Digitale Transformation in der Landwirtschaft - Landtechnik im Wandel des 21. Jahrhunderts

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Amie Mabel Phelps
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1 Digitale Transformation in der Landwirtschaft - Landtechnik im Wandel des 21. Jahrhunderts Thomas Herlitzius TU Dresden Professur Agrarsystemtechnik Dresden, 19. Oktober 2016 simul+ Forum Landwirtschaft 4.0 in Sachsen

Technology drives Productivity Today high performance agricultural machines establish

which expands engine power, weight & size.

become smarter by yet immature Process Automation Internal System-and Process Control

2 Technology drives Productivity Today high performance agricultural machines establish productivity by growing working width, higher operational speed, larger storage volumes, which expands engine power, weight & size. weight and dimension now are becoming a major limitation (NA, EU) Source: Claas Machines become smarter by yet immature Process Automation Internal System-and Process Control Machine Fleet Management Process Chain Control Autonomous Machine Control Source: John Deere Source: Horsch Oct 2016 Agriculture Systems & Technology -2-

3 Evolution to Smart & Connected Source: Roland Berger Consultants Oct 2016 Agriculture Systems & Technology Slide 3

Future information and communication technology could change agricultural production processes in a unprecedented way 5G mobile communication Mobile/Cloud

4 Future information and communication technology could change agricultural production processes in a unprecedented way 5G mobile communication Mobile/Cloud Computing Smart Phones, Tablets Internet of Things automated data exchange between devices location based monitoring GIS information, UAS Big Data Linked Open Data

5 Network Coding Multi-Path Latenz Mesh Datenrate Network Slicing ICN/CDN Heterogenität Compressed Sensing Ausfallsicherheit 5G Machine learning Air Interface Massiv Sicherheit Mobile Edge Cloud SDN/NFV

Evolution of Machines from embedded to cyber physical systems increasing complexity Embedded System e.g. hitch controller communication wall between machine system and the world Controllernetzwerk e.

6 Evolution of Machines from embedded to cyber physical systems increasing complexity Embedded System e.g. hitch controller communication wall between machine system and the world Controllernetzwerk e.g.traktor-implement - ISO-Bus Cyber-Physical System e.g. M2M, Telematics Vision: Internet of Things Data & Services Oct 2016 Agriculture Systems & Technology -7-

7 Challenges in Agri-Business productivity peak performance process quality cost of ownership connectivity sustainability resource recirculation biodiversity Oct 2016 Agriculture Systems & Technology -9-

Porter is a University Professor at Harvard, based at Harvard Business

8 How Smart, Connected Products Are Transforming Competition Harvard Business Review Michael E. Porter is a University Professor at Harvard, based at Harvard Business School in Boston James E. Heppelmann is the president and CEO of PTC Oct 2016 Agriculture Systems & Technology Slide 10

Definition Cyber Physical System Definition Edward A. Lee, 2008 [1] : Cyber-Physical Systems (CPS) are integrations of computation with physical processes.

9 Definition Cyber Physical System Definition Edward A. Lee, 2008 [1] : Cyber-Physical Systems (CPS) are integrations of computation with physical processes. Embedded computers and networks monitor and control the physical processes, usually with feedback loops where physical processes affect computations and vice versa. Acatech research agenda, 2012 [2] : Connection of physical system with information technology utilizing open global networks (e.g. Internet) Typical examples Smart Grids, Car-to-X [1] Cyber Physical Systems: Design Challenges, E. A. Lee, Technical Report No. UCB/EECS ; [2] Integrierte Forschungsagenda Cyber-Physical Systems, Acatech 2012; Oct 2016 Agriculture Systems & Technology -13-

10 Definition of mobile cyber-physical systems current automation structures CPS based automation farm operation level process level application level Internet Oct 2016 Agriculture Systems & Technology -14-

Definition of mobile cyber physical systems Connectivity

infrastructure systems of machines Systems of systems

centered Future creation of added value takes place with

11 Definition of mobile cyber physical systems Connectivity machine to machine machine to human machine to infrastructure systems of machines Systems of systems Automation New business models Security and safety Human centered Future creation of added value takes place with many and in real time communicating players in closely connected networks. Roland Berger Strategy Consultants / BDI, 2015 DIE DIGITALE TRANSFORMATION DER INDUSTRIE Oct 2016 Agriculture Systems & Technology -15-

12 Autonomous systems in agricultural environments Robust and economical viable automation is pre-condition for autonomous systems Problem of automation in biobased value chains: many disturbances and strong variation of inputs lack of sensors and process knowledge huge diversity of machines and execution of processes enterprise potential of improvement car manufacturing process machine component mobile machines in agriculture, forestry and construction automation level: low assisted full Griepentrog (2015), modified Oct 2016 Agriculture Systems & Technology -16-

13 Cost Vision of systems of machines towards robotic swarms Productivity, Customer Value Oct 2016 Agriculture Systems & Technology -17-

14 World of robotics AGRICULTURAL AND FORESTRY ROBOT European Robotics Technology Platform: Robotic Visions to 2020 and beyond The Strategic Research Agenda for robotics in Europe, 07/2009 (second edition) Oct 2016 Agriculture Systems & Technology -18-

15 Technology roadmap for developments driven by enhanced connectivity Source: Roland Berger Consultants Oct 2016 Agriculture Systems & Technology -19-

transporting sensors and navigation (*) durch die BLE gefördertes Projekt Partner: Hochschulen Osnabrück.

16 Example elwobot * Model range of a robotic platform for vine and fruit with standardized tool interfaces modularized components chassis and drives application and tools 1. spraying 2. mulching 3. cutting / pruning 4. transporting sensors and navigation (*) durch die BLE gefördertes Projekt Partner: Hochschulen Osnabrück. Geisenheim, TU Dresden, Raussendorf, Obstland Sachsen, Weingut Schloss Proschwitz Oct 2016 Agriculture Systems & Technology -20-

Communication Technology as Enabler Connectivity machine machine human machine machine - infrastructure Robotics & Automation navigation autonomy of machine fleets Telematics Digitalisierung/Big Data

17 Communication Technology as Enabler Connectivity machine machine human machine machine - infrastructure Robotics & Automation navigation autonomy of machine fleets Telematics Digitalisierung/Big Data analysis & forecast climate, soil process optimization remote operation and surveillance Sensorik characteristic process data stationary In-Field-Sensors image processing bird view images UAV airborne sensors Bio-Engineering assistance systems Seed selection Seeds transformation based on field data analytics Oct 2016 Agriculture Systems & Technology -21-

18 Swarm vision for tillage and seeding autonomous implement modules virtually connected to leader Swarm vision for grain harvest autonomous combine modules supervised from operator at site

19 Willkommen in der neuen Welt der Cyber-Physikalischen Systeme

INDUSTRY 4.0. Modern massive Data Analysis for Industry 4.0 Industry 4.0 at VŠB-TUO

INDUSTRY 4.0. Modern massive Data Analysis for Industry 4.0 Industry 4.0 at VŠB-TUO INDUSTRY 4.0 Modern massive Data Analysis for Industry 4.0 Industry 4.0 at VŠB-TUO Václav Snášel Faculty of Electrical Engineering and Computer Science VŠB-TUO Czech Republic AGENDA 1. Industry 4.0 2.