Integrating interoperable automation technologies across the IIoT Layered Databus Architecture

Transcription

1 EC HORIZON2020 Project Co-Funded by the European Commission Grant agreement: Call identifier: H2020 FoF Project Start Date: 1 st of October 2016 EC HORIZON2020 Project Co-Funded by the European Commission Grant agreement: Call identifier: H2020 FoF Project Start Date: 1 st of October 2016 Distributed control and simulation platform to support an ecosystem of digital automation developers Factory Automation Edge Computing Operating System Reference Implementation Integrating interoperable automation technologies across the IIoT Layered Databus Architecture Mauro Isaja, Coordinator, Far-Edge Franco A. Cavadini, Coordinator, Daedalus

2 One factory, two problems, two solutions Decentralized control of the factory by means of edge computing Virtualization of the factory automation pyramid Distributed real-time automation of manufacturing equipment Orchestration of interoperable CPS

3 IIRA integration pattern: the Layered Databus ENABLES: Connected Factories COMMUNICATES: Public Internet DEPLOYED: Enterprise / Cloud Systems-of-Systems Systems Enterprise LAN Unit LAN Factory Plant Machines Station Internal Bus

4 IIRA integration pattern: the Layered Databus

5 The Far-Edge architecture according to the Layered Databus pattern Automation Stack Analytics Stack Enterprise / Cloud System-of-Systems Factory System Plant Machine Station

6 The Far-Edge architecture according to the Layered Databus pattern Automation Stack Analytics Stack Open API for Automation Open API for Analytics Enterprise / Cloud System-of-Systems Secure State Sharing Factory System Machine Edge Analytics RTE Data Stream Connectivity Plant Station

7 Daedalus and real-time orchestration of intelligent devices and machines Industrial Internet System of Systems Cloud Enterprise LAN Specific hard requirements: Data timeliness is critical (real-time); Failure has severe consequences; Non-stop operations; High technical and economic scalability; Performance-driven; Strong safety requirements; Strong security requirements; Systems Machines Unit LAN Segment Unit DataBus Unit DataBus Think HMI Think Intra-machine HMI Think Sense HMI Act Intra-machine SenseIntra-machineAct Limits of current technologies: Current PLCs are programmed under a strictly scan-based paradigm; IEC s 5 languages are informatically old ; IEC is not conceived to simplify the development of distributed control applications; No interoperability nor portability;

8 Daedalus and real-time orchestration of intelligent devices and machines Daedalus core is an automation platform compliant with Sensors Cognitive functionalities CPS Actuators Greater productivity in development, deployment and commissioning: Development of a distributed control application through a single IDE Flexible and effective deployment mechanism Event-based programming approach Standard xml export/import schema

9 Daedalus and real-time orchestration of intelligent devices and machines Each CPS is ready to be interconnected with any other system of the automation network Service Oriented Interface Local Services Cognitive functionalities CPS REAL-TIME ANY-TIME Sensors Actuators Direct interaction to the CPS through a service oriented interfacing mechanism Access to relevant process data Access to configuration parameter Interaction with the control logic

10 Daedalus and real-time orchestration of intelligent devices and machines Each CPS exposes semantic information to enable advanced services (e.g. optimization, commissioning, etc.) Sensors Service Oriented Interface Semantic Model Local Services Cognitive functionalities CPS Actuators REAL-TIME ANY-TIME Daedalus will evolve to support Plug & Produce Assets can be added/ reconfigured/ removed easily from the production process Assets can expose their identity and their capabilities Management systems can implement discovery mechanisms to support dynamically changing configurations of the manufacturing process

11 Daedalus and real-time orchestration of intelligent devices and machines Operator Station PLC PLC PLC HMI Massflow metering Motor Valve Analog & Digital Sensors actuators Edge Devices Varspeed Motor Pneumatics Motion Image dedection

12 Daedalus and real-time orchestration of intelligent devices and machines Operator Station Router/Switch Information Technology IoT PLC PLC HMI PLC Gateway Massflow metering Motor Valve Analog & Digital Sensors actuators Varspeed Motor Cluster of Edge devices needs Distributed Control Pneumatics Motion Image dedection

13 Daedalus and real-time orchestration of intelligent devices and machines Is distributed control optional? NO Hardware is already distributed, Software has to follow It is the main requirement in Industry 4.0 (Modularity, Cyber Physical Systems) IIoT needs clusters of Distributed Edge Devices Complexity More Object & Aspect orientation needed Reusability Portability (XML) Scan-based PLCs induce Aliasing & Syncronity that can t be solved by TSN, DDS or any other Real Time COM (Event) based PLCs create a clear context between Data & Execution

14 Synergy by means of interoperable interfaces Automation Stack Analytics Stack Enterprise / Cloud System-of-Systems Factory System Plant Machine Arrowhead FB Data Stream Catalogue API Station

15 Synergy by means of interoperable interfaces Systems XML file network Automation development tool Web-socket server Configuration of the CPS network AH-to gateway HMI network adapter SO communication service to DDS gateway IEC IEC IEC network MODBUS link

16 Daedalus and Far-Edge: a joint roadmap Joint document of interface specifications Ø Q4 2017? Joint dissemination event Ø Q2 2018? Separate development and unit testing Ø Q4 2018? Joint work on CPS demonstrator Ø Q2 2019? Collaboration on exploitation planning

17 Focus on: joint effort on CPS demonstrator Every module of the new mechatronic cell will have embedded computational power and its own control intelligence A supervisory intelligent system will guarantee coordination of all modules Databus Mechatronic conception of the cell will follow the modular approach, to guarantee scalability at configuration stage Advanced human-machine interaction will be achieved through cobot systems and managed by advanced interfaces

18 Focus on: joint effort on CPS demonstrator Data stream connectivity and Edge analytics exploits the CPS paradigm to create new functionalities and enable vertical integration across the factory automation layers ArrowHead Databus The direct interfacing with each CPS controller enables advanced and decentralized data gathering

19 Focus on: disseminating and involving industrial parties Objectives of the event (to be confirmed!): Comparing projects approaches to most advanced industrial SoA; Link to real operating conditions, requirements and constraints; Highlight potential advantages to industrial stakeholders; Round table discussions about a few key topics for Factory Automation in I4.0 (i.e.: distribution, security, interoperability, standardization, etc.); 1. Identify a reference industrial domain to represent the most advanced of SoA (candidate: ceramic tile manufacturing); 2. Map projects technologies on scenario specific requirements and show improvements; 3. Select specific hot topics for cross-project discussion and industrial stakeholders involvement

20 For further questions Franco A. Cavadini, Coordinator, Synesis Mauro Isaja, Coordinator, Engineering