What are the Growth Drivers for Edge Computing?
IDC research predicts that 45% of the data created by IoT will be stored, processed, analyzed and processed at the near end or edge of IoT, and more than 6 billion devices will be connected to edge computing solutions by the end of 2023. Edge computing infrastructure minimizes the inherent challenges of cloud infrastructure (such as network latency, network bandwidth and data storage costs, security and compliance issues), which is the single most important key driver of edge technology.
The history of manufacturing is marked by major changes brought about by new technologies in the last couple of centuries. The first industrial revolution captured the power of water and steam. The second revolution brought electricity to factories, and the third revolution brought computerized automation. Today, the Fourth Industrial Revolution has ushered in the era of smart manufacturing, driven by new digital technologies for capturing and analyzing data and gaining insights and efficiency from data through not only edge computing but also artificial intelligence applications. Smart manufacturing supported by digital technology and enterprise-level infrastructure is the key to reducing downtime, improving product quality, increasing overall output, and exceeding current and future business goals.
To effectively compete in this new era, manufacturers must adopt smart manufacturing processes and the leading infrastructure that supports it. Delaying this conversion is no longer a viable option. Companies that want to remain competitive must now embrace a complete smart manufacturing journey.
How Do You Get There Though? How Do You Embark on a Smart Manufacturing Journey?
This is the journey from the factory floor using Edge Computing. Edge computing is an accelerating ramp towards smart manufacturing and Industry 4.0. In the industrial and manufacturing environment, there are two edges – the industrial edge and the enterprise edge.
Industrial Edge computing solves the problem of extracting data from traditional industrial assets such as PLC, DCS, robots and controllers, as well as the challenges of interfacing with hundreds of protocols, a large number of connected sensors, different data sources, and incompatible data formats. This is the key point for industrial equipment and factory systems to meet the digital world. Industrial Edge Computing provides the data context, repeatability, security and scale required for true conversion.
Standardized, rugged gateways can be quickly and repeatedly deployed to the field or factory floor through an IT-approved enhanced operating system. Applications for virtualization and containerized OT (Operational Technology) can be deployed at this edge to convert traditional protocols and sensor readings into analytical quality data, ready for any enterprise or business application in the data center or cloud.
Enterprise Edge deploys enterprise-level infrastructure and modern IT concepts locally on the factory floor or on-site. Systems at the edge of the enterprise need to manage and aggregate hundreds of data streams from the industrial edge. They can help bridge the gap between IT and OT organizations. Enterprise Edge Compute resources can manage Industrial Edge, deploy containerized and virtualized applications, provide cloud-native principles on Edge, and can immediately generate valuable insights through real-time and streaming analysis.
Computing at the edge of the enterprise can help manufacturers significantly reduce their cloud computing costs while providing low latency to achieve immediate response and real-time insights from the analysis of IoT data. It also addresses key regulatory and governance issues related to data sovereignty and the prohibition of cross-border mobile data.
There are usually three types of edge computing:
- Local Devices and Equipment: The local equipment can meet the defined and specified purpose. These are easy to deploy and maintain.
- Localized Data Centers: The localized data center can provide powerful storage and processing capabilities. These are pre-designed and can be customized and assembled on site. They save capital expenditures (CAPEX) very well.
- Regional Data Centers: These are closer to data sources than centralized cloud data centers. They will have higher storage and processing capabilities than local data centers, but they will cost more and require more maintenance. These edge devices can be designed to be manufactured to order or prefabricated.
Five Substantial Advantages the Edge Brings to Smart Manufacturing and Industry 4.0
One of the most frequently mentioned benefits of the edge is that it can greatly reduce the waiting time. It takes time to send the request to data centers around the world, and then wait for the response to return. Therefore, traditional cloud computing is not an ideal choice for many mission-critical applications.
