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XMPro Platform
XMPro Platform
  • What is XMPro?
  • Getting Started
    • Browser Requirements
    • Free Trial
    • End-To-End Use Case
  • Resources
    • What's New in 4.4
      • What's New in 4.3
      • What's New in 4.2
      • What's New in 4.1.13
      • What's New in 4.1
      • What's New in 4.0
    • Blueprints, Accelerators & Patterns
    • Integrations
    • Sizing Guideline
    • Platform Security
    • Icon Library
    • FAQs
      • Implementation FAQs
      • Configuration FAQs
      • Agent FAQs
      • General FAQs
      • External Content
        • Blogs
          • 2024
            • How to Build Multi-Agent Systems for Industry
            • Why Solving the Problem Doesn’t Solve the Problem: The Importance of Scalable Intelligent Operations
            • Content, Decision, and Hybrid: The Three Pillars of Multi-Agent Systems in Industry
            • Revolutionizing Manufacturing with AI and Generative AI: XMPro’s Intelligent Business Operations Sui
            • The Evolution of Skills: Lessons from Agriculture in the GenAI and MAGS Era
            • Part 1: From Railroads to AI: The Evolution of Game-Changing Utilities
            • Part2: The Future of Work: Harnessing Generative Agents in Manufacturing
            • Bridging Automation and Intelligence: XMPro’s Approach to Industrial Agent Management
            • XMPro APEX: Pioneering AgentOps for Industrial Multi Agent Generative Systems
            • Part 5 – Rules of Engagement: Establishing Governance for Multi-Agent Generative Systems
            • How to Achieve Scalable Predictive Maintenance for Industrial Operations
            • Understanding the Difference Between XMPro AI Assistant and AI Advisor
            • Part 3 – AI at the Core: LLMs and Data Pipelines for Industrial Multi-Agent Generative Systems
            • MAGS: The Killer App for Generative AI in Industrial Applications
            • The Importance of Pump Predictive Maintenance for Operational Efficiency
            • Progressing Through The Decision Intelligence Continuum With XMPro
            • The Value-First Approach to Industrial AI: Why MAGS Implementation Must Start with Business Outcomes
            • New Guide – The Ultimate Guide to Multi-Agent Generative Systems
            • The Ultimate Guide To Predictive Analytics
            • Part 4 – Pioneering Progress | Real-World Applications of Multi-Agent Generative Systems
            • Scaling Multi-Agent Systems with Data Pipelines: Solving Real-World Industrial Challenges
          • 2023
            • How to master Predictive Analytics using Composable Digital Twins
            • Accelerate Your AI Workflow: The 3 Key Business Advantages of XMPro Notebook
            • The Roadmap to Intelligent Digital Twins
            • What is edge computing, and how can digital twins utilize this technology?
            • THE TOP 5 USE CASES FOR COMPOSABLE DIGITAL TWINS IN RENEWABLES + HOW TO SUPERCHARGE RESULTS WITH AI
            • The Technology Behind Predictive Maintenance (PdM) : Hardware & Software
            • The Benefits of Using Digital Twins in Smart Manufacturing
            • XMPro I3C Intelligent Digital Twins Strategy Framework
            • The TOP 5 use cases for composable digital twins in mining – and how to use AI to supercharge result
            • The TOP 5 use cases for Composable Digital Twins in the Oil & Gas industry
            • Why Decision Intelligence with Digital Twins is “kinda like” DCS for Automation and Control
            • XMPro becomes an NVIDIA Cloud-Validated partner
            • From Reactive to Predictive : Introduction to Predictive Maintenance
            • Microsoft Azure Digital Twins : Everything You Need To Know
            • Unlocking Efficiency: The Right Time & Strategy to Launch Your Digital Twin for Enhanced Asset Manag
            • Revolutionize Your Supply Chain: How Digital Twins Can Boost Efficiency and Cut Costs
          • 2022
            • Create a Common Operating Picture of Your Operations with XMPro
            • 7 Trends for Industrial Digital Twins in 2022
            • How to Build a Digital Twin + 60 Use Cases By Industry
            • What are composable digital twins in the metaverse?
          • 2021
            • The Value of a Composable Digital Twin
          • 2020
            • Lean Digital Twin: Part 2
            • Digital Twin: Your Most Productive Remote Worker
            • From the Control Room to the Bedroom
            • Lean Digital Twin: Part 3
          • 2019
            • My Digital Twin: Digital Twin Applications for Real-time Operations (Like Me)
          • 2018
            • XMPro IoT Operational Capability Survey Results 2018
            • What is a Digital Business Platform and Why Should I Care?
            • [Robotic] Process Automation for IoT
            • 3 Patterns of Industrial IoT Use Cases
            • The CXO’s Guide to Digital Transformation – May The Five Forces Be With You
            • Is Security More Important Than Trustworthiness for Industrial IoT?
            • XMPro at bpmNEXT 2018: Watch The Presentation
          • 2017
            • The Top 5 Reasons to Invest in an IIoT Development Platform
            • IoT Business Solutions Start with Big Data & Create Business Outcomes
            • How AI Bots Bring Digital Twins to Life
          • 2016
