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Each episode of Industry40.tv Podcast will treat you to an in-depth interview with leading AI practitioners, exploring the Application of Artificial Intelligence in Manufacturing and offering practical guidance for successful implementation.
Episodes
Thursday Sep 22, 2022
Thursday Sep 22, 2022
More than anything else, the foundational power of personnel in fieldwork merely lies in the fact that we can see.
By extension, it makes sense that the biggest impact on industrial digital transformation will come from embedding vision in intelligent connected components.
More so when embedded vision and AI software are widely deployed in mobile and battery-powered field equipment.
To learn more about building this capability into industrial products, I invited Taylor Cooper for a chat on the podcast.
Taylor is the CEO and Principal Engineer at MistyWest where he's recently led the company in developing an Embedded Vision System on Module (MistySOM), based on the Renesas RZ/V2L processor, that enables the embedding of vision-based AI capabilities in field equipment.
Below is the outline of our conversation.
✅ Misty West, Embedded Vision & IIoT
✅ Latest Trends in Industrial IoT, and Chip Shortage
✅ Google IoT Core Retirement, IoT Boom and Bust
✅ MQTT in IIoT and Computer Vision
✅ Delivering AI Capabilities for IIoT with Renesas RZ/V2L Based System on Module
✅ Potential Applications of Low Power System on Module in Connected Intelligence,
✅ Workflow for developing Embedded Vision for Connected Products
✅ AI versus Rules-Based Image Processing in Embedded vision
✅ Selecting Embedded Vision Middleware
✅ Selecting wireless connectivity for Embedded Vision Applications
Thursday Sep 22, 2022
Thursday Sep 22, 2022
Here's the thing. Containerisation is not only an IT technology, it is an advanced IT technology. And yet, it already looms on the horizon for Operations Technology.
And, while the technology opens up massive opportunities for optimisation and efficiency in the OT network, it demands a fundamental rethink of industrial software distribution and management.
To find out what this actually means for vendors, engineers, and system integrators in the industrial space, I invited Neil Cresswell for a conversation.
Neil is the CEO and Co-Founder of a company called Portainer.io, the most popular Docker Container Management platform that abstracts the complexities of container management with a feature-rich and easy-to-use Graphical User Interface.
Below is the outline of our conversation.
✅ What are containers?
✅ Benefits of containerisation at the Industrial Edge
✅ Challenges of adopting containers for Industrial Edge Compute
✅ Key differences between containerisation at the edge and in the cloud
✅ Containerization Approaches and Microservices for IIoT
✅ What is Portainer and How it Works
✅ Use Cases in Industrial IoT
✅ Portainer Products
✅ Reference Architectures for Managing software in OT
✅ Best Practices Containerisation at the Industrial Edge
✅ How a Containerised PLC functions
✅ Impact of Containerisation on Industrial System Integration
✅ The Future of Industrial Software Distribution
Thursday Sep 08, 2022
Thursday Sep 08, 2022
While there may be disagreements on what data modeling, encoding, and transportation technologies to adopt for Industrial IoT, there's one aspect that's evidently being agreed upon across the board.
The fact that Publish-Subscribe architectures are, by far, more suitable for this new world of hyper-connectivity.
One implementation of such an architecture for IIoT is OPC UA PubSub, which defines a mapping of Binary and JSON encoding over an MQTT, AMQP, and UDP-based PubSub network.
To understand how OPC UA PubSub can be applied in Real-World Industrial scenarios, I had a conversation with Praveen Kumar Singh, who is the Chief OPC Solutions Architect at Utthunga, a Product Engineering and Industrial Solutions company that engineers industrial-grade digital products and solutions for industrial OEMs, Industries, ISVs, and Service Providers.
Below is the outline of our conversation.
✅ What is OPC UA PubSub?
✅ Real World Applications of OPC UA PubSub
✅ Embedded OPC UA PubSub Applications
✅ Configuration Mechanism of OPC UA PubSub Components
✅ How Discovery works in OPC UA PubSub networks
✅ How Information Modelling Works in OPC UA PubSub
✅ Consuming OPC UA PubSub using Third Party Applications
✅ OPC UA PubSub over TSN explained
✅ Use Cases for OPC UA Client-Server combined with PubSub
✅ Sensor to Cloud Using OPC UA PubSub
✅ Security mechanisms in OPC UA PubSub communication
✅ uOPC PubSub Bridge overview
✅ About Utthunga
Sunday Sep 04, 2022
Sunday Sep 04, 2022
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
Thursday Aug 25, 2022
Thursday Aug 25, 2022
Done right, the digital transformation of manufacturing enterprises has less to do with plugging in smart objects to collect data from the factory floor.
