Push IIoT Data from Sensor to Cloud Without Getting Lost Along the Way

Transcription

1 Push IIoT Data from Sensor to Cloud Without Getting Lost Along the Way Daymon Thompson Local Product Manager N.A.

2 Beckhoff Automation Global Headquarters: North America Headquarters Beckhoff offices worldwide: Sales network worldwide: Verl, Germany Savage, MN (Minneapolis area) 35 countries > 70 countries

3 Beckhoff Automation

4 IoT and Analytics Use Case Goals and Solutions 1. Corporate goals Machine builders End customers 2. Solution strategies 3. Requirements 4. Solutions 5. Solution validation

5 Business Goals of End Users Reduce production costs Increase product quality Efficient production control Minimize production losses Increase competitiveness!!

6 Business Goals of Machine Builders Reduce machine costs Smart machine optimization Optimize production cycle times Optimize energy consumption Efficient machine maintenance Dedicated and predictable Increase machine attractiveness Increase competitiveness!! Develop new business models

7 IoT and Analytics Goals and Solutions 1. Corporate goals Machine builders End customers 2. Solution strategies 3. Requirements 4. Solutions 5. Solution validation

8 Solution strategies More and detailed data Metadata Easy and secure data access Infinite data storage Powerful and scalable tools Location-independent availability High usability High uptime and reliability Easy integration into infrastructure Use of standards

9 IoT and Analytics Goals and Solutions 1. Corporate goals Machine builders End customers 2. Solution strategies 3. Requirements 4. Solutions 5. Solution validation

10 Requirements More detailed data Capture more process data Data transport / exchange Data storage Data analysis Data security MES SCADA/HMI ERP PLCs Factory Floor (Sensors, Actuators)

11 Requirements More detailed data Capture more process data Data transport / exchange Data storage Data analysis Data security MES SCADA/HMI ERP PLCs Analytics on the device Factory Floor (Sensors, Actuators)

12 Requirements Current Solution: central server High hard-/software costs High expertise & staff required High maintenance effort Poor scalability Good security Central server Analytics tools PLCs Factory Floor (Sensors, Actuators)

13 Requirements Modern Solution: Cloud services Low hard-/software costs Little expertise & staff required Low maintenance effort Great scalability Good security Analytics Connectivity PLCs Factory Floor (Sensors, Actuators)

14 IoT and Analytics Goals and Solutions 1. Corporate goals Machine builders End customers 2. Solution strategies 3. Requirements 4. Solutions 5. Solution validation

15 Solutions Cloud Computing [ ] on-demand network access to a pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort [ ] NIST 2011 Different types Public Cloud Private Cloud

16 Solutions Public Cloud Service Provider Leases access to his data center infrastructure out to customers Virtual Machines Web Sites Cloud Services Storage Services Different services, e.g. Communication services Service Bus Analytics Services Storage services Analytics services Examples: Microsoft Azure Computing Services Queueing Services Directory Services Storage Services Amazon AWS Google Cloud Platform PTC Notification Services Analytics Services Autodesk Fusion Connect 16

17 Solutions Publisher / Subscriber Concept with MQTT/AMQP Publisher Public Cloud Connectivity Service Message Queue Subscriber Subscriber Public Cloud Connectivity Service Message Queue Publisher Advantages Devices do not need to know each other decoupling of applications All communication is outgoing easy firewall configuration easy setup in IT infrastructure MQTT/AMQP lightweight, standardized protocols high performance

18 Solutions IP: IP: Firewall Subscriber Connectivity Service IP: Publisher Source IP Source Port Destin. IP Destin. Port TCP reply Source IP Source Port Destin. IP Destin. Port

19 Solutions Publisher / Subscriber concept in a Private Cloud Cloud service can be hosted in company / machine network, too Low firewall barriers with Pub/Sub Message Broker via MQTT/AMQP Only outgoing communication connections Smart Factory MQTT/AMQP Broker Message queue Firewall Firewall 19

