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Artificial Intelligence forIndustrie 4.0
The Digital Transformation of Manufacturing IndustriesNew York City, March 06, 2018
Professor Wolfgang WahlsterCEO of DFKI
German Research Center for Artificial IntelligenceSaarbrücken, Kaiserslautern, Bremen, Berlin, Osnabrück
Phone: +49 (681) 85775-5252/4162
Email: [email protected]: http://www.dfki.de/~wahlster
© W. Wahlster
Machine-readable Data: Internet and Cloud Tchnologies
Machine-understandable Data: Artificial Intelligence and Machine Learning
First Wave:Digital Data- Record- Store- Transmit- Process
Second Wave:Digital Data- Understanding- Refining- Active Usage- Monetize
Digitalization „with Rhyme and Reason“
Artificial Intelligence for the Second Wave ofDigitalization
© W. Wahlster
„Understanding” by AI on Digital
Computers
Digital Data
Text
SpokenLanguage
Image
Video
Sensor Data
Physical Reactionof Robots or
Networked Devices
Virtual Reactionfrom Digital Assistants
or Chatbots
Summarization of Texts or
Conversations
Answering Questions Based on Texts, Videos or
Sensor Values
Linguistic Description, of Images or Videos
Digital Understanding: Understanding Digital Data and Understanding with the Help of Digital Systems
Understanding Test: Adequate System Reaction
© W. Wahlster
Towards Intelligent Environments based on the Internet of Things and Services
90% of allcomputers areembedded
5) IntelligentEnvironments
4) Embedded Computers
3) Smart PhoneSmart Card
2000 202019801960
Smart Factory
1) Central Computer2) PC, Notebook
1 ComputerMany Users 1 Computer
1 User
1941
Many Computers, 1 User
© W. Wahlster
AI + Big Data as the Jet Engine forSmart Factories, Products and Services
AI +Big Data
SmartService
SmartProduct
SmartFactory
Three Large-Scale German Future Projects for Disruptive Innovation: Industrie 4.0 – Smart Service World – Learning Systems
© W. Wahlster
After Our Initial Publication in April 2011 the German Term „Industrie 4.0“ was Propagated Exponentially Worldwide
According to GENIOS Data Base of Publications in Germany2010 2011 2012 2013
12.588
0200400600800
1000120014001600
2015
46.305
2016 2018
89.101
© W. Wahlster
Today‘s IT-Environments Boost AI Solutions
Google: From „Mobile First“ to „AI First“
AI
CloudTechnologies
WebTechnologies
BigDataIn-Memory Computing
GPUParallelCluster
MobileInternet
5G
© W. Wahlster
Industrie 4.0 CharacteristicsSemantic Service Matching
Machine Learning
Ontology Engineering
GPU-based Anytime Planning
Deep Learning,Active Sensor Fusion
Semantic Product Memory, Multiagent Architecture
Plan Recognition, User Modelling, IUI
Deep Learning
Multiagent Planning, BDI Architectures
Demand for AI SolutionsMass Customization
Predictive Maintenance
Plug & Produce
Realtime Line Balancing
Online Quality Control
Digital Twin
Worker Assistance
Process Anomaly Detection
Hybrid Teams
AI Technologies for Industrie 4.0 Characteristics
© W. Wahlster
Cars
Home AppliancesAgricultural Machinery
Medical Equipment
Manufacturing Equipment
Disrupting German Economy by Injecting AI: Transforming Premium Products Into Smart Products and Smart Services
© W. Wahlster
Plug&Produce Based on Adaptive Service Ontologies• Plugin of CPS production
components on a physical, digital and semantic level
• Automated Expansion of theService Ontology
New Assembly Component is installed on-the-fly
© W. Wahlster
Digitalization of Brownfield Factories Based on Distributed Intelligence
Example of an augmented industrial scale sending sensor data via an edge device using OPC UA to thelocal cloud for condition monitoring, anomaly detection, and predictive maintenance in DFKI‘sSmartFactory
Edge Devices are used for vertical integration and retrofitting of existing factories
© W. Wahlster
Deep Learning-based Object Recognition on the Job Floor
© W. Wahlster
Intelligent Human-Robot-Collaboration in the Smart Production Lab of Volkswagen in Cooperation with DFKI
© W. Wahlster
Based on GPU Computing for Extremly Large States Bases
fundedby BMBF
in theSmartF-IT
Project
AI-Based Real-time On-the-fly Planning of Hybrid Production Teams (Marcel Köster, DFKI)
© W. Wahlster
AI Enables Human Workers and Collaborative Robots to Use a Dual Toolbox
PneumaticScrewdriver
CordlessScrewdriver
GripperElement
Franka Panda RobotShared Toolbox Worker
Shared Workspaces for Human-Robot Collaboration
© W. Wahlster
AI for an „X-Ray“ View through the Worker‘s HoloLens forTracking Dangerous Actions of Occluded Heavy-Weight Robots
Collaborative ligth-weight robotsworking together with humans on
the interior sideof the fuselage
Heavy-weight robotsworking on the exterior side
of the fuselage
© W. Wahlster
Smart Worker Assistance as a Service: DFKI for Hitachi
© W. Wahlster
The Smart Automation Line of Bosch-Rexroth
Cooperation with DFKI and Power4Production Center in the SmartF-IT Project Source: Bosch-Rexroth
© W. Wahlster
The Spin-Off Company IOXP of DFKI HasRevolutionized the Workflow for AR Presentations
© W. Wahlster
New National Future Project on AutonomousSystems Starting 2016
© W. Wahlster
Robotic Electric EO2 Car of DFKI with Advanced Autopilot (DFKI RIC)
Advanced Autopilot for Merging with other Cars in Road TrainsAdaptable Shape of the Car
© W. Wahlster
Autonomous Driving of 4 Electric Cars as a Road Train
© W. Wahlster
Conclusions• Artificial Intelligence is a key enabler for advanced manufacturing in the
Industrie 4.0 paradigm.
• Condition monitoring, predictive maintenance, anomaly detection, and realtimeline balancing can only be achieved by advanced data analytics, machinelearning and automated planning.
• Semantic interoperability of cyber-physical production systems and digitaltwins enable plug&produce and multiadaptive smart factories, that are based onsemantic technologies and manufacturing ontologies.
• Factory workers will be assisted by a new generation of collaborative robotsand intelligent industrial assistance systems using multimodal dual andaugmented reality.
• Systems based-on long-term autonomy and deep learning go beyond Industrie4.0 and enable autonomous smart factories and autonomous cars as smartproducts.
Design by R.O.
Thank you for your attention
