Notes: (AWS re:Invent 2020 ZCW205) Connected Factory Solution drives Industry 4.0 success


For me as a layman, this Lightning Talk is for the purpose of capturing keywords and major categories. Looking at the wording in the industrial field, the film mainly reads the slides. For those who are already in progress, you don’t need to watch this session. For those who have not yet, you can skip to the end to find a suitable partner to get started faster.

You can consider referring to this official blog article “Connected Factory Solution based on AWS IoT for Industry 4.0 success”, basically the same content, you can take time to watch other sessions.



Connected Factory Solution drives Industry 4.0 success


  • Pugal Janakiraman, AWS Speaker (WW IIoT GTM Specialist Lead, AWS)
  • Prashanth Adiraju, AWS Speaker (Sr. Mgr, AWS IoT Partner Acceleration Team, AWS)



  • Data drives manufacturing transformation
    • By consistently leveraging the value of industrial data, manufacturers can:
      • Reduce product development costs by up to 50%
      • Reduce operating costs by up to 25%
      • Increase gross margins by 1/3
    • Average impact customers are seeing:
  • Implementation challenges
    • Multiple devices (PLCs, SCADAs, RTUs)
    • Multiple protocols
    • OT integration into devices from applications does not scale
    • Lack of single source of truth of data
    • Inconsistent interfacing with OT
    • Systems for similar output
    • Scalability challenges
    • Note: OT = Operational technology
    • Multiple protocols (Note: sort of survey result, from high percentage to low)
      • None
      • Modbus
      • Don’t Know
      • CAN
      • Industrial Protocol (Ethernet/IP…)
      • OPC-UA
      • Profibus, Profinet
      • KNX
      • BACNet
      • EtherCat
      • IEC 60870, 61850
      • Other
      • DNP3
      • FOUNDATION fieldbus
      • Sercos
  • Undifferentiated heavy lifting for
    • Device connectivity
    • Certification of edge hardware
    • IT - OT integration and solution scalability
    • Data visualization across multiple form-factors including mobile devices
  • Vision
    • Enterprise-level visibility
    • Division- and plant-level visibility
    • includes
      • Ingest data to AWS (machine data, quality data)
      • Store data in a time series optimized data store
      • Model assets specify performance metrics for your equipment and processes
      • Visualize live and historical equipment data
      • Deploy ML/AI applications that optimize factory output, product quality, maximize asset utilization, and identify equipment maintenance issues
  • Use Cases
    • Root cause analysis
    • Predictive maintenance
    • Predictive quality management
    • Energy/sustainability solution
    • Digital Twin
      • a digital replica of a physical product, factory, or process
  • AWS delivery approach
    • Proof of value (PoV)
      • Deliverable: Production-ready MVP solution
      • indentification of a plant
      • Discovery workshop with plant
      • AWS PoV proposal
      • Solution prove-out
    • Maturity assessment and roadmap
      • Deliverable: Roadmap and Industry 4.0 maturity assessment report for all plants
      • Top business use cases identification and prioritization (press, forklift, welding, quality, etc.)
      • Maturity assessment of plants for Industry 4.0 readliness
    • Scale-out
      • Deliverable: Detail scale-out proposal for all plants
      • Deployment proposal
  • AWS IoT partner ecosystem for Connected Factory
    • Partner Solutions
    • Deployment partners
    • Edge applications
    • Qualified hardware
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