            • How To Get Started With Industrial IoT
            • How To Overcome The Top 5 Challenges To Industrial IoT Adoption
            • What is an IoT Platform vs. an IoT Business Application Suite?
            • Industrial IoT: How To Get Started with Predictive Maintenance
            • 3 Ways The Internet of Things is Transforming Field Service
            • 7 Types of Industrial IoT Data Sources (And How To Use Them)
          • 2015
            • How Important Are Processes To The Internet Of Things?
            • Understanding the Value of Real Time KPI Management as Your Next Strategic Project
            • 6 Myths About Machine Learning
            • 10 Predictive Analytics Use Cases By Industry
            • What is a “Business Moment” in your business?
            • Does Operational Intelligence Make Business Intelligence Obsolete?
            • How To Reduce Operational Costs by 36% with Predictive Analytics
            • From Many, One – The Nature of Complex Event Processing
            • Herding Cats: What Enterprise Architects need to know about Business Process Management
          • 2014
            • Making Business Operations More Intelligent
          • 2013
            • Best Next Action Is The Next Big Thing For Intelligent Operations
            • The learns from two ‘Best in class’ organisations acquiring BPM technology
          • 2012
            • Why Intelligent Business Operations is Mobile, Social and Smart
            • Why Do You Want Intelligent Business Operations?
            • How big of a problem are ‘dark processes’?
            • Operational Risk: When You Stick Your Head In The Sand
            • The Difference Between Event-based And Workflow-based Processes
          • 2011
            • Is mobile BPM now essential to the business?
            • Stretch Socially Dynamic Processes To Fit Your Business
            • Social Listening – Get Control Of The Conversation
            • Operations Management – The Keys To KPIs
            • Benefits of BPM v 1.0
            • How to Prioritise Processes
          • 2010
            • The Business Drivers
            • Preserving Capability and Agility
            • Mobile BPM
        • Use Cases
          • Aging Pipe Predictive Maintenance in Water Utilities
          • Air Quality Monitoring For Agriculture
          • Alarm Management and Triage
          • Asset Condition Monitoring for Surface Processing Plants in the Mining Industry
          • Bogie Health Monitoring in the Rail Industry
          • Boiler Feed Water Pumps
          • CHPP Throughput Loss Monitoring
          • Casting Guidance
          • Conveyor Belt System Monitoring and Optimization in Automotive Manufacturing
          • Cooling Tower Fin Fan Monitoring
          • Cyclone/Slurry Pump Monitoring
          • Demand Planning to Reduce Stockholding in Stores
          • Demin Water Monitoring for Boiler Tube Corrosion
          • EV Battery Assembly Process Optimization for the Car Manufacturing Industry
          • Flood Prediction & Response in Water Utilities
          • Golden Batch For Culture Addition In The Dairy processing Industry.
          • Golden Batch Monitoring
          • Improve First Pass Yield (FPY)
          • Induced Draft (ID) Fan Monitoring
          • Long Conveyor Monitoring
          • Monitor Process Health to Reduce Cash-to-Cash Cycle
          • Monitor Storm Water Reservoirs For Flood Prevention
          • Monitor and Reduce Energy Consumption
          • Oil Well Maintenance Planning
          • Oil Well RTP Monitoring
          • Pipe Scaling Prediction for Roller Cooling
          • Precision Irrigation in Agriculture
          • Predict Heat Exchanger Fouling
          • Predictive Maintenance & Asset Health Monitoring For Haul Trucks In The Mining Industry
          • Predictive Maintenance For Mobile Assets Within The Mining Industry
          • Predictive Maintenance for Robotic Arms in the Automotive Industry
          • Predictive Maintenance for Wind Turbines
          • Pump Health Monitoring in Water Utilities
          • Pumping Station OEE
          • Real-time Balanced Business Scorecard (BBS)
          • Real-time Safety Monitoring
          • Short Term Inventory Planning
          • Strategic Performance & Safety Oversight for Global Mining Operations
          • Wheel and Track Wear Monitoring In The Rail Industry
          • Wind Turbine Performance Optimization
        • Youtube
          • 2024
            • Discover Gen AI Powered Operations With XMPro iBOS
            • Generative AI and Digital Twins in 2024 - XMPro Webinar
            • Go From Reactive To Predictive Operations In Water Utilities With XMPro iDTS
            • How to add Timestamps to Elements in XMPro App Designer
            • How to Build an AI Advisor for Industrial Operations Using XMPro
            • How XMPro Stream Hosts and Collections Enable Scalable, Real-Time Data Processing
            • Mind Blowing AI Agentic Operations For Industry With XMPro MAGS
            • The Ultimate Beginner's Guide To Predictive Analytics Podcast
            • XMPro's Flexible Deployment Options: Flexible Cloud & On-Premise Solutions For Industry
            • XMPro iBOS: The Only AI-Powered Suite for Scalable Intelligent Operations
          • 2023
            • 2023 XMPro Product Roadmap - Webinar
            • An Introduction To Intelligent Digital Twins - Webinar
