Industrie 4.0 Chances for robotics and automation Smart U-Meet evening, University of Twente
Twente, 2 October 2014
Laboratory for Machine Tools (WZL), RWTH Aachen Fraunhofer Institute for Production Technology (IPT) Wolfram Lohse Š WZL/Fraunhofer IPT
RWTH Aachen University and Fraunhofer-Gesellschaft Fraunhofer-Gesellschaft More than 80 institutes and establishments at 40 locations in Germany 18,000 employees Research budget of 1.65 Billion €, with 1.4 Billion € contract research 3 institutes in Aachen RWTH Aachen University Founded 1870 About 40,000 students Faculty of Mechanical Engineering 11,700 students (including 1,800 first-year students) 62 professorships 2,600 employees 160 graduates per year © WZL/Fraunhofer IPT
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Production Engineering at RWTH Aachen University Laboratory for Machine Tools (WZL) Institute of RWTH Aachen University Founded in 1906 Approx. 820 employees
(approx. 250 academic staff) 16,000 m² offices and laboratories
Fraunhofer-Institute for Production Technology IPT Institute of Fraunhofer-Gesellschaft Founded in 1980 Approx. 380 employees
(approx. 100 academic staff) 3,000 m² offices and laboratories Partner institute in Boston/USA: CMI Fraunhofer Center for Manufacturing Innovation
WZLforum Knowledge transfer to the industry Organising workshops, training and
seminars © WZL/Fraunhofer IPT
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Our Focus Process Technology Machining and material removal processes Laser materials processing Forming processes CAx, Virtual Reality
Production and Machine Tools Design of production machines and components Control technology and automation Component and production machines testing
Metrology Tactile metrology Optical metrology
© WZL/Fraunhofer IPT
Gearing Technology Gear manufacturing Gear calculation and investigation
Management Business Engineering Technology management Innovation management Production management Quality management Education Professional training Executive MBA for Technology Managers Conferences, congresses, seminars
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Content 1
Industrie 4.0
2
"Plug & Produce" with smart robots
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Smart automation for small batch sizes
4
Conclusion
Š WZL/Fraunhofer IPT
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Industrie 4.0 Virtualization and Cross-linking Industrie 4.0 Internet of Things, Smart Services
Virtual world
PLM
Fusion
Logistics
ERP
Real world
MES
Business processes Technical processes
Controller
Order Transmission Order Processing Order Disposition Performance Provision Invoicing
Resource Selection Track and Technology Planning Control Simulation Physical Simulation Final Post Processing
Semantics, intelligence / autonomy
Virtualization
Finite-ElementModels State Models
Data Models Analytical Models
Cross-linking HMI / MMI PLM/PDM CAx-Chains Clouds Mobile Ubiquitous Devices Computing
Image sources: Daimler, Chiron, WZL Š WZL/Fraunhofer IPT
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Industrie 4.0 “Plattform Industrie 4.0“ – Industrial roadmap for research & innovation New social infrastructures
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New business strategies
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Framework Value-Added Networks
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Automation of value-added networks
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Industrie 4.0 by design
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Integration of real and virtual world
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Systems Engineering
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Sensor data analysis
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Intelligence / flexibility / adaption
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Multimodal assistance systems
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Technology acceptance / workplace design
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Wireless communication for I4.0 scenarios Horizontal integration Security & Safety of value-added networks CPS platform
© WZL/Fraunhofer IPT
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micro-electronics
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12
10
11 Basis technology of ICT and 12
Basic technologies 11
2035 2025 5
2018 6
2015
4 3 2 1 8
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Vertical integration and cross-linked production systems
Engineering continuity / consistency along the entire lifecycle
Source: Plattform Industrie 4.0 Seite 7
Industrie 4.0 The Aachen Perspective cyber
Single Source of Truth ERP systems
IT Globalisation
PLM/Engineering systems
Big Data Assessing and Storage in the cloud Data mining, safety, security High Speed Computing 4th Industrial (R)evolution
Local data storage
Collaboration productivity - Human / Human - Human / Machine - Machine / Machine
physical
Cooperation
Software © WZL/Fraunhofer IPT
Business Communities Social Communities
Cognitive System
Adaptation by sensors Intuitivity, reliability IT-Openness Cost-efficiency Robustness
Automation
Hardware Seite 8
Industrie 4.0 Cross-linking in production systems Cross-linked levels of production Automation technology ERP
Planning level
MES Control level Cell control
Today: (Rigidly) clocked automated production and assembly Manual operations
Cell level NC, RC, PLC Controller level Input/Output signals Field level
Vision: Plug & Produce for flexible processes Efficient process control, also for small batch sizes
Process © WZL/Fraunhofer IPT
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Content 1
Industrie 4.0
2
"Plug & Produce" with smart robots
3
Smart automation for small batch sizes
4
Conclusion
Š WZL/Fraunhofer IPT
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"Plug & Produce" with smart robots Flexible automation with human-robot cooperation Flexibility / Plug & Produce Mechanical interfaces
Electrical interfaces
Controller interfaces
Ramp-up / restart “Skin” of robot with capacitive, contactless
proximity sensors Activation distance of approx. 50 mm No additional safety equipment required,
certified by the German Berufsgenossenschaft (BG) Task-oriented programming for fast process
ramp-up
Reduced time for ramp-up / setting-up © WZL/Fraunhofer IPT
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"Plug & Produce" with smart robots Flexibility by sensors – „Bin Picking“
Optical data acquisition and evaluation
Object identification and part selection
Complex interaction between – 3D image recognition software – Robot – Machine Control Advantage: Chaotic buffering of workpieces Drawbacks: Lack of determinism in output rate,
