What is Edge Computing? Pros, Cons, and How to Get Started

The fourth industrial revolution is nigh upon us and has already given rise to industrial computers, factory automation, and so much more. And new innovations show no signs of stopping! 

A survey conducted by the Manufacturers Alliance or Productivity and Innovation highlights this fact. According to them, investment in new tech will be a key factor in reversing the rather sluggish performance manufacturers have suffered over the last couple decades. In fact, advancements are now occurring so quickly, we’ve begun to experience bottle-necking in other parts of the manufacturing process. 

We’re no longer worried about a lack of sophisticated tech. Rather, concerns are now placed on two things.

• Manufacturers’ ability to bring in new workers to meet their demands for more skilled labor. 
• Manufacturers’ ability to manage the almost absurd amount of data that’s drawn from new fourth industrial revolution tech.   

And while we’ve already covered the topic of manufacturing’s skilled labor shortage, today’s topic focuses on the latter issue. More specifically, we’re discussing how Edge Computing has helped manufacturers optimally use their data to drive up productivity and ROI. 

What is Edge Computing?

Edge computing is the practice of bringing data storage and computation closer to the actual devices where data is being gathered. Essentially, it refers to running less processes on the cloud and moving those processes to a local facility to improve performance. 

Of course, this doesn’t mean completely removing all of your operations from the cloud. IoT devices are going to be an integral part of the fourth industrial revolution. Denying your factory those tools is simply going to harm you in the short and long term. 

The idea behind edge computing is, rather, to make as many processes as you can internal. In some cases, this can mean storing data on a computer or industrial tablet within your own facility, or even having devices with internal components capable of storing its own data instead of immediately offloading it all onto the cloud.

Benefits of Edge Computing

On many factory floors, there are several machines each gathering data that is then sent to a central cloud server where it’s processed and analyzed for things like preventative maintenance, automation, and more. The issue here is that, with such vast amounts of data being sent to off-site servers and back, a considerable amount of bandwidth across a factory’s entire server is being consumed, resulting in heavy latency. 

Edge computing tackles this by taking some of the load that would normally be sent to an off-site server and processing it on-site. This diminishes latency, meaning real time data drawn from your devices can be exactly that, real time, resulting in better diagnostics, preventative maintenance, and responsiveness on the floor.

Edge Computing Examples

Edge computing has several applications, hardly limited to the few we’ll highlight here. These use cases highlight how effectively strain can be taken off the cloud for improved in-house productivity. 

Camera Surveillance

An hd surveillance camera does more work than many might immediately consider. It records hours’ worth of high definition video then sends that video over to a central cloud computing server where it’s put through a motion-detection algorithm, ensuring only clips showing actual activity are saved to the database. And that process is repeated several times a day across multiple cameras, devouring your bandwidth if you let it.

With edge computing, those cameras would have their own internal computers capable of running those motion detection algorithms. This means the cameras would only save and send footage that detected movement over to the cloud server, shaving hours and hours of useless footage that would have been sent prior. Significantly less footage is sent, significantly less bandwidth is consumed, and much less latency occurs across your floor.

Fleet Management

Simply installing an edge gateway on the dash of your delivery trucks can take edge computing beyond just the devices within your factory. Through these gateways, data on things such as vehicle diagnostics, collision prevention, and even driver fatigue drawn from patterns in recorded video can be collected. 

Instead of sending all of this data to the cloud, it can be processed internally and used to notify drivers in real time about broken parts or if they’re about to drift into another lane or get into a collision. Not only does this optimize your fleet and delivery times, it considerably cuts down on the amount of data being sent to the cloud.

Predictive Maintenance

One of the greatest productivity stopgaps is a broken down machine. Predictive maintenance can help avoid these costly breakdowns, but only if issues are addressed before they have a chance to grow. Latency, of course, impedes this process when it jeopardizes getting those crucial updates on time when something can still be done to prevent machine breakdowns.

With edge computing, instead of having the data collected and then sent off to cloud centers for analysis, that data can be analyzed in-house on an HMI panel, providing real time preventative maintenance reports, and THEN sent off for further analysis. This way, red flag signs of a breakdown can first be spotted in-house in real time and addressed. Naturally, this also cuts down on strain on your bandwidth and cuts down on latency.           

How to Get Started in Edge Computing

Like many manufacturing initiatives, it’s important to determine whether or not your operation stands to benefit from edge computing. Do you have several IoT devices drawing in tons of data? Do you plan to in the future? Have you noticed latency across your machines and software? If your answer to any of these is yes, it might be worth at least considering if not now, then in the future. 

Also ask yourself where you stand to gain the most benefit should you use edge computing. Does your operation suffer from frequent, unexpected breakdowns? Consider edge computing devices for your in-house machines. Are you looking to specifically boost your fleet performance? Maybe invest in outfitting your trucks with the proper edge computing hardware. Everyone’s approach will be tailored to them specifically.

Once you’ve decided to employ edge computing and know where in your operation you want to incorporate it, consider investing in some IoT Edge Gateways. Edge gateways are physical devices or software that function as connection points between IoT sensors and cloud centers, operating as locations where data can be pre-processed before being sent to those cloud centers.    

Considerations Before Investing in Edge Computing

Of course, in the age of technology we find ourselves in, incorporating new tech is never as simple as plugging in a new shiny piece of hardware and experimenting. Cybersecurity threats are very real and every new piece of tech with internet connectivity provides one more gateway through which cybercriminals can attack. With that in mind, be sure you’re staying up to date on the latest methods of cyberattack as well as your industry’s cybersecurity best practices. 

Another thing to consider is that edge computing requires considerably more complex machinery and smart technology. Devices like cameras can’t just perform one operation. For the sake of edge computing, they’ll need to have their own processing capabilities and more. While the return on investment is very promising, these devices  can be more costly than you’re used to, so budget accordingly.  

Join the Revolution

Sometimes, just tossing in the latest and greatest technology isn’t the best way to optimize and modernize an operation. Often, making sure your operation has foundations such as edge computing in place to support that new technology will help you derive the greatest ROI. For more information on how you can start building out those foundations, contact an expert from Cybernet today.