Understanding edge computing for manufacturing
Edge computing is a top priority for organizations looking for effective ways to modernize operations and implement virtualization. The manufacturing industry is making a shift toward merging information technology (IT) with operational technology (OT) for more transparency, improved efficiency, and more timely data analysis.
Manufacturers need to reduce plant emissions, create richer customer experiences, support resilient supply chains, as well as minimize downtime, and detect problems before they impact production.
Network functions ranging from predictive analytics, elevating control and monitoring processes with automation, improving production, eliminating high latency, and optimizing logistics are only some of the use cases that inspire manufacturers to employ an infrastructure that has the bandwidth to manage the massive amounts of data that endpoint devices send and receive.
Edge computing (as opposed to cloud computing) allows manufacturers to implement automation across factory floor and supply chain processes through advanced robotics and machine-to-machine communication closer to the source, rather than sending data to a server for analysis and response. For example, scanning sheet metal to detect fatigue, monitoring flow through pipes, or keeping track of automated machine cycles, to improve latency, resulting in faster analysis and correction.
Gathering, analyzing, and acting on data on the factory floor in real-time offers profound benefits. Reducing downtime, accurately predicting maintenance, and improving overall product quality results in higher yield, reduced waste, increased throughput, and lower overall costs.
Challenges
Edge computing is already a large part of the manufacturing industry’s landscape. However, even companies that are accustomed to operating across multiple locations are struggling to remove silos by bringing IT and OT together.
Advances in manufacturing technology have caused existing factory equipment to become outmoded. New regulations that call for more stringent monitoring of power consumption, vibration data, and predictive maintenance also contribute to the need for edge computing solutions that use existing tools, can be administered by minimal staff, and are flexible enough to adapt and grow as demands change.
Each organization has different requirements. However, all end users rely on the need to gather, curate, analyze, and then act on data that is being communicated from many different sources, often across multiple locations or various data centers. Funneling that data through a centralized network causes bottlenecks and increases latency. A common horizontal framework that spans the entire IT infrastructure can help manage data sources that are distributed across many locations.
Some companies have existing edge solutions that are composed of a mismatched variety of hardware housed in small spaces with little room to expand. Components are added as needed, then spliced together to handle specific processes and technologies. Over time, this increases complexity, making it ever more difficult to manage and scale. Cloud services and Internet of Things (IoT) solutions allow manufacturers to manage growing infrastructure needs without having to dedicate their own limited real estate.
Managing the large numbers of edge computing sites, which gather massive amounts of data generated by edge devices, can prove to be a major challenge. A manufacturer may have several locations, each with a number of automated machines and processes that stream thousands of data points per minute. As demand grows, so does the amount of data that is passed through servers, causing latency. In some cases, this is a minor inconvenience. In others, a delay can cause serious problems, resulting in lost productivity. Flexible, long-term scalability is critical for manufacturers to respond quickly to changing circumstances with a minimum of disruption to operations.
Edge computing and open hybrid cloud
There’s no doubt that edge computing offers a level of productivity that is unmatched by traditional technologies. But it’s not a total solution for all of the challenges manufacturers can encounter. Edge computing becomes more powerful when used in concert with an open hybrid cloud infrastructure.
Open hybrid cloud infrastructure helps manage the data gathered from multiple locations to more easily adapt to changes in demand with flexible compute, network, and storage resources. It enables manufacturers to gather insights, analyze problems, and develop solutions faster.
Using public and private clouds from different sources to handle a variety of tasks allows companies to dedicate existing on-premises infrastructure for critical functions. Open hybrid cloud infrastructure provides flexibility in resourcing and makes it easier to create a cohesive server environment that is flexible enough to adapt to evolving needs. Data on the edge is managed more efficiently.
Historically, manufacturers have relied on proprietary solutions and vertically-integrated vendors to address their immediate edge computing needs. But that is changing as leaders are leaning toward solutions that can grow and respond to changing circumstances. Having a platform that can flex and expand without proprietary limitations enhances interoperability and allows for seamless expansion, smooth growth, and unfettered innovation.
An important benefit of adopting edge computing on the open cloud is removing the manual configuration of disparate systems and applications, which is time-consuming and prone to errors. Managing and scaling workloads is possible with minimal operational overhead. Teams can focus on developing applications to improve monetization, rather than configuring systems or performing routine tasks.
Edge computing in a hybrid cloud environment also supports redundant mechanisms, allowing processes to continue working when a component fails or needs maintenance. This results in decreased downtime, improved safety, and a longer life cycle for components.
Red Hat’s approach to edge computing for manufacturing
The future of manufacturing is one in which decisions are made autonomously right on the factory floor, based on real-time conditions. Edge computing helps to integrate all aspects of the manufacturing process, including design, supply chain, and operations. This allows companies to react to changes faster with more flexibility and less waste. Edge computing coupled with open hybrid cloud infrastructure can provide real time transparency, accelerate software-driven production, maximize scaling, and leverage big data for analytics across the IT infrastructure.
Adopting edge computing requires transformative thinking. Implementing the tools and processes necessary at potentially thousands of sites with little to no IT staff is challenging at the best of times. In addition, each edge tier has varying requirements regarding the hardware footprint, the physical operating environment parameters, and with that, the cost. Most often, a single vendor isn’t able to provide an end-to-end solution. Interoperability depends on obtaining resources from multiple vendors to create consistency across the IT architecture.
Why Red Hat?
Red Hat’s broad portfolio of solutions helps manufacturers plan, adopt, and implement the technology necessary for successful transformation to edge computing on an open hybrid cloud. Red Hat® Enterprise Linux® provides the foundation with a large ecosystem for building and running applications and containers. Red Hat® OpenShift® is a high-performance Kubernetes environment for building, deploying, and managing container-based applications across any infrastructure—physical, virtual, or in the cloud. Red Hat Edge provides the platforms to support your workloads wherever you need them. An Open Innovation Labs residency helps connect innovation with tools to bring your team’s ideas and potential to life.
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