There is a lot to gain from diving deeper into the Industrial IoT. This huge topic requires some navigation. Avnet provides resources to help engineers find the right solution for their current and future design objectives.
The Industrial IoT is one, important, element of Industry 4.0. On a wider scale, Industry 4.0 impacts all vertical markets. It describes new ways of doing old things, and innovative technologies that enable entirely new concepts.
These concepts are rapidly gaining attention and becoming trends. It is important for all commercial enterprises to be aware of these trends because they represent competitive advantage. We could argue that it is too late to be an early adopter in the Industrial IoT, and those arriving now are the early majority. Some would say that the risk is much lower for the late majority but so too may be the reward. For this reason, trends can help shape business decisions.
The trends now visible in the IIoT go beyond buzzwords. The important difference is they reflect significant buy-in from suppliers. This leads to investment and enablement. The intention of any investment is to see a return. The enablement impacts manufacturers looking to exploit these trends.
Understanding IIoT trends
As part of its ongoing support for customers looking to capitalize on the IIoT, Avnet offers a series of resources and solutions. In a new article, Avnet looks at three of the trends shaping the IIoT right now. The full impact of these trends is yet to be felt.
The article covers three trends that converge to enable the new industrial landscape. This could be characterized as being widely distributed, on-demand, service-based manufacturing. The trends include micromanufacturing, additive manufacturing and digital twins.
These three distinct but connected aspects of Industry 4.0 are in various stages of their development. Arguably, additive manufacturing is the most mature but the way it will be used to enable new manufacturing services is still developing. Digital twins is becoming a common term but it can mean different things to different people, depending on what they need from technology. Micromanufacturing is the relative newcomer but it could be the most impactful, particularly as more companies look towards onshoring for future growth and stability.
To read the full article, visit Three future Industrial IoT trends manufacturers should think about now (avnet.com)
Discovering IIoT Platforms
Industrial systems are moving beyond routine control. Manufacturers see this and appreciate that their systems need to understand more about the operating environment. Connected sensors bring that understanding through real-time data. This presents its own challenges, but the industry is reacting to this challenge through the development of platforms.
These platforms are intended to balance simplicity with complexity and provide scalability. Abstraction is fundamental to this approach, but it also demands a new way of developing solutions. Platforms aimed at the IIoT need to understand how to provide a robust yet flexible approach to system development.
Software development is one of the biggest demands on engineer resources. Not only that, but it also provides perhaps the biggest potential for design errors. A large amount of embedded software doesn’t contribute to the OEM’s value-add, making it even more cost-intensive.
How no-code design could accelerate Industrial IoT development (avnet.com) explains how abstraction is implemented in IIoT platforms. It describes how developers can meet their objective of designing and maintaining a network of smart endpoints. It achieves this by reducing the burden of software development, potentially removing it completely.
Machine Learning in the IIoT
Artificial intelligence is becoming almost synonymous with cloud computing. It already influences commercial activities across all vertical markets but is perhaps mostly felt in the service industry today. That is changing rapidly as AI and machine learning find their way into smaller systems at the network’s edge.
Machine vision is already widely used in industrial manufacturing. There is a clear connection between machine vision and machine learning, but how simple is it to implement? How to get to market with machine learning (avnet.com) provides one expert’s view on taking that next step.
Image sensors are a key element of machine vision. The data they generate is essential in any system that uses machine learning. Avnet explores this common thread to give engineers an insight into how to bring machine learning to their machine vision applications.
Take the next step
At its core, the IIoT relies on the same electromechanical, hardware and software components that enable all modern life. As a leading distributor working with a broad supplier base, Avnet also provides design services to help its industrial customers throughout their digital transformation journey.
Avnet has been doing business the right way since 1921. It has over 1,800 FAEs available to customers, support from its extensive engineering communities, subject matter expertise and access to the latest development kits. These resources will help you move from proof of concept to production faster. Avnet supports you through rapid prototyping and small volume production.
Customers have access to over a century of experience in supply chain management, to ensure your production scales. We provide assurance of supply and flexible inventory programs through a global distribution and logistics infrastructure.
Avnet’s capabilities cover technologies and solutions, design services and expertise, and supply chain and logistics. Accelerate your digital transformation to the IIoT with Avnet.
This UrIoTNews article is syndicated fromIoTBusinessNews