Another year has come and gone, and still, almost every IIoT use case in manufacturing requires some sort of compute capability near the source of the data in order to solve some of the toughest challenges in Manufacturing Digital Transformation.
But yet, the currently dominant model for Industrial IoT is the Cloud-Based Platform-As-A-Service.
The issue is, while Edge Computing architectures do provide immense power and capabilities such as system resilience through delegation of computational workloads to autonomous IIoT devices in Distributed Edge Computing, it brings with it implementation complexity in manufacturing enterprises.
So, to provide you with practical guidance on Edge Computing, Architectures, and the building blocks necessary for an Edge Computing implementation in manufacturing, I invited Dominik Pilat, who is the Vice President of Customer Support & Field CTO at Hivecell, and John Kalfayan who is the Vice President of Energy, also at Hivecell.
Hivecell is a complete Edge-As-A-Service solution that allows companies to process vast amounts of raw data from smart machines and IoT Devices in real-time, at the Edge. It is both a hardware and software solution that supports the most widely used platforms today such as Kubernetes and Apache Kafka.
Outline
✔️ Key Drivers for Deployment of Compute Capabilities at the Industrial Edge
✔️ Industrial IoT Edge Computing Technology Stack
✔️ Characteristics of Distributed Edge Computing Model for IIoT
✔️ Management and Monitoring of Edge Deployed Software
✔️ Data Governance in Industrial Edge Computing
✔️ Apache Kafka Deployment at The Edge for IIoT
✔️ How Edge Compute Enables AI at the Industrial Edge
✔️ Hardware for Running AI Applications at the Edge
✔️ Practical Use Case of Industrial Edge Computing and AI
✔️ Hivecell Edge As A Services Solution
I wish you all a prosperous 2022.
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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