Time is money, and when an automated process stalls, the costs stack up by the seconds. Downtime is expensive to productivity and throughput, but also to security and reputation. And while processing and storing data in the cloud has transformed industrial data management capabilities, it’s not ideal when you’re talking milliseconds of a data center breach or utility failure. That’s where edge computing comes in.
It might sound like a buzzword, but it’s actually a simple way to bring all that data back from the cloud and into your facility. Data is generated and processed at the edge of the network, hence the term. Since all the data doesn’t have to be sent to a centralized cloud before it’s processed, it offers manufacturers a more efficient way to make decisions; analysis happens right there on the floor, allowing the system and operator to make split-second decisions.
Edge computing reduces reliance on internet connectivity for industrial data analytics, making the term “real-time” as true as it gets. And it has several benefits to offer any sector that relies on automation:
1. Faster Response Time
The big benefit of edge computing is the local data processing. Say a robot arm indicates an obstruction on a conveyor line, or a mixer detects a recipe anomaly. Edge computing ensures that these defects are caught immediately, slashing downtime and preventing subpar product from leaving the facility. Because data is processed right at the source, machines can react in real time, which minimizes risks and improves operational agility.
2. Improved Process Reliability
Internet connectivity is no longer the be-all end-all of automation; it comes with its risks. Cloud-based systems rely on internet, so when it goes down, operations are interrupted and your networks left vulnerable. Edge computing allows critical operations to continue even if access to the cloud is disrupted. Production lines are more resilient to adverse events because edge devices can continue to process and analyze industrial data and execute automation logic without relying on the cloud.
3. Enhanced Security & Compliance
The security of intellectual property is integral for most operations, whether proprietary batching, confidential data, or sensitive product design. And compliance to certain data regulations is not optional in sectors like aerospace, pharmaceuticals, and government operations.
Transmitting data to a cloud to process introduces vulnerabilities. And in some sectors, data is even required to remain in the facility on a local system. Edge computing allows sensitive data to be processed in-house, which keeps the manufacturer in control of sensitive information. They can decide what data is shared with the cloud and what data needs to be kept under lock and key.
4. Upgraded Predictive Maintenance
Automation platforms and AI have already made predictive maintenance an accessible asset to manufacturers. But just like edge computing provides quicker insight into real-time processes and problems, it also all but eliminates lag in detecting warning signs of equipment failure. Whether end-of-life/obsoletion issues or simply required maintenance, edge computing puts operators ahead of the maintenance game, which prevents costly defects and downtime.
5. Superior Ability to Scale
Scalability is a major attraction of advanced control system software and automation equipment. Flexible platforms and custom system design set up a facility for future growth. But what about scaling across facilities? Many manufacturers need to apply similar technology and processes across multiple locations. But cloud-based systems can create bottlenecks if overloaded and coordinating operational data more complicated than it needs to be.
Edge computing supports scalable architectures by filtering shared data. It enables localized control systems tailored to that facility’s specific processes, physical layout, and size, but still connected to the broader multi-facility network. This also improves operational agility because each facility can make present decisions specific to their needs.
At the same time, strategic data can be shared with the cloud and used to analyze trends across facilities. Edge computing offers a balance between autonomy and connectivity, which allows simpler implementation of similar control system solutions across facilities without overloading the network.
Edge Computing + AI: An Automation Superpower
Pairing AI and edge computing technology combine to create what is essentially an autonomous facility management system that learns, adapts, and optimizes all on its own. AI models at the edge of the network can be programmed with algorithms that continuously fine-tune operations in real time without the cloud lag. This unlocks three seriously valuable capabilities:
- Detection of anomalies in product dimensions, texture, consistency, etc.
- Optimize energy uses in real time based on demand
- Adapt robotic processes to different products
The result? Intelligent factory automation that self-optimizes, responds on its own, and is scalable.
Getting Real with Real-Time Data Processing
Edge computing is clearly the future of Industry 4.0, but not without its challenges. Cybersecurity during migration is always a concern, as is initial investment. And there is a possibility some legacy control systems won’t be able to integrate with edge computing technology. However, with a Main Automation Partner specialized in custom, strategic control system solutions, any automation obstacle can be overcome.
Edge computing represents a foundational shift in how manufacturers are able to use their data. Analytics performed at the edge of the network improve agility, flexibility, response time, security, compliance – pretty much every aspect of floor operations stands to benefit from the application of edge computing. This new development in automation empowers facilities to operate smarter, faster, and more reliably in increasingly competitive markets.
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