            • Energy and Utilities Asset Optimisation through Digital Twin technology
            • Explore Model Governance using our MLflow Agent
            • Exploring XMPro Notebook and MLflow for Data Science and Model Governance
            • How Changing Properties For One Block Can Be Applied To All Blocks Within Same Style Group
            • How do I Use A Button To Update a Data Source In XMPro App Designer
            • How Does XMPro Compare To ESBs (Enterprise Service Buses)-
            • How to Configure and Integrity Check in Data Streams
            • How To Create A Widget Within XMPro App Designer
            • How to Create Intelligent Digital Twins Using XMPro AI
            • How to export grid data to Excel In XMPro App Designer
            • How to Revolutionize Your Supply Chain with Digital Twins
            • How To Rotate Text In App Designer
            • How To Update a Data Source Using A Button
            • How To Use & Clone XMPro Demos For Your Own Use
            • How To Use And Build 3rd Party Apps To Extend The Capabilities Of The XMPro App Designer.
            • How to use Avatars and why they are important
            • How to view stream host logs In XMPro Data Stream Designer
            • Logging Provider Support With XMPro
            • Mastering Health Check Endpoints: A Guide to Ensuring Service Uptime and Performance with XMPro
            • Mastering Root Cause Analysis with XMPro: Capture, Value, Impact
            • Microsoft Azure Digital Twins Everything You Need To Know
            • Model Based Predictive Maintenance (PdM) With XMPro
            • Monthly Webinar - Accelerate your digital twin use cases - XMPro Blueprints, Accelerators & Patterns
            • Optimizing Time Series Chart (TSC) Performance
            • Predictive Maintenance & Condition Monitoring - A Hot Seat Q&A Session
            • Predictive Maintenance with XMPro iDTS
            • Smart Facilities Management with Intelligent Digital Twins
            • The Benefits of using Digital Twins in Smart Manufacturing
            • The Four Industrial Revolutions Explained In Under 4 Minutes! #industry4 #smartmanufacturing
            • The Roadmap To Intelligent Digital Twins
            • The Technology Behind Predictive Maintenance (PdM) - The Hardware & Software that makes PdM Tick...
            • THE TOP USE CASES FOR COMPOSABLE DIGITAL TWINS IN RENEWABLES
            • Tips on how to use cache in agent configuration and get live updates
            • Webinar - XMPro 4.3 Release Showcase
            • What is a Digital Twin- Why Composable Digital Twins is the Future.
            • What Is Predictive Maintenance- (PdM)
            • What To Do When a Data Source Is Not Showing in Pass Page Parameter
            • XMPro - The World's Only AI - Powered Intelligent Digital Twin Suite
            • XMPro - The World's Only No Code Digital Twin Composition Platform
            • XMPro AI : How It Works
            • XMPro AI End To End Use Case
            • XMPro Auto Scale - Understanding Distributed Caching for Cloud-Native Applications
            • XMPro Promo Video - Dell Validated Design For Manufacturing Edge
          • 2022
            • Aggregate Transformation Agent Example - XMPRO Data Stream Designer
            • App Layout Best Practices for Desktop & Mobile - XMPro Lunch & Learn
            • Broadcast Transformation Agent Example - XMPRO Data Stream Designer
            • Calculated Field Transformation Agent Example - XMPRO Data Stream Designer
            • CRC16 Function Agent Example - XMPRO Data Stream Designer
            • Create a Common Operating Picture of Your Operations with XMPro
            • CSV Context Provider Agent Example - XMPro Data Stream Designer
            • CSV Simulator Agent Example - XMPRO Data Stream Designer
            • CSV Writer Agent Example - XMPRO Data Stream Designer
            • Data Conversion Transformation Agent Example - XMPro Data Stream Designer
            • Digital Twin Strategy To Execution Pyramid - XMPro Webinar
            • Event Printer Action Agent Example - XMPRO Data Stream Designer
            • File Listener Agent Example - XMPRO Data Stream Designer
            • Filter Transformation Agent Example - XMPRO Data Stream Designer
            • Group & Merge Transformation Agent Example - XMPRO Data Stream Designer
            • How To Bind Data To A Chart and Get It Working As Expected - XMPro Lunch & Learn
            • How To Send Data To My App (Including Caching Introduction) - XMPro Lunch & Learn
            • Join Transformation Agent Example - XMPRO Data Stream Designer
            • Min/Max Function Agent Example - XMPRO Data Stream Designer
            • PART 1- How To Manage Complex Operations in Real-time Using Composable Digital Twins
            • PART 3 - How To Manage Complex Operations in Real-time Using Composable Digital Twins
            • PART2 - How To Manage Complex Operations in Real-time Using Composable Digital Twins
            • Pass Through Agent Example - XMPRO Data Stream Designer
            • Pivot Table Transformation Agent Example - Count - XMPRO Data Stream Designer
            • Pivot Table Transformation Agent Example - Sum - XMPRO Data Stream Designer
            • Real-Time Is Real - How To Use Event Intelligence Tools to Manage Complex Operations in Real-time.
            • Row Count Agent Example - XMPRO Data Stream Designer
