RA TechED - DE10 - Simulation and Optimization of Lines using RAPID, Line Balancing and LogixAI
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This document discusses using simulation and optimization tools like RAPID, line balancing, and a LogixAI application to optimize the behavior of a beverage production line. It demonstrates building a digital twin of the line in Emulate3D, using smart tags and the FactoryTalk Linx gateway to extract and analyze real-time data, and employing a LogixAI algorithm to iteratively learn and improve the line balancing over multiple simulations. The goal is to optimize key performance indicators like machine speeds and throughputs.
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RA TechED - DE10 - Simulation and Optimization of Lines using RAPID, Line Balancing and LogixAI
- 1. Simulation and Optimization of Lines using RAPID, Line Balancing and the LogixAI™ Application
- 3. Integrated Architecture® Application Content from Rockwell Automation
- 4. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 4 Agenda Line Balancing Application / Simulation Smart Tags Technology Demonstration of Libraries / LogixAI™ Application Discussion 1 2 3 4
- 5. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 5 This Application was created using standard Rockwell Automation Machine Builder Library Frameworks in combination with a Line Balancing Algorithm and a custom LogixAI™ application Introduction: Beverage Line Application A Beverage Line with 5 machines and 25 conveyors in a Digital Twin (Emulate3D) running at around 700 containers/min. In this demonstration we will optimize the behavior of the line at Design Time to produce better balanced results We employ an AI that is interacting with the user to analyze the process and eventually provides direction and optimization
- 6. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 6 For complex interacting systems such as a mass flow application it is difficult to find perfect adjustments, even at runtime – often it takes weeks for systems to become optimized Session Flow • In this session we will cover • How Emulate3D and Machine Builder Libraries Virtualization are used to build more realistic simulations • How we used Line Estimation and Balancing Technologies in Logix Controllers • How Smart Tags help us extract KPIs from processes • How the FactoryTalk® Linx Information Gateway helps to surface data into a custom LogixAI™ application • How the AI learns in iteration about the process • How we have built Line Optimization in the AI Digitized Models with Smart Tags Machine ID Speed State Conveyor Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Machine ID Speed State Conveyor Conveyor Machine ID Speed State Conveyor Conveyor Machine ID Speed State Conveyor Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Machine ID Speed State Conveyor Conveyor Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Algorithms based on LogixAI™ Simulation in Emulate3D Notification in ViewSE Screens and Pop-Ups Machine Learning and Weighting UI, Dialogs / Selections Process Optimization
- 7. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 7 From around 1.000.000 total Tags and properties in the Application down to 500 relevant tags that are used in the AI, preserving the real- time context and surfacing the equipment structure Relevant data points for a Mass Flow Application To provide tangible process insights to the LogixAI™ application, it is important to extract: • Physical data, • Geometrical data, • Performance data within one cohesive structure In our example more than 500 properties form a digitized picture of the process 10.8 12.110.48.4 6.9 5.4 9.7 12.3 22.522.5 22.5 15.0 41.2 51.0 53.1 54 712 8.3 17.2 15.1 14.2 46 25.8 40.6 55.354.158.7 55.9 62.3 52.7 82 5.0 10.8 12.110.48.4 6.9 5.4 9.7 12.3 22.5 22.5 22.5 15.0 41.2 51.0 53.1 54 xx 8.3 17.2 15.1 14.2 46 25.8 40.6 55.354.158.7 55.9 62.3 52.7 82 5.0 10.8 12.110.48.4 6.9 5.4 9.7 12.3 22.522.5 22.5 15.0 41.2 51.0 53.1 54 712 8.3 17.2 15.1 14.2 46 25.8 40.6 55.354.158.7 55.9 62.3 52.7 82 5.0 10.8 12.110.48.4 6.9 5.4 9.7 12.3 22.522.5 22.5 15.0 41.2 51.0 53.1 54 xx 8.3 17.2 15.1 14.2 46 25.8 40.6 55.354.158.7 55.9 62.3 52.7 82 5.010.8 12.1 10.4 8.4 6.9 5.4 9.7 12.3 22.5 22.5 22.5 15.0 41.2 51.0 53.1 54 xx 8.3 17.2 15.1 14.2 46 25.8 40.6 55.354.158.7 55.9 62.3 52.7 82 xx 10.8 12.110.48.4 6.9 5.4 9.7 12.3 22.5 22.5 22.5 15.0 41.2 51.0 53.1 54 xx 8.3 17.2 15.1 14.2 46 25.840.6 55.354.158.7 55.9 62.3 52.7 82 5.0 10.8 12.1 10.48.4 6.9 5.4 9.7 12.3 22.5 22.5 22.5 15.0 41.2 51.0 53.1 54 712 8.3 17.2 15.1 14.2 46 25.8 40.6 55.354.158.7 55.9 62.3 52.7 82 5.0 10.8 12.1 10.48.4 6.9 5.4 9.7 12.3 22.5 22.5 22.5 15.0 41.2 51.0 53.1 54 xxx 8.3 17.2 15.1 14.2 46 25.8 40.6 55.354.158.7 55.9 62.3 52.7 82 5.0
- 8. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 8 Adding and Preserving Context to Automation Data Smart Tags and FactoryTalk® Link Information Gateway Smart Tags • Implemented as Logix Designer application AOIs, will include documentation and configuration applet • Collects data with context into time-stamped logs as arrays in the controller • Available to select customers via Application Content Libraries • Backward compatible to support existing installed base FactoryTalk® Linx Information Gateway • Discovers Smart Tag in controllers • Associates Smart Tags with corresponding Edge Applications • Can automatically publish definitions, instances and organizational models into PTC ThingWorx applications • Streams data into PTC ThingWorx applications