20 Amazon AWS IoT Data ingest Data ingest directly from device Primary transport protocols supported for data ingest: MQTT, HTTPS Data format JSON Data ingest AWS IoT IoT rule AWS Lambda Data processing Connect applications to retrieve and process data ingest, e.g. Amazon S3 or an AWS Lambda function TF6710 TF6720 Amazon S3 20

21 Microsoft Azure Stream Analytics Data ingest Data ingest via several services IoT Hub Event Hub Blob storage Data format JSON Input ( Data ingest ) Output ( Sink ) Stream IoT Analytics Hub Stream Analytics Output ( Sink ) Data analytics and visualization SQL-like query language for analysis Easy-to-configure via website Possible outputs ( sink ): 21 Event Hub SQL database Blob storage Power BI... Query Query

22 Smart Devices with MQTT/AMQP

23 IoT Bus Coupler From Sensor to Cloud Communication based on IoT protocols pub/sub principle Configuration via a website Microsoft Azure Certified TwinCAT Analytics compatible 23

24 Solution Strategies Analytics More detailed data Where is the data? Where to perform the analytics? What to do with the data? Easier remote service find failures Predictive Maintenance Machine Optimization Machine Learning

25 Solutions TwinCAT Analytics Run local analyses TwinCAT Analytics TwinCAT Runtime

26 Solutions TwinCAT Analytics Run local analyses Use private cloud computing within your network Private Cloud TwinCAT Analytics TwinCAT Runtime

27 Solutions TwinCAT Analytics Run local analyses Use private cloud computing within your network Use public cloud computing Public Cloud TwinCAT Analytics TwinCAT Runtime

28 Analytics Infrastructure IoT Communication Global Cloud Analytics Storage 202/208/211 End customer n 202/208/211 End customer Local Cloud Analytics Storage 234/236/238 Machine 1 PLC 234/236/238 Machine 2 PLC 234/236/238 Machine builder/ Automation 234/236/238 3 rd Party Analyst Analytics Analytics 3 rd Party Software Storage Storage

29 Analytics Application 1 Tc Analytics Logger Application 2 Tc Analytics Logger Application n Tc Analytics Logger Message Broker Cloud Storage Provider Blob Store Analytics in Controls System IDE Matlab/Simulink Analytics Dashboard

30 Analytics Workbench Analytics Configurator: Choose data by known tools Analysis of online and offline data Generate Post Scope Configurations Extendable with external algorithms 33

31 Analytics Workbench Analytics for Machine Builders! 34

32 Analytics Code generation 24/7 Analytics applications Code generation for TwinCAT runtime based on Analytics PLC library Code will be generate also for Matlab/Simulink extensions Extendable with own algorithms in PLC code

33 Analytics Library for PLC programmers General library with standard algorithms Also usable as standalone PLC library for target systems Functions: Threshold monitoring Counting Timing Analysis: total, min, max and average Life time monitoring Logic Operators RMS calculation State Analysis Energy calculation 246/207/56 TwinCAT Analytics User 36 TwinCAT 246/207/5 Analytics 6 Library Analytics Algorithm C++ TwinCAT Analytics Configurator

34 IoT and Analytics Goals and Solutions 1. Corporate goals Machine builders End customers 2. Solution strategies 3. Requirements 4. Solutions 5. Solution validation

35 Solution Validation / End User Reduce production costs Data analytics for predictive maintenance Higher machine availability Higher machine productivity Increase product quality Data analytics for machine optimizations Better control/prevention of reject parts Efficient production control Location independent data aggregation Optimized production chain

36 Solution Validation / Machine Builder Reduce machine costs Easier and faster engineering for M2M Decreased hard-/software costs High scalability of infrastructure Efficient machine maintenance Ongoing analysis of process data Smart machine optimization Detailed analysis of machine parameters Increased machine competitiveness New business models for custom services

37 Industrie 4.0 easily implemented: with Beckhoff Thank you!