            • Sort Transformation Agent Example - XMPRO Data Stream Designer
            • Transpose Transformation Agent Example - Columns - XMPRO Data Stream Designer
            • Transpose Transformation Agent Example - Rows - XMPRO Data Stream Designer
            • Trim Name Transformation Agent Example - XMPRO Data Stream Designer
            • Twilio Action Agent Example - XMPRO Data Stream Designer
            • Union Transformation Agent Example - XMPRO Data Stream Designer
            • Variables & Expressions in App Designer - XMPro Lunch & Learn
            • Window Transformation Agent Example - XMPRO Data Stream Designer
            • XML File Reader Action Agent Example - XMPRO Data Stream Designer
          • 2021
            • The Value of a Composable Digital Twin - XMPro Webinar
          • 2020
            • 1. Understanding The Problem - UX Design - XMPRO
            • 1.1 Welcome - XMPRO UI Design Basics
            • 1.2 Introduction To UI Design - XMPRO UI Design Basics
            • 2. Creating User Stories - UX Design - XMPRO
            • 2.1 Responsive Design - XMPRO UI Design Basics
            • 2.2 Grids - XMPRO UI Design Basics
            • 2.3 Visual Hierarchy - XMPRO UI Design Basics
            • 2.4 Wireframes - XMPRO UI Design Basics
            • 3. Creating User Flow Diagrams - UX Design - XMPRO
            • 3.1 Color Palette - XMPRO UI Design Basics
            • 3.2 Typography - XMPRO UI Design Basics
            • 3.3 White Space - XMPRO UI Design Basics
            • 3.4 UI Elements - XMPRO UI Design Basics
            • 4. Plan Your App with Wireframes - UX Design - XMPRO
            • 4.1 Chart Types - XMPRO UI Design Basics
            • 4.2 Chart Styling - XMPRO UI Design Basics
            • 5. Designing for Dynamic Data - UX Design - XMPRO
            • Agents and Their Types - XMPRO Data Stream Designer
            • Data Wrangling: Row Transpose - XMPRO Data Stream Designer
            • Digital Twin: Your Most Productive Remote Worker - XMPRO Webinar
            • End-To-End Real-Time Condition Monitoring Demo - XMPRO Application Development Platform
            • Error Endpoints - XMPRO Data Stream Designer
            • Export and Import Recommendations - XMPRO App Designer
            • How To Add Buttons To Agents - XMPRO Data Stream Designer
            • How To Add EditLists to Agents - XMPRO Data Stream Designer
            • How To Change UI Language - XMPRO Subscription Manager
            • How To Configure a Stream Object - XMPRO Data Stream Designer
            • How To Configure The Aggregate Transformation - XMPRO Data Stream Designer
            • How To Configure The Anomaly Detection Agent - XMPRO Data Stream Designer
            • How To Configure The Azure SQL Action Agent - XMPRO Data Stream Designer
            • How To Configure The Azure SQL Context Provider - XMPRO Data Stream Designer
            • How To Configure The Azure SQL Listener - XMPRO Data Stream Designer
            • How To Configure The Calculated Field Transformation - XMPRO Data Stream Designer
            • How To Configure The CSV Context Provider - XMPRO Data Stream Designer
            • How To Configure The CSV Listener - XMPRO Data Stream Designer
            • How To Configure The Data Conversion Transformation - XMPRO Data Stream Designer
            • How To Configure The Edge Analysis Transformation - XMPRO Data Stream Designer
            • How To Configure The Email Action Agent - XMPRO Data Stream Designer
            • How To Configure The Email Listener - XMPRO Data Stream Designer
            • How To Configure The Event Printer Action Agent - XMPRO Data Stream Designer
            • How To Configure The Event Simulator Listener - XMPRO Data Stream Designer
            • How To Configure The FFT Function - XMPRO Data Stream Designer
            • How To Configure The File Listener - XMPRO Data Stream Designer
            • How To Configure The Filter Transformation - XMPRO Data Stream Designer
            • How To Configure The IBM Maximo Action Agent - XMPRO Data Stream Designer
            • How To Configure The IBM Maximo Context Provider - XMPRO Data Stream Designer
            • How To Configure The IBM Maximo Listener - XMPRO Data Stream Designer
            • How To Configure The Join Transformation - XMPRO Data Stream Designer
            • How To Configure The JSON File Reader Context Provider - XMPRO Data Stream Designer
            • How To Configure The MQTT Action Agent - XMPRO Data Stream Designer
            • How To Configure The MQTT Advanced Action Agent - XMPRO Data Stream Designer
            • How To Configure The MQTT Advanced Listener - XMPRO Data Stream Designer
            • How To Configure The MQTT Listener - XMPRO Data Stream Designer
            • How To Configure The Normalize Fields Function - XMPRO Data Stream Designer
            • How To Configure The OSIsoft PI Context Provider - XMPRO Data Stream Designer
            • How To Configure The OSIsoft PI Listener - XMPRO Data Stream Designer
            • How To Configure The Pass Through Transformation - XMPRO Data Stream Designer
            • How To Configure The PMML Agent - XMPRO Data Stream Designer
            • How To Configure The REST API Context Provider - XMPRO Data Stream Designer
            • How To Configure The RScript Agent - XMPRO Data Stream Designer
