Accelerating Smart Manufacturing with Connected ... Accelerating Smart Manufacturing with Connected

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  • Accelerating Smart Manufacturing with Connected Machine Services

    從智慧機械到智慧製造

    Deh Hui Chuan / Andy Li

    Strategic Engagement & Industrial IoT

    Azure IoT R&D

  • Myth# 1: Manufacturing plants are standardized and homogeneous…

  • Reality: There are many protocol and HW to deal with and there is no winner in this war…. In short, the Brownfield

    No winner in the field bus/industrial

    ethernet war!

  • Myth#2: We just need to focus on building our next future factory…. Why do we still need brownfield?

  • 1960s - 1970s 1980s 1990s 2000s 2010s

    1968

    1978 1989 1993 2001

    1982 19951973 2002 2009 2011

    2006

    2018

    Reality: You invested in various protocols and HW/SW over time…

    1940s-1960s: 1st- 3rd gen NC

    1961: 1st robotic arm by Unitec

    1950s: 1st SCADA appears to work

    with telephone relay

    system….

  • Myth#3: I just need an end to end vendor to help me out in my entire manufacturing value chain….

    Raw materials

    Manufacturing plant Engine transportation

    Engine tracking

    Machine processingMachine transportationProduction line Machine tracking

    Machine assembly

    Machine transportation

  • Microsoft Azure enables scale through IoT PaaS services

    ▪ Azure enables Top 10 automation companies to leverage secure-by-default Azure IoT PaaS and focus on value creation

    ▪ Azure partners with builder ecosystem to offer predictive maintenance solutions, bundled with machines

    ▪ Azure enables manufacturers to focus on process optimization through digital transformation

    Automation Companies Machine Builders ManufacturersGateway and SI

    • Azure leverages specialized solutions integration to focus on process optimization; connectivity specialist for OT/IT interoperability.

    Reality: There will be an ecosystem of experts that comes together in support of your value chain…

  • The Top Automation Companies today run on Azure IoT…

  • Azure-Powers up most Industrial IoT Edge Gateways and Solutions in Market today…

  • Myth#4: Let’s build some dashboards, AI models and have my Connected Factory up & running today!

    Connected

    Factory as a

    Service

    Result

    Digital

    Feedback

    Loops,

    Method Calls

    Adaptability

    AI Models,

    Machine

    Learning

    Predictions

    Time-

    Series/Historic

    al Data,

    Hierarchical

    Data Modeling

    Transparency

    Telemetry

    Dashboards

    VisibilityConnectivityComputerization

    Value

    Time

  • Reality: 7 step journey in Digital Transformation, you can always leapfrog but have you solved Steps 1-2? (Connected Machine)

    Connected

    Factory as a

    Service

    Increased Business Value

    Optimized processes

    Result

    7

    Digital

    Feedback

    Loops,

    Method Calls

    Taking action

    “Self-optimizing”

    Adaptability

    6

    AI Models,

    Machine

    Learning

    What will happen?

    “Being prepared”

    Predictions

    5

    Time-

    Series/Historic

    al Data,

    Hierarchical

    Data Modeling

    Why is it happening?

    “Understanding”

    Transparency

    4

    Telemetry

    Dashboards

    What is happening?

    “Seeing”

    Visibility

    3

    How to Connect?

    “Plugging in”

    Connectivity

    2

    What Data?

    “Defining Tags”

    Computerization

    1

    Value

    Time

    Many are looking to go

    through Steps 1 & 2

    Connected

    Machines first

  • First, it’s Connected Machines, then it’s Connected Factory

    Azure IoT

    ecosystem (to enable brownfield &

    greenfield scenarios)

    Azure IoT

    platform and

    services

    Azure Data

    Platform and

    AI

    Azure D365

    and 3rd party

    providers (SAP, etc.)

    Connected

    Factory as a

    Service

    Increased Business Value

    Optimized processes

    Result

    7

    Digital

    Feedback

    Loops,

    Method Calls

    Taking action

    “Self-optimizing”

    Adaptability

    6

    AI Models,

    Machine

    Learning

    What will happen?

    “Being prepared”

    Predictions

    5

    Time-

    Series/Historic

    al Data,

    Hierarchical

    Data Modeling

    Why is it happening?

