Cloud vs. edge computing in manufacturing
Edge and cloud computing in manufacturing complement each other, supporting more responsive, autonomous, and data-driven operations.
Edge and cloud computing in manufacturing complement each other, supporting more responsive, autonomous, and data-driven operations.
Modern manufacturing is growing more complex and distributed by the day. To compete, your operations must evolve to be more connected, data-driven, and time-sensitive than ever. Unfortunately, most traditional on-premises systems can’t keep up – especially when data is stored in silos, making it difficult to access and use to make quick decisions.
Enter cloud and edge computing. Cloud platforms allow manufacturers to access real-time data and coordinate activities from anywhere. They provide the computing power and security to scale up operations across multiple lines, plants, and suppliers. And with edge solutions, manufacturers can quickly transmit and analyze raw machine and equipment data collected from embedded sensors and devices right on the factory floor – for immediate action.
Cloud computing platforms provide a centralized place for storing data and running advanced analytics. They also tightly integrate core manufacturing systems – ERP, MES, IoT, supply chain management, and more – providing visibility across them. Cloud platforms really act as the operational foundation for digital and smart manufacturing.
In contrast, edge computing solutions run on gateways and industrial computers, processing data in close physical proximity to machines and devices. Edge systems extend the cloud to the shop floor, where they can either transmit and receive data from the cloud or they can trigger automated actions based on certain conditions. By processing data so close to its source, you get heightened speed and actual “real-time” responses even when connectivity is down.
Cloud computing in manufacturing has become essential for companies that need to scale up operations and act on advanced intelligence. Here’s how cloud computing supports better operational outcomes:
The cloud provides a common view of data captured from multiple factories and sites that can be accessed with an Internet connection. Teams can use this up-to-date information to track demand and material constraints, coordinate operations, and improve performance.
Today’s cloud platforms offer impressive computing power and flexible storage that can scale to meet growing production demands. They make it easier to add new applications, technologies, and industry-specific processes across the organization without disruptions.
Embedded AI and advanced analytics technology in cloud platforms can analyze the massive volumes of IoT data generated by industrial equipment and operations. They can then make intelligent predictions, forecasts, and recommendations to guide workflows and processes.
Cloud platforms provide automatic updates for the latest technologies, security protocols, and enhancements. They support an agile approach to innovation where manufacturers can rapidly test and roll out new approaches, such as AI-driven scheduling.
Edge computing is essential for manufacturers who want to automate important production elements and adapt quickly to changing conditions. Here are just some of the operational advantages of edge computing:
When data from equipment is processed and analyzed close to the source, teams can respond to the changing production environment in milliseconds. Operators can adjust machine settings or processes, such as reallocating a job based on machine availability.
Data processed at the edge requires less bandwidth than sending everything to the cloud, lowering the strain on networks as well as associated costs. With the ability to filter and process data locally, only relevant insights are transmitted, improving response times.
Edge computing helps manufacturing operations continue running without disruptions when there are spotty network connections or outages. This becomes even more important for remote plants where reliable connectivity is limited but continuous production is critical.
Edge computing keeps sensitive operational and machine data on site when needed, reducing exposure to external networks. This gives manufacturers tighter control over how data is accessed and shared and helps them meet strict security and compliance requirements.
Cloud and edge computing technologies work together to support modern manufacturing. Cloud platforms provide centralized, long-term data storage, along with environments for training models, benchmarking, and coordinating workflows across the supply chain and multiple locations. Edge software allows machines to make real-time decisions, take action based on current conditions, and detect anomalies on the fly, even when operating offline. Together they form a continuous optimization loop: edge systems capture and filter data, and cloud systems analyze and improve it before sending insights back to the edge for further action.
Edge and cloud computing present manufacturers with unique challenges, but all of them can be addressed with the right strategies. Let’s take a look at a few of the roadblocks and solutions.
When implementing edge and cloud systems, it’s a good idea to start with your highest-value use cases first. For most manufacturers, predictive maintenance, quality management, and energy optimization offer the most value and ROI. By focusing on one priority area at a time, companies can keep operational disruptions to a minimum while getting up and running in these areas.
It’s also essential to build a connected architecture that can integrate your IoT devices, edge solutions, and cloud systems. Modern platforms make this process much easier. They act as a central hub with features like prebuilt connectors and APIs that help data flow everywhere you need it to, without heavy coding. An event-driven architecture is a must for manufacturers who need robots and machines to be able to trigger workflows, analytics, and automated actions. Platforms that include built-in analytics, AI, and other automation tools allow for delivering actionable and predictive insights across systems and teams.
To future-proof your business, prioritize platforms that support interoperability and scalability. For example, systems that support open standards and flexible integration not only make it easier to connect changing systems over time, but they also allow for scaling up operations as your needs – and technologies – change.
While both cloud and edge computing offer distinct advantages, their true power comes when they work together. Advanced technology like AI and predictive analytics are best supported in the cloud, but machines on the ground rely on the smart analysis and decision-making they bring. With the introduction of 5G technology, the real-time integration between them is supported on a massive scale. Going forward, more manufacturing systems will use a hybrid cloud and edge computing model, allowing for more autonomous operations where systems can learn, improve, make automatic adjustments – and ultimately, power self-optimizing smart factories.
A hybrid “edge to cloud” strategy offers the most competitive value. It amplifies the benefits of both technologies, allowing manufacturers to run faster, move toward autonomous systems, and make smarter decisions based on conditions on the shop floor and across the enterprise.
Discover how the Infor Industry Cloud Platform can help you innovate with cloud and edge computing technologies.