Manufacturing was once seen as a lagging industry but is rapidly catching up to digital transformation plans through the deployment of technologies such as the Industrial Internet of Things (IIoT), cloud, and big data analytics.
The introduction of IoT in the manufacturing ecosystem has simplified production processes by providing real-time feedback and alerts from factory floors. The massive amounts of data collected in this way are paving the way for the application of machine learning and artificial intelligence algorithms in areas such as fault prediction and quality assurance.
At the same time, cloud adoption rates in the field are on the rise, largely due to the increased availability of cloud-based manufacturing systems, as well as productivity and CRM systems in the office.
IIoT, cloud, and big data together constitute the technological push driving the digital transformation of the sd wan edge computing industry. However, to make these technologies successful, the quality of network connectivity is essential. Enterprise networks must have a strong architecture capable of carrying the massive amounts of data generated by IIoT devices in factory floors, prioritizing critical task data from cloud-based manufacturing systems, supporting office productivity and CRM SaaS applications, and ensuring that machines running AI and ML algorithms can access data.
IIoT is a critical part of manufacturing's digital transformation. IIoT devices in factory floors collect massive amounts of data that are categorized, analyzed, and stored in data pools. Traditional backhaul architectures are heavily geared toward handling north-south traffic from users to applications rather than traffic flowing east-west from sensors to applications and servers.
According to a survey, over 50% of executives in the manufacturing industry believe that the cloud is critical, particularly in critical manufacturing areas such as the production process, supply chain, and design and prototyping. In addition to SaaS applications in these specific areas, companies also use SaaS solutions to increase productivity in the office and other areas. It is important to ensure that each of these traffic types is segmented and differentiated.
The SD-WAN solution is a cloud-first solution that supports the industry's digital transformation plan.
The SD-WAN solution provides low-latency transmission for critical task IoT traffic and ensures security by segmenting IoT traffic. The management portal provides a real-time view of traffic.
The cloud services solution can identify all major applications and accelerate them according to custom policies. It provides out-of-the-box capabilities for sd wan managed service provider.
SD-WAN in manufacturing ensures low latency and packet loss. Built-in WAN optimization and segmentation capabilities ensure that critical task data is prioritized.
A typical example is Makino, a leading manufacturer of manufacturing tools across several vertical industries that required connecting its factories in North America, Asia, and Europe over a wide area network. Data synchronization between locations took too long, increasing employee workloads processing old data, and the company realized its static, traditional MPLS backbone would be limiting as it migrated actively to the cloud.
The work of manufacturing machines and equipment involves transporting big data files of machine schematics, drawings, and statistical data. Using traditional MPLS networks, data synchronization between the Tokyo headquarters and the technical center in Mason, Ohio, takes six to seven hours.
SD-WAN professional services connect all of its facilities, and all that is needed is to use short dedicated Internet connections to connect its facilities to local PoPs. From there, the company's network data is optimized, transported anywhere in the world, improving Makino's data synchronization work. It also paved the way for moving to edge computing solutions and improved the performance of voice and video communication between company branches.