            • How To Configure The Run Recommendation Agent - XMPRO Data Stream Designer
            • How To Configure The Signal Filter - XMPRO Data Stream Designer
            • How To Configure The SQL Server Action Agent - XMPRO Data Stream Designer
            • How To Configure The SQL Server Context Provider - XMPRO Data Stream Designer
            • How To Configure The SQL Server Listener - XMPRO Data Stream Designer
            • How To Configure The SQL Server Writer Action Agent - XMPRO Data Stream Designer
            • How To Configure The Twilio Action Agent - XMPRO Data Stream Designer
            • How To Configure The Union Transformation - XMPRO Data Stream Designer
            • How To Configure The Unzip Function - XMPRO Data Stream Designer
            • How To Configure The Window Transformation - XMPRO Data Stream Designer
            • How To Create an App - XMPRO App Designer
            • How To Create and Manage Templates - XMPRO App Designer
            • How To Create and Publish a Use Case - XMPRO Data Stream Designer
            • How To Create and Use a Widget - XMPRO App Designer
            • How To Create App Data Connections - XMPRO App Designer
            • How To Create App Pages and Navigation - XMPRO App Designer
            • How To Create Recommendation Rules - XMPRO App Designer
            • How To Create Recurrent Data Streams - XMPRO Data Stream Designer
            • How To Do Integrity Checks - XMPRO Data Stream Designer
            • How To Edit Page Properties - XMPRO App Designer
            • How To Enable Audit Trails - XMPRO App Designer
            • How to Export, Import, and Clone a Data Stream - XMPRO Data Stream Designer
            • How To Export, Import and Clone an App - XMPRO App Designer
            • How to Export and Import an App - XMPRO App Designer
            • How To Find Help for an Agent - XMPRO Data Stream Designer
            • How To Install The XMPRO App Designer
            • How To Maintain and Capture Notes - XMPRO App Designer
            • How To Manage Agents - XMPRO Data Stream Designer
            • How To Manage and Use Server Variables - XMPRO Data Stream Designer
            • How To Manage Buffer Size - XMPRO Data Stream Designer
            • How to Manage Categories - XMPRO App Designer
            • How To Manage Categories - XMPRO Data Stream Designer
            • How To Pass Parameters Between Pages - XMPRO App Designer
            • How To Publish and Share an Application - XMPRO App Designer
            • How To Set Up and Use Charts in Live View - XMPRO Data Stream Designer
            • How To Set Up and Use Gauges in Live View - XMPRO Data Stream Designer
            • How To Share a Data Stream - XMPRO Data Stream Designer
            • How To Share a Use Case - XMPRO Data Stream Designer
            • How To Share an App For Design Collaboration - XMPRO App Designer
            • How To Troubleshoot a Use Case - XMPRO Data Stream Designer
            • How To Upgrade a Stream Object Version - XMPRO Data Stream Designer
            • How To Use App Files - XMPRO App Designer
            • How To Use Application Versions - XMPRO App Designer
            • How To Use Bar Gauge - XMPRO App Designer
            • How To Use Calendar - XMPRO App Designer
            • How To Use Chart Pan, Zoom and Aggregation - XMPRO App Designer
            • How To Use Chart Panes and Axes - XMPRO App Designer
            • How To Use Chart Print and Export- XMPRO App Designer
            • How To Use Charts - XMPRO App Designer Toolbox
            • How To Use Charts: Series - XMPRO App Designer
            • How To Use Collections - XMPRO Data Stream Designer
            • How To Use Content Card - XMPRO App Designer
            • How To Use D3 - XMPRO App Designer
            • How To Use Data Sources - XMPRO App Designer
            • How To Use Embedded Pages - XMPRO App Designer Toolbox
            • How To Use Fieldset and Field - XMPRO App Designer Toolbox
            • How To Use Flex Layout
            • How To Use Form Validation - XMPRO App Designer Toolbox
            • How To Use Input Mappings - XMPRO Data Stream Designer
            • How To Use Linear Gauges - XMPRO App Designer
            • How To Use Live View - XMPRO Data Stream Designer
            • How To Use Lookup - XMPRO App Designer
            • How To Use Maps - XMPRO App Designer
            • How To Use Page Layers - XMPRO App Designer
            • How To Use Pivot Grid - XMPRO App Designer
            • How To Use Polar Charts - XMPRO App Designer
            • How To Use Power BI - XMPRO App Designer
            • How To Use Radio Buttons - XMPRO App Designer Toolbox
            • How To Use Recommendations - XMPRO App Designer Toolbox
            • How To Use Select Box - XMPRO App Designer
            • How To Use Stacked Layouts - XMPRO App Designer Toolbox
            • How To Use Stream Host Local Variables - XMPRO Data Stream Designer
            • How To Use Tabs - XMPRO App Designer Toolbox
            • How To Use Tags - XMPRO App Designer Toolbox
            • How To Use Templated List - XMPRO App Designer
            • How To Use Templates - XMPRO App Designer
            • How To Use Text - XMPRO App Designer Toolbox
            • How To Use Text Area - XMPRO App Designer Toolbox
            • How To Use The Accordion - XMPRO App Designer Toolbox
            • How To Use The Block Styling Manager - XMPRO App Designer