Collision-free removal of parts
Critical analysis of required quantity, productivity and process change flexibility
productivity Image source: Liebherr, IPA © WZL/Fraunhofer IPT
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"Plug & Produce" with smart robots Reducing ramp-up efforts with multimodal interfaces Einschraubverbindung
Durchsteckverbindung
Assembly design Geometry models, Assembly features, Assembly relations
Virtual process planning
“Process interface”
Process Prozess
Process modelling “STEP Assembly”
Specification: automated process
Manual demonstration, Job list Assembly automation
© WZL/Fraunhofer IPT
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"Plug & Produce" with smart robots Acquisition of assembly operations “Kinect” sensor
Tool magazine “Leap Motion” sensor
Assembly group Assembly parts
© WZL/Fraunhofer IPT
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"Plug & Produce" with smart robots Machine-robot integration – Multi-technology platform Laser safety enclosure with active detectors
Integrated, sealed and rotating robot enclosure
Main spindle for milling, laser patterning and laser hardening
Media supply of the laser heads with subsequent positioning and length adjustment
Magazine for laser units Robot with laser head for laser cladding and laser hardening
Equally accessible work spaces with rotary tilting tables
Š WZL/Fraunhofer IPT
Integrated control panel for all machine components
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"Plug & Produce" with smart robots Machine-robot integration – Spectrum of integrated technologies
Š WZL/Fraunhofer IPT
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"Plug & Produce" with smart robots Vision: Simultaneous machining with two tools Machine tool: milling – Machine main spindle Machine spindle – Cartesian-serial kinematics (X / Y / Z) for tool movements – Rotational movements via rotary tilting table Workpiece RotaryTilting-Table
Robot: deburring – Deburring spindle – Six axes Process planning – Approach 1: master-slave path – Approach 2: simultaneous path planning Collision avoidance (offline / VNCK,
possibly online) Interpolated motions set by NC
controller (master) – Motion correction – Compensations (thermal, wear, …) © WZL/Fraunhofer IPT
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Content 1
Industrie 4.0
2
"Plug & Produce" with smart robots
3
Smart automation for small batch sizes
4
Conclusion
Š WZL/Fraunhofer IPT
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Smart automation for small batch sizes On the way to intelligent, model-based production control Conventional Production Control
Challenge Mass Customization
Intelligent, model-based Production Control Specification „what“ the target of production is
Specification „how“ production has to be carried out Alternative process sequences Procedures and processes as central, stringent sequences of instruction
Different efforts Alternative process parameter Multi-criteria optimization
Suitable for durable process chains in mass production
Information / objectives embedded in workpieces and production means Decentralized, semi-autonomous control units
Short product lifecycles Mutability
Flexibility in procedure and process changes
Individualised products Image Sources: Siemens, WZL © WZL/Fraunhofer IPT
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Smart automation for small batch sizes Viable MES for multi-dimensional optimisation of production ERP
MES
Optimisation of throughput time
Production line
Multi-level optimisation Object-oriented communication model
VSM Level 1
Cell 1
Cell 2
VSM Level 2
Common product and process model Machine 1 VSM MES ERP OPC UA
Viable Systems Model Manufacturing Execution System Enterprise Resource Planning Object Linking and Embedding Unified Architecture
Š WZL/Fraunhofer IPT
Optimisation of energy consumption
Machine 2
Machine 3
VSM Level 3
Combination of centralised and decentralised optimisation
(IT) plant topology of Viable MES
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Smart automation for small batch sizes Production control with semantic interpretation of product models Conventional control Printer Control Unit Manual requirements/ rigid specification of order data
Print image, position, orientation, target element
MES reads in the print job with order data
Control based on product models Modeling of product and plant functions
Semantic product model
MES reports provision of building elements to printer Š WZL/Fraunhofer IPT
Triggers Print Job
Response to MES
Suitable for fixed data flows
Printer Control Unit
Flexible changes of data interfaces
Product model (Data source) Model interpretation Function model (Action and data needs)
Triggers Print Job
Response to MES
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Smart automation for small batch sizes SmartFactoryAC – Individualised Production Injection molding process with stem-form
Planning level
Customer Standard part
Order dispatching
Product design Guidance level
ERP MES
Cell level Control level Field level
Manufacturing / production process
Process level
Individualized manufacturing
Assembly RFID-Tag Š WZL/Fraunhofer IPT
Pre-palletizing
Transport to printer
Individual color printing
Component assembly with robot cell
Cube assembly with FlexPicker Seite 22
Smart automation for small batch sizes Cognitive control for assembly processes Comparison real / virtual
Cell controller Cognitive sequence control Knowledge (models)
Modelling
Objectives
Cognitive architecture Example: Handling and assembly Target model
Simulation
Assembly system Š WZL/Fraunhofer IPT
Cell model
Operation
Paradigm change: Determination of sequences by objective analysis
Connection to automation periphery Product / assembly grp.
Production environment Seite 23
Smart automation for small batch sizes Planning and control of processes in a cognitive assembly cell
CAD Modell Assembly sequences
Cognitive sequential control
Sequence planning Sequence control
Optical tracking and component detection
Part identification
Grasp-planning
Sensory-guided joining
Joining
Geometrical grasp-planning Š WZL/Fraunhofer IPT
Validation
Validation with color and depth information Seite 24
Content 1
Industrie 4.0
2
"Plug & Produce" with smart robots
3
Smart automation for small batch sizes
4
Conclusion
Š WZL/Fraunhofer IPT
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Conclusion
“Industrie 4.0” Chances for robotics and automation Plug & Produce, self-awareness
Semantic models, cognition
Higher flexibility, faster changeovers
Reduced front-loading / engineering efforts
© WZL/Fraunhofer IPT
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