Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Tech Review: Digital Platforms and Reboot

104 views

Published on

In this tech review presentation, Erkki Siira from VTT analyses the state-of-the-art in IoT platforms, and opens the Reboot strategy for Proof-of-Concept scaling through platform integration.

Published in: Technology
  • Be the first to comment

  • Be the first to like this

Tech Review: Digital Platforms and Reboot

  1. 1. 14.2.2019 Reboot IoT Factory Digital Platforms and Reboot Erkki Siira, VTT rebootiotfactory.com
  2. 2. Current situation – a word cloud 2 IFS SAP Adafo Oracle Predix Azure LeanWare KepWareI Dassault systems Enovia ThingSee SalesForce Rockwell In-house solutions AWS Legacy systems
  3. 3. What future will bring RAMI 4.0 FIWARE Industrial Data Space IIRA IIoT PlatformsData economy Cloud AI, ML, Analytics Robotization Adaptive intelligent applications Legacy systems Industry 4.0
  4. 4. Hierarchy of Systems  ISA-95 model  Model for enterprise systems / automation systems  Background in Purdue model from 80s  Era of proprietary systems and slow connections  Ongoing discussion how (and if at all) Industrial IoT platforms are flattening the ISA-95 and making it obsolete 4
  5. 5. IDS – Industrial Data Space  A German-led initiative for peer-to-peer data sharing in industrial context  Data ecosystem and market place  Incl. data privacy and security (European regulations)  Business models for data creators  Aims for data sovereignity  Allow companies to exchange information and still stay in control of their data  All actors and technical components are (to be) certified  Five basic roles  Technical implementation of the whole IDS vision is not yet complete 5
  6. 6. Main building concepts of IDS 6Copyright: Thorsten Huelsmann 2018
  7. 7. 7 Fraunhofer-Gesellschaft 2016
  8. 8. FIWARE  Background in EU H2020 project  Aims to solve the problem of data in silos  Already 500 million euro investments (private/public) to FIWARE  Smart Cities, Smart AgriFood, Smart Industry, Smart Energy as main focus areas  Curated framework of open source platform components  Interoperability in context data level  Tries to solve the IoT interoperability in context level and not in standards level  Data economy and monetization  EU has had a big push towards FIWARE  Incl. Demanding use of FIWARE in public funded research projects 8
  9. 9. FIWARE reference architecure with major General Enablers 9
  10. 10. Future of FIWARE  A thriving community around FIWARE  Open source community, start-ups, global corporate companies  Open data models and APIs to avoid vendor lock-ins  Is sharing the vision with Industrial Data Space (IDS)  IDS architecture may be actualized by using FIWARE components  In future FIWARE, Industrial Data Space, Industrie 4.0 and Industrial Internet Consortium are working to align their work 10
  11. 11. IoT Platforms  There are lots of IoT plaforms available  From leading global IT companies to start-ups  Market is expecting consolidation  Industrial IoT is a subset of IoT  Basically connects diverse hardware to the cloud  Background as a middleware but have expanded their functionality  IoT approaches vary in terminology and focus  IIC – Three tier architecture Edge, Platform, Enterprise  Open connectivity foundation – 4 tiers: discovery, data transmission, device management and data management  OneM2M Standard – 3 tier architecture: Network services, common services and application layers  There are light interoperability and cooperation between the platform providers  E.g. MindSphere is using IBM Watson for analytics; and Azure and SAP for cloud infrastructure  Platforms are evolving towards plug-and-play style  Feature comparison of IoT platforms is usually not sufficient as the platforms have same features, need to dig deeper and check the level of service 11 Some major IoT platforms: Siemens MindSphere Amazon Web Services IoT Microsoft Azure IoT SAP Oracle IoT Cisco IoT Cloud Connect IBM Watson IoT ThingWorx IoT GE Predix
  12. 12. Reboot IoT Factory – Approach to platforms  Factory platforms have been identified to support proof-of-concept work  There is a scale-up activity after some proof-of-concepts where PoCs are taken to other factories in the same organization or even to other organizations’ factories in Finland and abroad  To make this scale-up easier and more attractive for companies the platform issues need to be taken care of  Reboot phase 1 plans and pilots the scale-up activities and it will become more systematic and impactful in phase 2  Every PoC is unique and challenges for scaling up are too, but with systematic approach Reboot can help in this 12
  13. 13. Models for scale-up  Versatile interfaces to handle external system communication  Development of wrappers, etc. to handle diversity  Modified PoC for each platform combination  All needed data may not be available, need to adjust the PoC  Choose common platforms and make PoCs to it  Quickest way to get impact if these PoCs are those that interest several factories  Change of the current Factory platforms  Platforms are in constant change and this may open avenues for PoC scale-ups 13

×