    “Understanding”

    Transparency

    4

    Telemetry

    Dashboards

    What is happening?

    “Seeing”

    Visibility

    3

    How to Connect?

    “Plugging in”

    Connectivity

    2

    What Data?

    “Defining Tags”

    Computerization

    1

    Value

    Time

    Connectivity: Open,

    Secure and Extensible

    Standard – OPC UA

    Edge Computing

    OEE: Remote Monitoring,

    Predictive Maintenance

    Quality Control: AI for

    Defect Inspection

    MES/ERP Integration

    Process Optimization

    Adaptive AI for Mfg

    ActionsThings Insights

  • … so let’s go back to that thing call Brownfield and let’s figure out how to standardize to OPC UA… but why?

  • VDMA released a Semantic Interoperability/ Companion Specs guidance to various industries

  • But you haven’t told me why standardize? Well…. What if everyone spoke different languages… how do you draw insights looking at different data models?

    Connected

    Factory as a

    Service

    Increased Business Value

    Optimized processes

    Result

    7

    Digital

    Feedback

    Loops,

    Method Calls

    Taking action

    “Self-optimizing”

    Adaptability

    6

    AI Models,

    Machine

    Learning

    What will happen?

    “Being prepared”

    Predictions

    5

    Time-

    Series/Historic

    al Data,

    Hierarchical

    Data Modeling

    Why is it happening?

    “Understanding”

    Transparency

    4

    Telemetry

    Dashboards

    What is happening?

    “Seeing”

    Visibility

    3

    How to Connect?

    “Plugging in”

    Connectivity

    2

    What Data?

    “Defining Tags”

    Computerization

    1

    Time

    Insights

  • … and that is why Azure Industrial IoT is built for open-ness and interoperability.

    Presentation & Business Connections

    Websites, Mobile Services

    Dynamics, Notification Hubs

    Azure Edge Analytics,

    Azure ML on Edge,

    Azure Functions,

    Azure Edge Runtime

    Azure Edge Analytics,

    Azure ML on Edge,

    Azure Functions,

    Azure Edge Runtime

    Azure IoT Edge

    On-Premises: Machine Interoperability Azure Cloud: Data Ingestion & Processing, Command & Control Azure Cloud: Presentation

    In du

    st ri

    al D

    ev ic

    es (O

    PC U

    A S

    er ve

    rs )

    Hot Path Analytics:

    Azure Stream Analytics, Azure Time Series Insights…

    Azure IoT Hub

    Connected Factory Solution Accelerator:

    OEE, KPIs calculation

    Alarms, Events & Telemetry based on OPC UA Information Model

    Cloud-based Device Management

    OPC Client using OPC UA .NET Standard stack

    OPC Publisher Module

    Firewall

    Cold Path Analytics, ML, Functions & Storage:

    Azure Machine Learning, Azure Data Lake, Azure CosmosDB Graph…

    UA Client/Server

    (UA Binary)

    UA PubSub

    (JSON over AMQP/MQTT)

    Azure Edge Analytics,

    Azure ML on Edge,

    Azure Functions,

    Azure Edge Runtime

    Micro-Services: OPC Twin, OPC Vault

    OPC Twin & Proxy Modules

    UA Client/Server

    (UA Binary) IoT Edge Methods/Properties

    & UA Client/Server (UA Binary over MQTT)

  • Hard truths summarized: Industrial IoT is after all NOT Consumer IoT

    Manufacturing

    environment is

    complex by nature

    • Long life cycles to

    modernize

    machinery

    • Isolated business

    processes

    • Security and liability

    challenges

    Integrations and

    platform

    • Machines cannot

    easily be replaced

    ($$$)

    • Must run for over

    20 years or more…

    Interoperable

    • Must be

    interoperable to

    avoid vendor lock-in

    Complex Ecosystem

    • Require ecosystem

    to optimize

    automation

    processes and

    enable new

    business models

  • Use case sharing

  • ▪ Producer and distributor of specialized plastics

    ▪ Five production sites

    ▪ Each site has two to six extruders

    Use Case

  • ▪ Samples are analyzed for quality control,

    every two hours

    ▪ Cost