSA for Deformable parts In-process part GD&T Quality Monitoring & Adjustment PRODUCTION SYSTEM CONFIGURATION

Production Volume

Parts GD&T

STATION / CELL CONFIGURATION

Cycle Time Throughput

Laser process

PROCESS DESIGN

Process Parameters

Quality as designed

PROCESS CONTROL

Quality

1: KET: Closed-loop Lifecycle  Lifecycle Analytics

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB32

Remote laser Welding (RLW) Door assembly process More information (1)

Ceglarek, D., Franciosa, P., Váncza, J., Erdos, G., Kovács, A., Kim, D-Y., Colledani, M., Marine, C., KogelHollacher, M., Mistry, A., Bolognese, L., Francini, F., Gerbino, S., Agyapong-Kodua, K., Stroud, I., Chryssolouris, C., 2011, “Remote Laser Welding (RLW) System Navigator for Eco and Resilient Automotive Factories,” FoF-ICT-2011.7, No. 285051, URL: http://www.RLWnavigator.eu/.

(2)

Ceglarek, D., Colledani, M., Vancza, J., Kim, D-Y., Marine, C., Kogel-Hollacher, M., Mistry, A., Bolognese, L., 2015, “Rapid Deployment of Remote Laser Welding Processes in Automotive Assembly Systems,” Annals of the CIRP, Vol. 64/1.

© 2009

Contact: THE Prof. Darek Ceglarek and Dr. Pasquale Franciosa , WMG, Univ. of Warwick, UK

DIGITAL LAB33