In recent years, there has been a computing exodus from closed networks to the cloud. Now, the next evolution in compute power is taking place at the edge. Gartner finds that around 10% of enterprise-generated data is now created and processed outside of a traditional centralized data center. That number is growing and, in the next five years, is expected to reach 75%.
Edge computing is a type of compute power that operates between smart objects and the cloud. Building on the cloud’s foundation, the edge expands possibilities for IoT, 5G, AI and machine learning as they take root and grow. As prospects for these technologies continue to expand in scope, it is becoming clear that edge computing is the future for data processing. Working in tandem with the cloud, edge computing makes possible technologies of the no-so-distant future such as autonomous vehicles.
In the manufacturing space, the explosion of data is catalyzing the transition to the edge. Industrial Internet of Things (IioT) and smart technologies have infiltrated every aspect of manufacturing in the form of operational technology (OT) generating data much too large to transport to the cloud. Even after refining output streams, the information that is relevant can still take days to upload. As a result, essential data has every opportunity to get lost on the factory floor without edge computing.
Making the shift to new hardware easier
The thought of having to overhaul or replace legacy systems is often a detriment when manufacturing professionals think about processing data at the edge. Companies have already invested in the technologies they have right now, and many may view the prospect of updating existing systems as a costly hurdle and a hindrance. However, edge computing is well on its way to becoming the new standard across IIoT industries. Since the edge collaborates with the cloud, these systems integrate seamlessly. Once implemented, networks at the edge will establish a new paradigm for data processing.
Edge computing’s true return on investment comes in the form of problems prevented. Edge computing’s ability to process data in real time or near real time can make an enormous difference in a company’s ability to make quick, yet informed, decisions and avert pauses in production. Being able to analyze data in real time gives operators the ability to carry out successful predictive maintenance. This, in turn, allows them to prevent costly shutdowns, and in some cases emergencies, which hinder production efficiency or compromise employee safety.
Manufacturers are always looking for new and innovative ways to boost productivity, reduce downtime and improve safety. For example, as the rollout of 5G commences, more and more organizations are turning to artificial intelligence (AI) and IIoT for innovative solutions. This kind of change is often far from simple. All this technology is usually running on legacy software, meaning that installing a new system requires a costly overhaul involving connecting and streaming processors to the cloud. Thankfully, this is unnecessary for the implementation of edge computing technology. With just a simple Ethernet port conversion, these same machines can stream real-time insights directly to an edge solution.
Bridging the gap between IT and OT
Edge solutions provide a critical opportunity to bridge the gap between information technology (IT) and OT. OT is an abundant source of data. On the factory floor, the information a company can gather from its OT devices is crucial in discerning opportunities to make improvements, maximize efficiencies and expedite production. Smart machines in modern factories create a vast array of data points which can provide the necessary insight to improve a company’s workflow in meaningful ways.
OT has always worked independently from IT and its data streams have historically functioned in silos within organizations. This is because IT requires a centrally organized infrastructure which is typically managed through cloud environments. These are suboptimal for OT devices due to the lack of autonomy they require. Edge computing unites these two technologies through local data collection that is housed directly on the factory floor while also providing centralized management and data to the cloud, creating an environment where IT and OT can function cohesively.
Edge computing also provides another feature which is advantageous in manufacturing facilities: reduced downtime. When a system is down, every second equates to dollars lost for an organization’s bottom line. Manufacturers recognize this and have spent years implementing smarter processes to help reduce downtime in their processing lines. However, in some manufacturing environments, a millisecond of data sampling time can be the difference between predictive maintenance and a mechanical shut down. Since edge computing processes data directly at the source, companies are able to minimize the amount of time and bandwidth required for data transmission and prevent these costly shutdowns.
In the same way, safety is also improved at the edge. Machine operators are able to process the data from their smart machines fast enough to allow them to make snap decisions at a moment’s notice. The unavoidable lag time that comes from uploading data to the cloud can be the difference between life and death for machine operators when something goes wrong. An increasingly common source of data being uploaded to cloud networks comes from video monitoring technology which assures compliance with COVID-19 protocols. This data is large, expensive, and creates significant lag. After edge computing is introduced to systems with video monitoring feeds, sending all this data to the cloud becomes unnecessary. Instead, organizations can implement an AI solution, in conjunction with an edge solution, to highlight when protocols are violated and move only event data to the cloud.
The value of edge computing
There are so many ways in which edge computing can maximize efficiency for organizations across a wide range of industries. It minimizes bandwidth, a crucial element in technological advancement, as more and more machines become smart objects tied to IIoT networks in an increasingly wireless world. Organizations are better able to make the most of the data they have by filtering it intelligently with an edge solution.
Edge computing reduces operational costs for companies by preventing shutdowns and errors, eliminating unnecessary data streams, and maximizing efficiency. In these ways, implementing an edge solution often propels a substantial ROI. This type of compute power is also vastly more reliable. Disruptions will still occur, of course. Power outages, mechanical troubles and issues related to power sourcing are all unavoidable. However, edge computing ensures, at least, that any disruption in business will not be the result of an unavailable network.
Security also benefits from the implementation of edge computing. Cloud networks that house vast amounts of sensitive data are liable to be breached. Once exposed, that data can become a big problem for any organization. Using an edge solution takes this data storage out of the equation with direct transmission from the source. Thanks to edge computing, companies no longer need to worry about housing sensitive data with a third party. Similarly, data storage is sometimes impossible due to legalities and compliance considerations. Because data can be transmitted directly at the edge, organizations have no need to assess the storage of such information on a cloud.
Lag times are a hindrance and, without 5G and edge solutions, they are all but unavoidable. Data cannot move faster than the speed of light. As such, cloud networks alone are no longer an option for technologies like self-driving cars which require the ability to make instantaneous decisions. Seconds or even milliseconds of lag due to latency can mean the difference between life and death for smart technology operators.
Edge computing at work
The most exciting part is that the applications for edge computing in the manufacturing space are all but limitless. They enable video processing for quality control in iron smelting lines. They create an event sourcing bus on the factory floor, facilitating the rapid integration and deployment of new data analytics. They also allow for local 5G breakouts to communicate with smart devices such as autonomous vehicles as they come off the factory line, saving the cost of creating a connection over a carrier’s network.
Edge computing truly is the future for IIoT technologies. 57% of mobility decision makers say that edge computing is on their roadmap according to Forrester. Those who choose not to adapt will be left behind. Edge computing is the key to maximizing the benefits of employing smart technologies and IIoT networks. Edge computing will not only bolster the bottom line for organizations, it will also ensure safety and productivity by ensuring that no data gets lost on the factory floor.
Paul Lyman is the President and Co-Founder of Hivecell, the Edge-as-a-Service company. Paul has 30 years of experience overseeing engineering projects in avionics and software, from large scale enterprises to military projects to start-ups. He is a graduate of Wichita State University.