Mar 26, 2015 - Easier management of all data needed for line design within the ..... desired quality information to evaluate the current ... Lifecycle Analytics.
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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