Across the manufacturing industry, innovation is happening at the edge. Edge computing allows manufacturers to process data closer to the source where it is being generated, rather than sending it offsite to a cloud or data center for analysis and response.
For an industry defined by machinery and supply chains, this comes as no surprise. The proliferation of smart equipment, robotics and AI-powered devices designed for the manufacturing sector underscores the value edge presents to manufacturers.
Yet, when surveyed, a significant gap appears between organizations that recognize the value of edge computing (94%) and those who are currently running mature edge strategies (10%). Running edge devices and smart-manufacturing machines does not always mean there is a fully functioning edge strategy in place.
Why the gap?
What is holding back successful edge implementation in an industry that clearly recognizes its benefits?
The very same survey mentioned above suggests that complexity is to blame– with 85% of respondents saying that a simpler path to edge operations is needed.
What specifically do these complexities consist of? Top among them is:
Data security constraints: managing large volumes of data generated at the edge, maintaining adequate risk protections, and adhering to regulatory compliance policies creates edge uncertainty.Infrastructure decisions: choosing, deploying, and testing edge infrastructure solutions can be a complex, costly proposition. Components and configuration options vary significantly based on manufacturing environments and desired use casesOvercoming the IT/OT divide: barriers between OT (operational technology) devices on the factory floor and enterprise applications (IT) in the cloud limit data integration and time to value for edge initiatives. Seamless implementation of edge computing solutions is difficult to achieve without solid IT/OT collaboration in place.Lack of edge expertise: a scarcity of edge experience limits the implementation of effective edge strategies. The move to real-time streaming data, data management, and mission-critical automation has a steep learning curve.
Combined, these challenges are holding back the manufacturing sector today, limiting edge ROI (return on investment), time to market and competitiveness across a critical economic sector.
As organizations aspire toward transformation, they must find a holistic approach to simplifying—and reaping the benefits of — smart factory initiatives at the edge.
Build a Simpler Edge
What does a holistic approach to manufacturing edge initiatives look like? It begins with these best practices:
Start with proven technologies to overcome infrastructure guesswork and obtain a scalable, unified edge architecture that ingests, stores, and analyzes data from disparate sources in near-real time and is ready to run advanced smart-factory applications in a matter of days, not weeks. Deliver IT and OT convergence by eliminating data silos between edge devices on the factory floor (OT) and enterprise applications in the cloud (IT), rapidly integrating diverse data types for faster time to value Streamline the adoption of edge use cases with easy and quick deployment of new applications, such as machine vision for improved production quality and digital twin composition for situational modeling, monitoring, and simulationScale securely using proven security solutions that protect the entire edge estate, from IT to OT. Strengthen industrial cybersecurity using threat detection, vulnerability alerts, network segmentation, and remote incident managementEstablish a foundation for future innovation with edge technologies that scale with your business, are easily configured to adopt new use cases— like artificial intelligence, machine learning and private 5G— that minimize the complexity that holds manufacturers back from operating in the data age.
Don’t go it alone
The best way to apply these practices is to start with a tested solution designed specifically for manufacturing edge applications. Let your solution partner provide much of the edge expertise your organization may not possess internally. A partner who has successfully developed, tested and deployed edge manufacturing solutions for a wide variety of use cases will help you avoid costly mistakes and reduce time to value along the way.
You don’t need to be an industry expert to know that the manufacturing sector is highly competitive and data-driven. Every bit of information, every insight matters and can mean the difference between success or failure.
Product design and quality, plant performance and safety, team productivity and retention, customer preferences and satisfaction — are all contained in your edge data. Your ability to access and understand that data depends entirely on the practices you adopt today.
Digitally transforming edge operations is essential to maintaining and growing your competitive advantage moving forward.
A trusted advisor at the edge
Dell has been designing and testing edge manufacturing solutions for over a decade, with customers that include Ericsson, McLaren, Linde and the Laboratory for Machine Tools at Aachen University.
You can learn more about our approach to edge solutions for the manufacturing sector, featuring Intel® Xeon® processors, at Dell Manufacturing Solutions. The latest 4th Gen Intel® Xeon® Scalable processors have built-in AI acceleration for edge workloads – with up to 10x higher PyTorch real-time inference performance with built-in Intel® Advanced Matrix Extensions (Intel® AMX) (BF16) vs. the prior generation (FP32)1.
See [A17] at intel.com/processorclaims: 4th Gen Intel® Xeon® Scalable processors. Results may vary.
Edge Computing