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Open Laser Metal Deposition(OpenLMD)
Jorge Rodríguez-AraújoAIMEN Technology Center, Porriño, Spain
Porriño, 7-12-2016
openlmd.github.io | [email protected] 2
Index
1. Motivation and Innovative Character
2. OpenLMD, modular architecture
3. ROS-based LMD cell integration
4. 3D geometrical monitoring
5. Multimodal monitoring
6. Off-line robot path planning
7. Real-time power control
8. Adaptive LMD path planning
9. Big data registration and analysis
10.Conclusions and future work
Index
openlmd.github.io | [email protected] 3
Motivation and Innovative Character
openlmd.github.io | [email protected] 4
Motivation and Innovative Character
Promising additive manufacturing technique. Parts are built up layer by layer directly from a 3D CAD model.
For repair and direct fabrication of pieces.
Near-net-shape (close to the final shape).
Manufacturing of large metallic parts. The material is directly deposited on the previous surface.
Complex setup and adjustment of parameters. Thermal heating accumulation produces geometrical distortions. Distortions rise in poor dimensional accuracy and defects. Traditional off-line process (with constant parameters)
becomes unsuccessful.
Laser Metal Deposition (LMD)
LMD Issues
openlmd.github.io | [email protected] 5
Motivation and Innovative Character
There are a lot of industrial robotized laser cells. Empower robotized laser cells for effective AM.
Retrofit current industrial facilities. Apply state of the art robotic
software solutions.
Motivation
Robotized Cladding Cell
MotionController
Main Controller
Off-line Path Planning
6-AxisRobot Laser Powder
Feeder
PowerController
FlowController
Innovation
openlmd.github.io | [email protected] 6
Multiprocessing architecture based on message publishing Multi-node and multi-machine Synchronized multimodal data acquisition
Multiple high speed image sensors Process equipment (e.g. robot, laser) and data
RT-control, cloud storage, data analysis, and visualization Common timestamp
High bandwidth multimodal data storage and analysis Thinked for deep learning algorithms
Open Laser Metal Deposition
ROS-based architecture
openlmd.github.io | [email protected] 7
OpenLMD Modular Architecture
openlmd.github.io | [email protected] 8
OpenLMD, modular architecure
CONCEPT
Open-source solution for on-line multimodal monitoring and control of LMD
Modular set of software components. Built on ROS (Robot Operating System)
Interoperability and standardization
Robotics, machine vision, embedded control, machine learning
ROS-based LMD cell integrationIntegration of ABB LMD robotized cell based on ROS.
3D Geometrical Monitoring3D on-line monitoring (point cloud) for LMD robotized cells.
Multimodal monitoringImage-based multimodal monitoring for Laser applications.
Off-line Robot Path PlanningOff-line path planning for robotized LMD automation.
Real-Time Process ControlImage-based asynchronous RT close-loop control for LMD systems.
Adaptive LMD Process PlanningAdaptive path planning for an automatic repair of large and complex metal parts.
Big Data Registration and analysisBig data registration for LMD adaptive parametric control (for Cloud Computing and Deep Learning)
openlmd.github.io | [email protected] 9
ROS-based modular laser cell integration
The PC integrates the interface and modules to command the robot (ROS)
The robot controls all the cell elements
ROS components:
Robot state publisher
Robot command server
ROS-based LMD cell integration
PowderFeeder
Fiber Laser
6-Axis Industrial Robot
PC Controller
Cladding Head
ROS-Driver(ABB Rapid)
Geometrical Cell Description
(URDF)
STATEPUBLISHER
Laser Source(slave)
Powder Feeder(slave)
COMMANDSERVER
PowerSpeed
Powder flow
Motion path
States
Commands
ROBOT
Process parameters
openlmd.github.io | [email protected] 10
On-line 3D scanning
Real –time point cloud registration
Actual metric measurements (mm)
Direct acquisition in robot coordinates
3D geometrical monitoring
Industrial Robotic Laser Cell
ROBOTROS-DRIVER
CAMERAIDS-DRIVER
State Publisher Peak Finder
Robot PoseTool-Camera
Laser TriangulationCalibration
3D ProfileCamera Pose
3D Point CloudWorking Cell Coordinate
Point Cloud Reconstruction
openlmd.github.io | [email protected] 11
Multimodal monitoring
Multimodal Cladding Head
3D System
TachyonMWIR
NIR
Multimodal monitoring approach
Coaxial SWIR/MWIR images (thermal monitoring): NIT microcore (1000fps) [1-3um]
Coaxial NIR images (surface monitoring): CMOS camera (100fps) [830-880nm]
Off-axis 3D system: on-line 3D point cloud scanning (50fps)
MWIR+NIRMultispectral
Imaging
LMD Cell Virtualization
openlmd.github.io | [email protected] 12
Off-line robot path planning
Robot Routine(ABB rapid)
Intuitive robot programming
Automatic generation of robot trajectories
User friendly interface with high level of abstraction
CAD-based off-line programming (no robot programming skills needed)
3D Part Visualization
openlmd.github.io | [email protected] 13
Melt poolgeometry
PI controller(Kp, Ki)
CLADDINGprocess
width
powereSP
PVMicroCore
Close-Loop Control
Real-Time power control
Without control With control
On-line asynchronous laser power control
Closed-loop control
Embedded vision
RT Control Interface
openlmd.github.io | [email protected] 14
Adapts the path to the real geometry
Automatic repair of large parts
On-line geometrical monitoring
Adaptive path planning
Geometrical control
Adaptive LMD path planning
Robotized Laser Cell
Track MeasurementPath Planning
3D Model
Layer Planning Layer Measurement
STL Generation
On-
line
3D Filtering
Initialization(setup)
Scan layer
Depth mapTarget
Depth map Disparity
Data
Layer pathplanning
Layer Path Planning(geometrical control)
Laser Cellsupervisor
Robotized Cell
0 Finished
Repair Job
Adaptive path planning
openlmd.github.io | [email protected] 15
Cyber Physical registration
High throughput (28MB/s) (NIR + MWIR + 3D point cloud+ Robot)
Deep learning capabilities
Data management and analysis (DataFrames)
Feature extraction
Integration of temporal data
Iterative adjustment
Quality diagnosis and
reconfiguration
Process parameters
LMD
Big data registration and analysis
60 GB/h
Cyber Physical Sytem
openlmd.github.io | [email protected] 16
Conclusions
openlmd.github.io | [email protected] 17
Data acquisition Spatial reference sistem and temporaly synchronized
Annalysis Deep learning: features extration
Actuation Real-time laser power control Adaptive path planning
Embedded vision and control systems
Robot
Pose Process speed
3D geometry
Point cloud (<0.5mm)
Multimodal: SWIR/MWIR-NIR
2D melt pool geometry Thermal distribution
and texture
Reconfigurable
Conclusions
Conclusions
Current lines
Modular and reconfigurable
Interoperability
Large parts
Low-cost solution
Scalability
AIMEN – Central y Laboratoriosc/ Relva 27 A
36410 – O PORRIÑO (Pontevedra)Telf.+34 986 344 000 – Fax. +34 986 337 302
Thank you for your attention
Jorge Rodríguez-Araújo | Research EngineerPh +34 986 344 000 | [email protected]
www.aimen.es | [email protected]