45 min
Ep 40 Digital Twins for Process Optimisation and Asset Reliability - [ Erik Udstuen, CEO TwinThread] The Fourth Generation Podcast
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- Technology
For years, manufacturers have had to navigate in relative blindness, implementing improvements on an as-needed, reactive basis.
This approach, although functional, has been markedly inefficient and reactive, particularly in terms of process optimisation and asset reliability, two vital aspects of industrial operations that can profoundly impact efficiency and profitability.
Digital Twins represent a transformative shift from this reactive approach to a proactive, predictive one. They facilitate a deeper understanding of how systems behave, providing industrial operators with actionable insights that were previously unavailable.
To learn more about the application of digital twins in manufacturing, I had a podcast conversation with Erik Udstuen, who is the CEO and co-founder of TwinThread, a company that provides a digital twin platform that combines Industrial Data with Industrial AI in an integrated development environment for engineers and data scientists.
Here's the outline of our conversation
✅ Challenges driving Digital Twins adoption in modern manufacturing✅ Key Functions of Digital Twins in Manufacturing✅ Industrial AI Ops✅ Use Cases for Asset and Process Digital Twins✅ Connectivity standards for physical assets to digital twins✅ Best practices for modelling assets and processes for digital twins ✅ Effective infrastructure abstraction techniques for Digital Twin Implementation✅ ISA 88 / 95, and Data Modeling standards for Digital twins✅ Principles-based vs Machine Learning-based modelling for advanced analytics✅ Practical examples of successful digital twin applications in Manufacturing ✅ Selecting a digital twin platform and evaluating capabilities✅ TwinThread Digital Twin Integrated development environment
For years, manufacturers have had to navigate in relative blindness, implementing improvements on an as-needed, reactive basis.
This approach, although functional, has been markedly inefficient and reactive, particularly in terms of process optimisation and asset reliability, two vital aspects of industrial operations that can profoundly impact efficiency and profitability.
Digital Twins represent a transformative shift from this reactive approach to a proactive, predictive one. They facilitate a deeper understanding of how systems behave, providing industrial operators with actionable insights that were previously unavailable.
To learn more about the application of digital twins in manufacturing, I had a podcast conversation with Erik Udstuen, who is the CEO and co-founder of TwinThread, a company that provides a digital twin platform that combines Industrial Data with Industrial AI in an integrated development environment for engineers and data scientists.
Here's the outline of our conversation
✅ Challenges driving Digital Twins adoption in modern manufacturing✅ Key Functions of Digital Twins in Manufacturing✅ Industrial AI Ops✅ Use Cases for Asset and Process Digital Twins✅ Connectivity standards for physical assets to digital twins✅ Best practices for modelling assets and processes for digital twins ✅ Effective infrastructure abstraction techniques for Digital Twin Implementation✅ ISA 88 / 95, and Data Modeling standards for Digital twins✅ Principles-based vs Machine Learning-based modelling for advanced analytics✅ Practical examples of successful digital twin applications in Manufacturing ✅ Selecting a digital twin platform and evaluating capabilities✅ TwinThread Digital Twin Integrated development environment
45 min