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Master Digital Twins: Industry 4.0 Implementation Pro Guide

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17:15:32

  • 1 - Overview of Industry 40.mp4
    04:52
  • 2 - Fourth Industrial Era.mp4
    03:35
  • 3 - Key Technologies Part1.mp4
    04:43
  • 4 - Key Technologies Part2.mp4
    23:45
  • 5 - Benefits of Industry 40.mp4
    06:27
  • 6 - Challenges of Industry 40.mp4
    08:09
  • 7 - Introduction to Digital Twins.mp4
    23:03
  • 8 - Applications of Digital Twins.mp4
    20:42
  • 9 - History and Development.mp4
    21:55
  • 10 - Key Components.mp4
    31:17
  • 11 - Types of Digital Twins.mp4
    32:30
  • 12 - Overview of Digital Twin Architecture.mp4
    01:47
  • 13 - Layers and Components.mp4
    06:59
  • 14 - Layers and Components Part 2.mp4
    20:40
  • 15 - Key Consideration.mp4
    09:09
  • 16 - Key Consideration Part2.mp4
    13:04
  • 17 - Data Integration.mp4
    17:26
  • 18 - Data Integration Technologies.mp4
    17:45
  • 19 - Communication Protocols Introduction.mp4
    11:45
  • 20 - Major Communication Protocols.mp4
    29:53
  • 21 - Modeling and Simulation.mp4
    04:14
  • 22 - Types of Models in Digital Twins.mp4
    05:32
  • 23 - Types of Models in Digital Twins Part2.mp4
    07:41
  • 24 - Types of Models in Digital Twins Part3.mp4
    03:36
  • 25 - Types of Models in Digital Twins Part4.mp4
    06:01
  • 26 - RealTime Simulation Techniques.mp4
    08:21
  • 27 - RealTime Simulation Techniques Part2.mp4
    13:12
  • 28 - Predictive Simulation Techniques.mp4
    11:42
  • 29 - Realtime and Predictive Simulation.mp4
    10:44
  • 30 - Tools and Software.mp4
    05:54
  • 31 - Analysis of Tools.mp4
    23:32
  • 32 - Overview of Data Analytics.mp4
    04:02
  • 33 - Role of Data Analytics.mp4
    15:56
  • 34 - Types of Data Analytics.mp4
    23:13
  • 35 - Visualization and reporting.mp4
    07:44
  • 36 - AI and Machine Learning.mp4
    10:00
  • 37 - Role of AI and Machine Learning in Digital Twins.mp4
    20:19
  • 38 - Case Studies.mp4
    04:37
  • 39 - Realworld Examples.mp4
    16:50
  • 40 - Module Introduction.mp4
    00:41
  • 41 - Planning and Strategy.mp4
    22:36
  • 42 - Steps for Implementation.mp4
    05:39
  • 43 - Steps for Implementation Part 2.mp4
    17:10
  • 44 - Challenges and Solutions.mp4
    15:55
  • 45 - Challenges and Solutions Part 2.mp4
    24:20
  • 46 - Challenges and Solutions Part 3.mp4
    18:36
  • 47 - Best Practices.mp4
    22:39
  • 48 - Digital Twin in Product Lifecycle Management PLM.mp4
    04:34
  • 49 - PLM Overview.mp4
    30:45
  • 50 - Enhancing PLM.mp4
    13:22
  • 51 - How digital twins enhance PLM processes.mp4
    16:25
  • 52 - Industry Examples.mp4
    13:30
  • 53 - Industry Examples Part2.mp4
    16:04
  • 54 - Smart Manufacturing Overview.mp4
    04:54
  • 55 - Digital Twins in Smart Manufacturing.mp4
    17:08
  • 56 - Integration with IoT.mp4
    13:44
  • 57 - Understanding Digital Twins in Smart Manufacturing.mp4
    17:41
  • 58 - Case Studies.mp4
    17:54
  • 59 - Realworld Applications.mp4
    12:39
  • 60 - Digital Twins in Maintenance and Optimization.mp4
    03:43
  • 61 - How digital twins are used for predictive maintenance.mp4
    22:26
  • 62 - Techniques and Tools.mp4
    31:16
  • 63 - Process and Performance Optimization.mp4
    03:31
  • 64 - Process and Performance Optimization Part2.mp4
    37:07
  • 65 - Examples of successful maintenance and optimization using digital twins.mp4
    27:36
  • 66 - Future Trends and Innovations.mp4
    02:30
  • 67 - Emerging Technologies.mp4
    20:02
  • 68 - Emerging Technologies Part2.mp4
    24:27
  • 69 - Innovations in Digital Twins.mp4
    23:50
  • 70 - Future Outlook.mp4
    20:12

    • More details

    Course Overview

    This comprehensive course provides expert training on Digital Twin technology and its practical applications in Industry 4.0, covering architecture, implementation strategies, and real-world case studies for smart manufacturing and predictive maintenance.

    What You'll Learn

    • Digital Twin architecture, modeling, and simulation techniques
    • Integration with IoT, AI, and data analytics for Industry 4.0
    • Implementation strategies for smart manufacturing and product lifecycle management

    Who This Is For

    • Manufacturing professionals transitioning to Industry 4.0
    • Engineering students specializing in digital technologies
    • Tech professionals exploring Digital Twin applications

    Key Benefits

    • No prerequisites - suitable for beginners and experts alike
    • Practical case studies from real industrial applications
    • Future-focused curriculum covering emerging trends

    Curriculum Highlights

    1. Industry 4.0 Foundations & Digital Twin Basics
    2. Advanced Modeling & Simulation Techniques
    3. Smart Manufacturing Implementation Strategies
    Focused display
    Category

    Industry 4.0

    • language english
    • Training sessions 70
    • duration 17:15:32
    • Release Date 2025/05/10

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