Rather, it has a lot to do with laying down a reliable, secure, and scalable data processing infrastructure in such a manner that it allows you to automate your entire manufacturing business process.
And for engineers and architects tasked with building IIoT solutions, it involves picking the right tools for each part of your data processing pipeline, from the edge of the network to systems at the highest level of your enterprise.
To understand why and how to achieve that using open source tools, I had a conversation with Jeremy Theocharis who is the Co-Founder and CTO of United Manufacturing Hub, a company centered around an Open Source Project that combines state-of-the-art IT/OT tools to help engineers build Industrial IoT solutions.
Here's the outline of our conversation which you can watch by clicking on the link below:
Outline:
Challenges in IT/OT Integration Introduction to United Manufacturing Hub (UMH) Why Open Source Matters Criteria for picking the core technologies for the UMH stack. Modernising Industrial Systems Architecture Using Microservices Why MQTT and Kafka for the IIoT Data Pipeline The role played by OPC UA in the UMH stack Unified Namespace Architectural Approach Factors influencing the design of the UMH DataModel Multisite Data Integration Using UMH Machine Vision Use Cases on the UMH Platform Historian vs Open-Source databases
Thursday Aug 25, 2022
Thursday Aug 25, 2022
By now, It's no longer up for debate whether artificial intelligence will permeate the industrial automation space as much as it has the commercial sector.
The biggest challenge, I'd imagine, is how do we build a robust enough nervous system that brings data to the AI agents at the industrial edge for processing, with unlimited horizontal scale.
To understand in-depth how that could work, I invited Angelo Corsaro for a chat.
Angelo is CEO and CTO at ZettaScale Technology, a company working to bring to every connected human and machine the unconstrained freedom to communicate, compute and store anywhere, at any scale, efficiently and securely.
Up until recently, Angelo was CTO at ADLINK Technology, a company that provides edge software and hardware for building and deploying Edge AI solutions, and it is from ADLINK where ZettaScale was "spinned-off".
Further, Angelo was one of the original members of the Data Distribution Service connectivity standard at the Object Management Group, where he was also a Member Board of Directors.
Below is the outline of our conversation to the linked video
Outline
Edge Computing as a Cloud-to-device continuum Benefits of intelligent edge computing in Industrial Automation Example Applications of AI at the Industrial Edge Challenges in building and deploying Intelligence at the Industrial Edge Edge AI Architecture for implementation in Manufacturing Approach for Big-Data Driven Edge-Cloud Collaboration in Industrial facilities High-Performance Real-Time Communication at the Edge using Eclipse Zenoh and Cyclone DDS OS Projects Integration of Eclipse Zenoh with MQTT ZettaScale, what it is, why it exists, and key concepts Security Threats and Countermeasures in Edge Computing for IIoT Architects The Role of 5G in Industrial Edge AI ZettaScale team and vision for the future of building industrial systems
Wednesday Feb 23, 2022
Wednesday Feb 23, 2022
Naturally, standard Ethernet does not guarantee real-time communication.
So, to provide guaranteed cycle times and latencies for machine control and process automation using Ethernet, vendors implemented real-time Fieldbus protocols on top of it.
Thereby creating a specialised type of Ethernet that is unusable for anything else, and causes fragmentation of industrial networks due to incompatibilities of Fieldbus protocols.
But yet, for the success of Industry 4.0, what is required is one type of Ethernet network that is usable for both, executing time-critical OT processes, as well as for non-time-critical collection of data from machines in a standardised and vendor-independent manner.
And this is what Time-Sensitive Networking (TSN) seeks to achieve.
To understand how TSN is able to solve these challenges and its combination with OPC UA, I had a conversation with Bhagath Singh Karunakaran
Bhagath is the CEO and Founder of Kalycito Infotech Pvt Ltd, India, an IIoT Software Solutions Company with Full-Stack device to cloud capabilities, and is a recognised thought leader in this space due to its pioneering effort to create an Open-Source ecosystem around OPC UA and TSN on real-time Linux. Including the world's first OPC UA Pub-Sub implementation.
