Edge or Cloud: What's Best for Manufacturers?

By Manish Jain, Product Leader for Edge Analytics and AI Applications, and Achim Thomsen, Director of Common Connected Applications, Rockwell Automation

The 2023 MLC Data Mastery and Analytics survey

found that more than one-third of manufacturers say the volume of data they’re collecting has at least doubled in the last two years, and nearly 20% say the amount of data has at least tripled. While this data surge presents opportunities for manufacturers, it also presents a critical question: where should manufacturers process and analyze this constantly increasing volume of information?

Enter cloud and edge computing, two distinct approaches to data processing in industrial data management. Cloud computing, with its centralized servers and vast storage capacity, offers scalability and accessibility. On the other hand, edge computing brings processing power closer to the data source, supporting real-time decision-making and low latency.

Both cloud and edge computing have advantages and limitations. Understanding these nuances is imperative for manufacturers to make the right decision that aligns with their unique digitization goals.

The Cloud Advantages

Cloud computing has revolutionized data management by shifting away from on-premises infrastructure. This computing paradigm allows manufacturers to transmit vast amounts of industrial data to IT and operational technology (OT) applications through an Internet connection, unlocking a range of benefits:

• Scalability: Cloud computing offers significant flexibility to adapt to dynamic business needs. This allows manufacturers to easily adjust computing resources based on demand fluctuations, such as varying workloads or evolving data-processing demands. Whether experiencing a sudden surge in data processing needs or periods of reduced activity, cloud platforms provide the agility to optimize costs and maintain operational efficiency.  
• Cost-Effectiveness: One advantage is that outsourcing software and infrastructure management to cloud providers reduces the need for dedicated IT personnel and costly hardware. This cuts costs and simplifies operations.
• Accessibility: Cloud computing enhances accessibility by supporting seamless data access and collaboration from any location with an Internet connection. Teams can work collaboratively and access data in real time, irrespective of geographic boundaries. Facilitating remote work empowers employees to be productive and make informed decisions.

Cloud and Edge Limitations

Cloud and edge computing offer immense potential for businesses, but they both also have challenges.

Cloud computing’s dependence on connectivity can be a significant hurdle for industrial settings. Constant Internet access isn't always guaranteed in remote locations, factories or situations with fluctuating network strength. This can lead to disruptions in operations, delays in decision-making, or hindered efficiency.

The sheer volume of data generated by industrial processes can also make cloud-based processing expensive. The constant data flow not only incurs high costs, but also can create bottlenecks and potential lags in processing.

Perhaps the most critical limitation of cloud computing for certain applications is its inherent latency. The time it takes for data to travel to the cloud, be processed, and return with instructions can range from seconds to minutes.

This delay is unacceptable for applications demanding real-time responses, such as automated industrial processes. In time-sensitive scenarios, even a minor delay can have significant consequences, impacting operational efficiency and potentially compromising safety.

While edge computing offers solutions to the cloud's limitations, it comes with its own set of drawbacks. Managing a vast network of edge devices and sensors distributed across various locations adds significant complexity to the IT infrastructure. This requires specialized expertise and can strain existing IT resources, especially for smaller organizations.

The additional hardware and software needed to implement edge computing can also translate to higher costs compared to traditional cloud-based architectures. This can be a barrier for manufacturers with limited budgets or those hesitant to invest in a new infrastructure.

Best of Both Worlds

Both edge and cloud computing offer unique advantages. The "best" choice hinges on the specific needs and priorities of the manufacturer. This involves careful consideration of factors such as cost, security, latency and the reliability of Internet connections.

Industrial leaders might find cloud solutions more advantageous when dealing with applications that demand extensive computational power and storage capacity. Large-scale data analytics, machine learning, and centralized data processing are instances where the scalability and flexibility of cloud infrastructure can shine.