- 9. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 9 DEMONSTRATION • Emulate3D • Machine Builder Library Virtualization • Line Balancing Application in Logix
- 10. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 10 Line Balancing / Mass Flow Application Logix Controller Line Balancing Algorithm
- 11. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 11 Smart Tag Integration – A digitized Asset Model Line Diameter Height Machine ID Speed State Conveyor Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Machine ID Speed State Conveyor Conveyor Machine ID Speed State Conveyor Conveyor Machine ID Speed State Conveyor Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Machine ID Speed State Conveyor Conveyor Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Machine ID Speed State Conveyor Conveyor Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Machine ID Speed State Conveyor Conveyor Conveyor Sensor1 Sensor2 Speed Volume Machine ID Speed State Conveyor Conveyor
- 12. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 12 The Line Balancing Application at the Gateway will automatically convert the custom model into a legible data stream, which is used by the custom LogixAI™application to analyze the process Custom LogixAI™ Configuration Line Diameter Height Filler Speed Conveyor Conveyor Sensor1 Speed Volume Conveyor Sensor1 Speed Volume Cartoner Speed Conveyor Conveyor Sensor1 Speed Volume TrayPacker Speed Conveyor Using Algorithms based on LogixAI™
- 13. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 13 Line Balancing Machine Learning – ITERATION 1 Machine ID Speed State Conveyor Conveyor Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Filler ID Speed State Conveyor Conveyor TrayPacker ID Speed State Conveyor Conveyor Machine ID Speed State Conveyor ConveyorConveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Cartoner ID Speed State Conveyor Conveyor Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Iteration 1: • User pointed Target KPI to Filler Speed • LogixAI™ Found Conveyor 13 Volume • Time to result: 30 minutes
- 14. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 14 Line Balancing Machine Learning – ITERATION 2 Machine ID Speed State Conveyor Conveyor Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Filler ID Speed State Conveyor Conveyor TrayPacker ID Speed State Conveyor Conveyor Machine ID Speed State Conveyor ConveyorConveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Cartoner ID Speed State Conveyor Conveyor Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Iteration 2: • User pointed Target KPI to Conveyor 13 Volume • LogixAI™ found: Cartoner Stop longer than 40 sec • Time to result: 1 day = 40sec
- 15. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 15 Line Balancing AI Optimization – ITERATION 3 Machine ID Speed State Conveyor Conveyor Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Filler ID Speed State Conveyor Conveyor TrayPacker ID Speed State Conveyor Conveyor Machine ID Speed State Conveyor ConveyorConveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Cartoner ID Speed State Conveyor Conveyor Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Conveyor Sensor1 Sensor2 Speed Volume Iteration 3: • Expanded Production Run Variable Conditions • User pointed KPI to Filler OEE • LogixAI™ found Filler OEE dependent on Speed Cartoner and Speed TrayPacker • Time to result: 7 days
- 16. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 16 We asked the custom LogixAI™ application to predict the amount of Filler Stops against a set of Cartoner / TrayPacker Speeds within a given time Speed Predictions – LogixAI™ application – compared to real results 0 20 40 60 80 100 120 140 160 -12 8 28 48 68 88 108 Filler Hold sherlock
- 17. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 17 Demonstration • Logix AI • Line Speed Changes • Notifications
- 18. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 18 Interactions Indication that updated values from the EdgeApplication are available
- 19. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 19 Application Content sessions at RA TechED™ • SY04 - Studio 5000® Application Code Manager: Introduction and Demonstration • SY05 - Studio 5000® Application Code Manager Project Execution and Library Management: Lab • SY06 - Using Machine Builder Libraries to Enhance Machine Performance by Adopting New Technologies • SY07 - See how the Next-gen Device Library of Pre-configured Faceplate/AOI sets can reduce development time, improve diagnostics and allow application logic reuse. • SY08 - Developing Information Ready Applications using Smart Tags and Rockwell Automation Edge Devices • PR04 - Introduction to the Rockwell Automation® Library of Process Objects • PR05 - Advanced Functionality and New Features of the Rockwell Automation® Library of Process Objects • PR24 - FactoryTalk ® Brew: Designed to help large brewer's succeed • DE10 - Simulation and Optimization of Lines using RAPID, Line Balancing and LogixAI™
- 20. PUBLIC | TechEd | #ROKLive | Copyright ©2019 Rockwell Automation, Inc. 20 Share your feedback Please complete the session survey on the mobile app Select TechEd and login Use your email and last name that you used to register for the event. Click on Schedule on the main menu • Select the session you are attending • Click on the survey tab • Complete the survey and submit 2 3 Download the Events ROK mobile app 1