You can watch our conversation below, and here's the outline:
✔️ What is TSN and how does it work
✔️ Advantages of TSN over traditional Industrial Ethernet networks.
✔️ Running Fieldbus Protocols on TSN
✔️ Core elements of TSN for achieving time-deterministic communication
✔️ Requirements for machines to participate in TSN network
✔️ Importance of achieving field-level communication using OPC UA
✔️ Combination of OPC UA with TSN
✔️ The role played by OPC UA over TSN play in Industry4.0
✔️ OPC UA Pub-Sub over TSN for Sensor to cloud communication
✔️ Use cases of OPC UA over TSN in Manufacturing
✔️ Convergence of OPC UA over TSN and 5G for Industry 4.0
✔️ Commercialised products implementing OPC UA over TSN
✔️ Open Source crowd-funded OPC UA and TSN project
Friday Feb 18, 2022
Friday Feb 18, 2022
As the saying goes, "Don't throw the baby out with the bathwater".
Many people in the manufacturing space are quick to dismiss Web 3, and justifiably, because of the recent sensationalism created around it by Big Tech.
And yet, Web 3 has the potential to massively impact how we build production systems. In fact, the success of Industry 4.0 lies, to some extent, in the enablement of decentralised peer-to-peer networking of factories, with decentralised storage, compute, and connectivity.
In any case, now that Web 3 has come to the fore, I decided to invite Rex St. John, a passionate advocate for Web 3, to discuss the Application of Web 3 in Industrial Edge Computing.
Rex has spent over a decade building developer relations programs at companies such as Intel, ARM, and NVIDIA, where he is currently building a global software ecosystem for NVIDIA Jetson.
Here's the outline of our discussion linked below.
✔️ What Web 3 Really is and its Key Drivers
✔️ How will Web 3 impact Industrial IoT in Manufacturing
✔️ Current challenges of Web 3 Application in Industrial Edge Computing
✔️ Architectural Approach for decentralizing compute, storage, and connectivity using Web 3
✔️ Existing projects for decentralised compute, storage, and connectivity.
✔️ Subsidising hardware for Web 3 in Industrial Edge Computing
✔️ Practical Use Cases of Web 3 and Edge Computing in Industry
✔️ Distributed Training of Artificial Intelligence models using Web 3
✔️ The future potential of Web 3 and Edge Computing in Industry
Monday Jan 17, 2022
Monday Jan 17, 2022
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.
Thursday Nov 04, 2021
Thursday Nov 04, 2021
The biggest challenge in the transition to Industry4.0 lies in the horizontal and vertical integration of information flow within and across manufacturing organisations, and the digitalisation of the engineering processes involved.
Among the technologies and standards developed to enable this flow of information, is the compelling combination of AutomationML, OPC UA, and the Asset Administration Shell.
To discuss this combination, I talked with Dr. Miriam Schleipen, the Chief Research Officer at EKS InTec GmbH where she deals with semantic interoperability in automation ecosystems based on Digital Twins and their application in automation environments.
Miriam is head of the joint working group of OPC foundation and AutomationML e.V., leads the German Glossary Industrie 4.0, and participates in national and international standardization groups dealing with semantic interoperability for Industrie 4.0.
Outline:
✔️ Introduction to AutomationML and its role in Industry4.0
✔️ Why and How AutomationML Integrates with OPC UA
✔️ Fundamentals of The Asset Administration Shell
✔️ Defining an Information Model Inside an Asset Administration Shell
✔️ Interrelation of the Asset Administration Shell and the AutomationML
✔️ Software Tools for Describing Models in AutomationML
✔️ Standardisation of the Asset Administration Shell
✔️ Benefits and Uses Cases of AutomationML, AAS, and OPC UA Combination
✔️ Best Practices for Implementing Asset Administration Shell Ecosystems
✔️ Role played by AutomationML, AAS, and OPC UA in Digital Twin Implementation
✔️ Distributed Digital Twins for Smart Manufacturing
✔️ AutomationML Association
✔️ EKS InTec GmbH