            • How To Use The Box and Data Repeater Box - XMPRO App Designer Toolbox
            • How To Use The Button - XMPRO App Designer Toolbox
            • How To Use The Circular Gauge - XMPRO App Designer Toolbox
            • How To Use The Data Grid - XMPRO App Designer Toolbox
            • How To Use The HTML Editor - XMPRO App Designer Toolbox
            • How To Use The Hyperlink and Box Hyperlink - XMPro App Designer Toolbox
            • How To Use The Image - XMPRO App Designer Toolbox
            • How To Use The Indicator - XMPRO App Designer Toolbox
            • How To Use The Layout Grid - XMPRO App Designer Toolbox
            • How To Use The Number Selector - XMPRO App Designer Toolbox
            • How To Use The Pie Chart - XMPRO App Designer Toolbox
            • How To Use The Range Slider - XMPRO App Designer Toolbox
            • How To Use The Recommendation Chart - XMPRO App Designer Toolbox
            • How To Use The Scroll Box - XMPRO App Designer Toolbox
            • How To Use The Select Box - XMPRO App Designer Toolbox
            • How To Use The Sparkline - XMPRO App Designer Toolbox
            • How To Use The Textbox - XMPRO App Designer Toolbox
            • How To Use Tree Grid - XMPRO App Designer
            • How To Use Tree List - XMPRO App Designer
            • How To Use Unity - XMPRO App Designer Toolbox
            • How To Use Variables - XMPRO App Designer
            • How To Write and Maintain Notes and Business Case - XMPRO Data Stream Designer
            • Interactive 3D Models For Digital Twins - XMPRO Event Intelligence Platform
            • Manage Input Arrow Highlights - XMPRO Data Stream Designer
            • Manage Recommendation Access - XMPRO App Designer
            • Realize Value from End-To-End Condition Monitoring in 6 - 8 Weeks - XMPRO
            • Recommendation Versions - XMPRO App Designer
            • Solution Development Process For Event Intelligence Apps - XMPRO
            • Stream Hosts and How To Install Them - XMPRO Data Stream Designer
            • Use Case Versioning - XMPRO Data Stream Designer
            • XMPRO App Designer Overview - Event Intelligence Applications
            • XMPRO Data Stream Designer - Event Intelligence Applications
            • XMPRO Real-Time Event Intelligence Demo
            • XMPRO Recommendations - Event Intelligence Applications
          • 2019
            • Data Distribution Service: Using DDS in Your IoT Applications
            • My Digital Twin: Digital Twin Applications For Real-Time Operations (Like Me)
            • Setting up a Typical Industrial IoT Use Case with XMPro
            • XMPro Overview & Fin Fan Failure Demo
          • 2016
            • XMPro iBPMS Overview
          • 2013
            • XMPro Best Next Action - 3 Examples for XMPro blog
            • XMPro Case Management Example
            • XMPro Internet of Things Demo
          • 2012
            • Is Agile Business the New Normal
            • The Future of BPM Moving Towards Intelligent Business Operations
            • What industries does XMPro serve-
            • Who is XMPro for-
            • XMPro - The Social Listener - Why You Should Be Listening.wmv
            • XMPro Cool Vendor 2012
            • XMPro iBPMS For SharePoint
            • XMPro iBPMS v6 XMWeb for Intelligent Business Operations
            • XMPro News and Gartner BPM Sydney Summit Discount Offer.mp4
            • XMPro Version 6 - Introducing the Next Generation BPM for Intelligent Business Operations
    • Practice Notes
      • Unified Recommendation Alert Management
      • Performant Landing Pages in Real-Time Monitoring
  • Concepts
    • XMPro AI
      • XMPro Notebook
    • Data Stream
      • Stream Object Configuration
      • Verifying Stream Integrity
      • Running Data Streams
      • Timeline
    • Collection and Stream Host
    • Agent
      • Virtual vs Non-Virtual Agents
    • Application
      • Template
      • Page
      • Block
      • Canvas
      • Page Layers
      • Block Styling
      • Devices
      • Flex
      • Block Properties
      • Data Integration
      • Navigation and Parameters
      • Variables and Expressions
      • App Files
      • Metablocks
    • Recommendation
      • Rule
      • Execution Order
      • Auto Escalate
      • Form
      • Action Requests
      • Notification
      • Recommendation Alert
      • Deleted Items
      • Scoring
    • Connector
    • Landing Pages & Favorites
    • Version
    • Manage Access
    • Category
    • Variable
    • Insights
      • Data Delivery Insights
  • How-To Guides
    • Data Streams
      • Manage Data Streams
      • Manage Collections
      • Use Remote Receivers and Publishers
      • Manage Recurrent Data Streams
      • Use Business Case and Notes
      • Run an Integrity Check
      • Check Data Stream Logs
      • Use Live View
      • Use Stream Metrics
      • Troubleshoot a Data Stream
      • Upgrade a Stream Object Version
      • Setup Input Mappings
      • Use Error Endpoints
      • Use the Timeline
      • Context Menu
    • Application
      • Manage Apps
      • Manage Templates
      • Manage Pages
      • Import an App Page
      • Design Pages for Mobile
      • Navigate Between Pages
      • Pass Parameters Between Pages
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Wheel and Track Wear Monitoring In The Rail Industry