Without such low-latency smart manufacturing, you will not be able to experience all the advantages of the IoT. If the connected machine on the assembly line recognizes a fault, any delay in transmitting that signal can be costly. Otherwise, parts may stop functioning or even be damaged beyond repair. Low latency is essential for the normal operations of interconnected systems. The nature of traditional cloud computing is limited in this regard.
Contrary to what is touted by most technology industries, for personal gain, cloud is not a hard requirement for the Industrial Internet of Things. You do not necessarily need a cloud IoT platform. Industry 4.0 is all about connected machines, so your manufacturing process can respond faster and smarter to changing factory floor conditions. Connecting assets will help you achieve a higher level of agility and automation. But this also increases your risk. More connected organizations can provide more attack surface and are more vulnerable to cyber attacks. However, your Industry 4.0 strategy can minimize risks through edge computing.
If you process as much data as possible at the edge instead of sending them to the cloud, the risk of interception or tampering is much lower. A powerful edge computing system allows you to keep most of your IT and OT systems in a secure network.
More Manageable Data Analytics
Bringing intelligence to your manufacturing operations means collecting and analyzing data from sensors in your equipment to make real-time decisions and predictive maintenance. However, even in a modest Industry 4.0 project, the amount of data can overwhelm existing and new systems and increase bandwidth, data storage, computing, and data science huge costs.
Processing most of the data at the edge to filter out the signal from the noise can help ensure that you only focus on the most important information, which greatly reduces the cost of data.
Edge computing can be the integration layer between your factory data and ERP systems. Just as edge computing can help you connect devices and processes without sending data to the cloud, it can also integrate factory floor data with ERP systems without cloud.
Companies are rapidly moving towards event-driven architectures and expectations for real-time automated digital processes. Edge computing can be a real-time, event-driven integration layer between factory floor data and enterprise systems that can help you accelerate and automate business processes and digital insights.
Reduced Storage Costs
Smart manufacturing involves a large amount of data that needs similar storage. Traditional local storage options can be inconvenient, and cloud services can be expensive. Storing data at the edge is the ideal middle ground. With edge storage, factories can choose to only send relevant data to their cloud solutions. By analyzing data locally and sending only the results or aggregated data to the cloud, the edge can act as a gateway.
In addition to reducing the pressure of cloud-based analytics, this also helps save storage costs. Some edge applications can even save some data locally. They do not need much storage, because each machine only processes its own operating data. The result is a segmented, organized and affordable data storage solution.
Pratiti’s PraEdge – an Edge Computing Platform
Pratiti has developed its own Edge Platform – PraEdge, for building IoT Apps on Edge to enable industrial device connectivity with a simple drag and drop interface, application deployment, and secure access to remotely located gateways.
Key Features of PraEdge are:
- It is meant for collecting data from various industrial systems, aggregate, analyse and connect it to cloud systems.
- Industrial systems include Sensors, PLCs, Industrial Controllers, SCADA systems or Historians.
- It is meant for on-premises of Discrete Manufacturing, Process Manufacturing, Power Generation, Water Distribution, Sewage Treatment etc.
- It is meant for various requirements of IoT apps ranging from data acquisition services to building full-fledged apps to run within plant firewalls.
- It is deployable on Industrial PCs or Windows Servers or Linux Servers.
- Benefits include maximum privacy & security, enablement of proactive use cases, lower bandwidth & latency issues, reduced hosting costs and real time insights and triggers.
The future of Industry 4.0 depends on edge computing. Industry 4.0 can only go so far. If the IoT is a computing step after the cloud, then the edge is the next logical step after the IoT. If this technology is not adopted, Industry 4.0 will not be able to develop all its functions and realize its maximum potential.
This transition is almost inevitable but will not happen overnight. The speed at which the manufacturing industry can enter the next industrial revolution depends on the speed at which it implements these latest technologies. To realize the maximum potential, it is important to adopt edge computing and make it a cornerstone of your digital transformation initiatives, wherever applicable. To start your edge journey, reach out to us today!