PLC to Cloud. Changing industrial automation with AWS Sven Goldstein, Product Manager Beckhoff Automation

Transcription

1 PLC to Cloud Changing industrial automation with AWS Sven Goldstein, Product Manager Beckhoff Automation , Amazon Web Services, Inc. or its Affiliates. All rights reserved.

2 About Beckhoff Automation

3 Facts and figures Headquarters: Employees worldwide: Number of engineers: Sales/technical offices in Germany: Beckhoff companies worldwide: Subsidiaries and distributors: Sales worldwide 2015 Sales worldwide 2016 Verl Verl, Germany 3,350 1, countries > 75 countries 620 million (+22 %) 670 million (+8 %)

4 Components for industrial automation The IPC Company The Automation Company The I/O Company The Motion Company

5 Products and system solutions Industrial PC EtherCAT Box TwinCAT Embedded PC Bus Terminal EtherCAT Infrastructure Components Drive Technology XTS

6 TwinCAT automation software PLC, Motion and HMI in one software on one CPU PC-based control offers an open control system PC hardware Abstraction is the key Functions in software independent of hardware Fieldbus TwinCAT software Base: I/O TwinSAFE PLC Control Control (PID) Connectivity Motion NC PTP NC I CNC Robotics Measurement Technology

7 IT challenges

8 IT challenges until 2011 Self-hosting of web server infrastructure became an agony for us (manpower, availability, internet connection, costs) for our customers (delay times, availability) Internet VPN-connected subsidiaries Round-Robin Web Server Web Server FTP Server Beckhoff Headquarters Verl, Germany ftp.beckhoff.*

9 IT challenges - lift and shift to AWS in 2011 Web servers and FTP servers lifted to Amazon EC2 Multiple instances in geographically distributed locations Amazon EC2 Amazon S3 Amazon RDS Faster response times Better availability Faster download speed Less manpower in IT

10 IT challenges - situation now in 2017 Situation now : even more services being used! Amazon EC2 Amazon S3 Amazon RDS Amazon Route 53 AWS Elastic Beanstalk Amazon Cloud Front Amazon SNS AWS WAF

11 Energy data management

12 Energy data mangement requirements Energiedienstleitungsgesetz (EDL-G) Option 1: Energy audit Option 2: Building an energy management system (ISO50001) ISO many things to consider Boards 4000 m2 energy-political (definition of goals) organizational technical I/O 4000 m2 IPC 6500 m2 Drives 2000 m2 Administrative Building and R&D m2 Cabinet 3500 m2 Service 1600 m2 Warehouse m2

13 Energy data mangement approach Where to install energy measuring points? Pareto analysis: find 20% consumers that consume 80% of total energy Resulting areas: Product testing (climatic chamber) Lighting (old T8 pipes) Motors and compressors What to do with measured data? Historical data storage Visualization (live data + historical data) Simple analysis (data correlation)

14 Energy data mangement solution Visualization Amazon EC2 Amazon Kinesis AWS IoT Amazon S3 Amazon Redshift

15 AWS for automation projects

16 Goals of machine builders / end customers Reduce machine costs Smart machine optimization Efficient maintenance windows Increase machine attractivity Reduce production costs Increase product quality Efficient production control Minimize production losses Increase competitiveness

17 Machine data capture and analysis Classic connectivity pyramid data flow Sensor data acquired via PLC (fieldbus) EtherCAT, Profinet, Profibus,... High-speed (µs!) Machine-to-Machine communication Data analysis can occur on the PLC Data analysis on a central server Data analysis on the PLC

18 Machine data capture and analysis This approach has been used for years But problems arised: Hard-/Software costs (server+licenses) Know-How and staff required (IT) Poor scalability (data increase) AWS provides a solution Data analysis Data analysis on the PLC

19 Machine data capture and analysis This approach has been used for years But problems arised: Hard-/Software costs (server+licenses) Know-How and staff required (IT) Poor scalability (data increase) AWS provides a solution What do we need first? à Connectivity??? Data analysis on the PLC

20 Machine data capture and analysis Recap: Energy management project AWS IoT perfectly suited Standardized transport (MQTT) Bidirectional Security via TLS Scalability Rule engine to forward data to eco-system PLC device should be able to send/receive data to/from AWS IoT secure communication via TLS use a standardized transport AWS IoT IoT Rule eco system

21 Standard solutions by Beckhoff Launch: TwinCAT IoT product family Add-On for TwinCAT automation software Supports MQTT (among other protocols) Includes smartphone app (ios, Android) Enables push messages to wearables Enables connectivity with AWS IoT AWS IoT IoT Rule eco system TwinCAT IoT

22 Standard solutions by Beckhoff Launch: EK9160 IoT Coupler Hardware device with analog/digital I/O Supports MQTT (among other protocols) Enables connectivity with AWS IoT Extendable I/O terminals... Easy configuration via integrated website AWS IoT IoT Rule

23 Standard solutions by Beckhoff Launch: EK9160 IoT Coupler

24 Standard solutions by Beckhoff Launch: EK9160 IoT Coupler

25 Standard solutions by Beckhoff Launch: TwinCAT HMI Machine data visualization Supports MQTT (among other protocols) Client/Server, based on HTML5 Extendable framework Connectivity with AWS IoT Installable on Amazon EC2 Amazon EC2 TwinCAT HMI Server AWS IoT Web browser to visualize machine data Web browser (HMI Client)

26 Standard solutions by Beckhoff PoC: TwinCAT IoT Alexa Skill Voice recognition integration for PLC Based on Amazon Alexa Connectivity via AWS IoT PoC for Smart Home and Custom skill AWS IoT Device Shadow AWS Lambda Alexa, ask TwinCAT to turn lights in living room on + Amazon Echo Amazon Echo Dot

27 Summary

28 Summary Beckhoff Automation manufacturer of automation systems Industrial-PCs, drives, motors, I/Os, automation software,... First IT projects with AWS in 2011 (web srv infrastructure) Energy management project based on AWS IoT Standard products for AWS IoT connectivity TwinCAT IoT, EK9160 Visualization for machine data on Amazon EC2 TwinCAT HMI Voice recognition for PLC using Alexa

29 Thank you