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Last updated 6 days ago

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Wheel and Track Wear Monitoring Solution for the Rail Industry Introduction In the rail industry, the integrity of wheels and tracks is paramount for safe and efficient operations. XMPro's solution focuses on monitoring wear and tear to prevent derailments and reduce maintenance costs. The Challenge Rail systems face significant challenges in maintaining the health ofTags: Condition Monitoring

Wheel and Track Wear Monitoring Solution for the Rail Industry

Introduction

In the rail industry, the integrity of wheels and tracks is paramount for safe and efficient operations. XMPro’s solution focuses on monitoring wear and tear to prevent derailments and reduce maintenance costs.

The Challenge

Rail systems face significant challenges in maintaining the health of wheels and tracks:

  1. Risk of Derailments: Abnormal wear in wheels and tracks can lead to increased risk of derailments, posing serious safety hazards.

  2. Maintenance Efficiency: Identifying the optimal frequency for maintenance activities to ensure safety while controlling costs.

  3. Operational Downtime: Unplanned maintenance and repairs can lead to significant operational downtime and disruptions.

The Solution: XMPro Wheel and Track Wear Monitoring

XMPro’s solution leverages data from advanced sensors and machine learning (ML) for anomaly detection, providing a proactive approach to wheel and track maintenance.

Key Features

  1. Streamlining Sensor Data Integration and Transformation

    XMPro’s Data Stream Designer excels in integrating and transforming sensor data for rail systems. It seamlessly aggregates data from vibration and acoustic sensors on trains and tracks, utilizing XMPro’s comprehensive integration library. This system efficiently processes and interprets diverse sensor data, providing crucial insights into wheel and track wear patterns for proactive maintenance and operational decision-making.

  2. Machine Learning for Anomaly Detection:

    Implementing ML algorithms to analyze sensor data and detect anomalies indicating abnormal wear. Continuous learning and model refinement based on new data and identified wear patterns.

  3. Maintenance Scheduling Optimization:

    Using data-driven insights to optimize maintenance schedules, shifting from fixed intervals to condition-based maintenance.

  4. Real-Time Alerts and Reporting:

    Providing real-time alerts to maintenance teams about potential issues.Generating detailed reports on wheel and track conditions for maintenance planning and regulatory compliance.

Figure 1. Real-Time Rail Asset Overview Dashboard

Real-Time Rail Asset Overview Dashboard

This comprehensive dashboard provides users with an up-to-the-minute view of their rail assets. It features an interactive map that dynamically updates with the GPS coordinates of trains in motion, offering a clear visual representation of their railway lines. Each asset on the map is marked with a color-coded status icon, indicating its current operational state, including active status and any alerts or error messages.

The dashboard comprehensively displays the overall status of various asset categories, such as trains, crossings, tracks, maintenance vehicles, and substations. It also highlights all active recommendations generated by the system’s rule logic. This includes critical alerts like exceeded wheel wear thresholds, ensuring immediate attention to potential issues.

Additionally, the dashboard includes a detailed graph that tracks maintenance requirements across assets. It prioritizes assets based on their upcoming service needs, facilitating efficient maintenance scheduling.

Each section of the dashboard is designed for deeper exploration. Users can drill down into specific asset and recommendation details, gaining granular insights and enabling targeted actions based on the system’s recommendations. This level of detail ensures that users can make informed decisions quickly and maintain optimal operational efficiency.

Figure 2. Asset Drill Down View – Trains

Asset Drilldown View – Trains

The specific asset view for trains provides users with a comprehensive and informative dashboard.

  • Alerts Overview: Graphical representation of open alerts categorized by severity – no alerts, medium, and high severity.

  • Work Order Status: Displays current status of each asset, categorized as available, in planning, or waiting.

  • Performance Metrics (Last 30 Days): Summarizes key metrics such as new alerts, number of work orders, open work orders, and open work requests. It also tracks the duration from alert initiation to work order completion, comparing it with the previous 30-day period.

  • Asset Filtering and Service Information: Enables filtering across all train assets, showing details like the last service date, upcoming service schedules, and due dates.

  • Recent Recommendations: Lists recent recommendations triggered for train assets, with options for users to view details and take necessary actions.

