Advanced as they may be, modern analytics systems fall short of enabling the complete digital transformation of manufacturing enterprises.
For example, instead of only detecting symptoms of impending machine failure, what would be more valuable would be to determine the actual cause of failure.
Causal Machine Learning, a recent advance in ML holds the problem to solve this problem.
To understand how it can be applied in Digital Twins to enable complete digital transformation for manufacturers, I had a conversation with Dr. PG Madhavan.
PG has deep expertise in Data Science and extensive experience in advanced analytics development, both in industry and academia.
Below is the outline of our conversation:
✅ Enthusiasm about Digital Twins Today
✅ Why Predictive Maintenance is not the Killer App for IIoT
✅ What is the central purpose of a Digital Twin?
✅ Challenges in Integrating Digital Technologies for DT Realisation
✅ Role of Industrial IoT in Digital Twins
✅ Machine Learning Methods in Digital Twins
✅ Application of Root Cause Analytics Method in DTs
✅ Application of Causality in Industrial IoT Data
✅ Key Steps to Digital Transformation in Manufacturing
✅ Manufacturing Digital Transformation through Digital Twins
✅ PyWhy, an open-source repository of AWS & Microsoft joint work in Causality for machine learning.
✅ Systems Analytics Solutions
Ep 43 Infrastructure as Code for Industrial IoT - [ Peter Sorowka, CEO Cybus GmbH]
Ep 42 Data Driven Optimization in Process Industries - [ Jim Gavigan, President, Industrial Insight]
Ep 41 Applied AI in Manufacturing - [ Roey Mechrez, Head of AI, and EMEA MD @Tulip]
Ep 40 Digital Twins for Process Optimisation and Asset Reliability - [ Erik Udstuen, CEO TwinThread]
Ep 39 DataOps for Digital Transformation In Manufacturing - [ Aron Semle, CTO Highbyte]
Ep 38 LoRaWAN for Industrial IoT Applications - [ Wienke Giezeman, The Things Industries]
Ep 37 Data Modelling and Manufacturing Ontologies for Digital Twins - [ Erich Barnstedt - Microsoft ]
Ep 36 Agility, Open Platform Strategy & Industrial Data Spaces for Industry4.0 - [ Sandeep Sreekumar - IndustryApps ]
Ep 35 Human-Machine Collaboration for Smart Manufacturing - [ Rafael Amaral - Tillit ]
Ep 34 Node-Red for IIoT in the Enterprise - [ Nick O’Leary, CTO Flowforge Inc ]
Ep 33 Unified Namespace for Industrial IoT: The Masterclass - [ Walker D Reynolds, 4.0 Solutions ]
Ep 32 Low Foot Print OPC UA Over TSN for Real-Time Communication - [ Melvin Francis, Be Services ]
Ep 31 Architecting IIoT Solutions Using Unified Namespace - [ David Schultz, G5 Consulting ]
Ep 30 Fundamentals of OPC UA Information Modelling - [ Jouni Aro - CTO, Prosys OPC ]
Ep 29 Manufacturing Execution Systems for Data-Driven Manufacturing - Kevin Jones, CEO Ectobox
Ep 28 Predictive Analytics in Manufacturing - Maciek Wasiak, CEO Xpanse AI
Ep 27 First Principles : First Principles of Smart Manufacturing - Conrad Levia, CESMII
Ep 26 : Embedded Vision and Connectivity for IIoT - Taylor Cooper (CEO, Principal Engineer - MistyWest) )
Ep 25 : Containerisation for Industrial IoT - Neil Cresswell (CEO, Co-Founder - Portainer) )
Ep 24 : Real World Applications of OPC UA PubSub - Praveen Kumar Singh (Chief OPC Solution Architect - Utthunga) )
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