  • XMPro Co-Pilot Integration: Features an interactive block where users can query the AI model, trained on internal data like train engine manuals, for specific advice on errors, warnings, and issues. This information can be directly linked to work order requests and triage instructions.

This dashboard is designed for ease of use, allowing quick access to vital information and efficient management of train assets.

Figure 3. Asset Analysis View – Train T001

Asset Analysis View – Train T001

The Asset Analysis View offers detailed insights into specific assets, exemplified here by Train T001 within the train asset category.

  • Comprehensive Asset Metrics: In this detailed view for Bogie B001, we concentrate on specific metrics crucial for monitoring wheel wear.

    Key metrics include Spring Compression, indicating load distribution and wear patterns; Bearing Temperature, signaling potential friction issues; Bearing Vibration Amplitude, identifying internal wear; and Wheel Vibration Amplitude, detecting uneven wear or defects. These metrics collectively provide a crucial overview for maintaining wheel health and ensuring operational safety.

  • Interactive 2D and 3D Asset Models: Features detailed 2D and 3D models of Train T001, with capabilities to ‘explode’ the view for in-depth examination of specific components. Notably, the 3D model visually identifies issues, such as those highlighted by recommendation rules related to wheel and track wear. For instance, areas of concern, like the wheels and bogie of affected wheels, are marked in red for easy identification.

  • Error Identification and Actionable Recommendations: Clicking on highlighted errors directs users to the associated recommendations, where a range of actions can be explored to address the issue. This functionality is integrated with XMPro’s Recommendation Manager for efficient problem resolution.

  • Detailed Train Information: The view encompasses comprehensive information about Train T001, including its type, model, description, and manufacturer details.

  • XMPro Co-Pilot Integration: This feature includes XMPro Co-Pilot, trained on internal company data, providing users with specific guidance and answers to queries related to Train T001. This AI-driven support enhances decision-making and problem-solving related to the asset.

This Asset Analysis View is designed to provide users with a holistic understanding of Train T001, combining detailed visual models with actionable data and AI-assisted insights for effective asset management.

Why XMPro iDTS?

XMPro’s Intelligent Digital Twin Suite (iDTS) offers unique and innovative solutions for Wheel and Track Wear Monitoring in the rail industry, leveraging advanced technologies and analytics. Here’s how XMPro iDTS specifically addresses this challenge:

Digital Twin Modeling for Rail Systems:

XMPro iDTS creates a digital twin of the rail system, including detailed models of the tracks and wheels. This virtual representation allows for sophisticated simulation and analysis of wear patterns, enabling predictive maintenance and anomaly detection.

Comprehensive Data Integration And Sophisticated Transformation

XMPro iDTS features a comprehensive library of integrations that allow businesses to integrate and transform data from virtually any data source. In this case the solution integrates data from vibration and acoustic sensors installed on trains and tracks.

Advanced Machine Learning for Anomaly Detection:

Utilizing machine learning algorithms, XMPro iDTS analyzes sensor data to identify anomalies that indicate abnormal wear. This approach allows for early detection of potential issues that could lead to derailments or other safety hazards.

Optimization of Maintenance Schedules:

By analyzing wear patterns and predicting maintenance needs, XMPro iDTS helps optimize maintenance schedules. This shift from fixed-interval to condition-based maintenance reduces costs and prevents unnecessary downtime.

Real-Time Alerts and Decision Support:

XMPro iDTS provides real-time alerts to maintenance teams regarding potential wear issues. It also offers decision support tools to help prioritize maintenance activities based on the severity and urgency of detected anomalies.

Customizable Dashboards and Reporting:

The solution includes customizable dashboards that present key data and insights on wheel and track conditions. It also generates comprehensive reports for maintenance planning and regulatory compliance.

Scalability and Flexibility – Start Small, Scale Fast:

XMPro iDTS is scalable and flexible, capable of adapting to different sizes of rail networks and integrating with various types of sensor technologies. XMPro has been consistently deployed in only a matter of weeks.

Enhanced Safety and Operational Efficiency:

By enabling proactive maintenance and early detection of wear issues, XMPro iDTS enhances the safety and operational efficiency of rail systems, reducing the risk of accidents and improving service reliability.

Quick Time To Value – XMPro Blueprints

Leverage XMPro blueprints as pre-configured templates tailored for wheel and track wear monitoring. These blueprints provide a starting point for setting up the digital twin dashboard, incorporating best practices and industry standards.

In summary, XMPro iDTS addresses the unique challenges of wheel and track wear monitoring in the rail industry by providing a comprehensive, real-time, predictive, and integrated solution. Its capabilities in digital twin technology, advanced sensor data integration, machine learning for anomaly detection, and effective visualization tools make it a powerful tool for enhancing rail safety, maintenance efficiency, and operational reliability.

Not Sure How To Get Started?

No matter where you are on your digital transformation journey, the expert team at XMPro can help guide you every step of the way - We have helped clients successfully implement and deploy projects with Over 10x ROI in only a matter of weeks!

Request a free online consultation for your business problem.

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