BrandPosts are written and edited by members of our sponsor community. BrandPosts create an opportunity for an individual sponsor to provide insight and commentary from their point-of-view directly to our audience. The editorial team does not participate in the writing or editing of BrandPosts.
By Todd M. Edmunds
The history of manufacturing is marked with major transformations brought by new technologies. The First Industrial Revolution captured the power of water and steam. The Second Revolution brought electric power to the factory, and the Third brought computerized automation. Today the Fourth Industrial Revolution is upon us, and in the words of Klaus Schwab, founder of the World Economic Forum, it is driven by “a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres.”
Today, the Fourth Industrial Revolution is ushering in the era of smart manufacturing, driven by new technologies for capturing and analyzing data and for gaining insights and efficiencies from that data via Edge Computing and artificial intelligence applications. Smart manufacturing, enabled by digital technologies and enterprise-grade infrastructure, is the key to reducing downtime, improving product quality, increasing factory output and exceeding business objectives today and in the future.
To compete effectively in this new era, manufacturers must adopt smart manufacturing processes and leading-edge infrastructures that enable it. Delaying this transformation is no longer a viable option. Companies that wish to remain competitive must embrace the full smart manufacturing journey now.
So how do you get there? This is a journey that begins on the factory floor, with Edge Computing.
Edge Computing is the acceleration ramp to smart manufacturing and Industrie 4.0. The Edge isn’t just one thing, however. In industrial and manufacturing environments, there are actually two Edges — an Industrial Edge and an Enterprise Edge.
Industrial Edge compute solves the problem of extracting data from legacy industrial assets like PLCs, DCS’s, robots and controllers as well as the challenges with interfacing with hundreds of protocols, vast numbers of connected sensors, disparate data sources and incompatible data formats that exist in the wild. This is the point at which industrial equipment and factory systems meet the digital world. Industrial Edge Compute provides the data context, repeatability, security and scale required for true transformation.
Standardized, ruggedized edge compute hardware (sometimes called gateways) can be quickly and repeatably deployed to the field or plant floor with an IT-approved, hardened operating system. Virtualized and containerized OT (operational technology)-focused applications can be deployed at this edge, transforming legacy protocols and sensor readings into analytics-quality data ready for any enterprise or business application in the data center or cloud.
The Enterprise Edge brings enterprise-grade infrastructure and modern IT concepts on-prem, to the plant floor or site. Systems at the Enterprise Edge need to manage and aggregate the hundreds or thousands of data streams coming from the Industrial Edge, and they can help bridge the gap between IT and OT organizations. The Enterprise Edge Compute resources can manage the Industrial Edge, deploying containerized and virtualized applications, delivering cloud-native principles at the Edge and can generate immediate valuable insights with real-time and streaming analytics.
Computing at the Enterprise Edge helps manufacturers significantly reduce their cloud computing costs, while providing low latency to enable immediate responses and real-time insights gained from running analytics on IoT data. It also solves critical regulatory and governance issues associated with data sovereignty and prohibitions against moving data across borders.
How do you get started with this transformation to smart manufacturing? The path to the future begins with a scalable, next-generation, modern infrastructure with software-defined networking, compute and storage. This type of hyperconverged infrastructure allows your organization to prevent the spread of the accidental architectures that pervade today’s manufacturing environments.
What’s an “accidental architecture?” The typical manufacturing plant might have 50 to 100 islands of automation, resulting from machines that were supplied with their own PLCs, systems and controllers that typically weren’t developed with external connectivity in mind. And when other supervisory, inventory, messaging and video systems are added to the plant later, it is not uncommon to have each system connected to its own network in order to keep the network traffic separated. With this fragmentation, the collective pool of data from the factory floor isn’t freely available in the enterprise. These accidental architectures can seriously impede the road to smart manufacturing.
The goal here is to implement a modern industrial architecture that supports smart manufacturing and allows the plant to grow and evolve without adding to the complexity and redundant hardware required by the legacy approaches.
Let’s look at some of the key building blocks of this modern architecture.
A modern architecture begins with Edge Computing, which is the gateway to smart manufacturing. Edge Computing puts data processing and analytics systems close to where the data is generated and captured. The idea is to bring context and analytics to the data, rather than sending all the data to an enterprise or cloud data center for analysis. Edge Computing allows intelligent systems to take immediate actions to optimize everything from machinery performance and equipment maintenance to supply chains, logistics and factory security.
Software-defined networking (SDN) adds a programmable layer on top of physical network devices to enable plant operators to control and modify new and existing network infrastructure via software. With software-based controls, the manufacturing environment becomes more agile. Changes to the network can be made quickly and efficiently to react to a dynamic business environment, and the network as a whole is always in a future-ready state.
Software-defined data center with hyperconverged infrastructure
A software-defined data center (SDDC) featuring hyperconverged infrastructures (HCI) makes digital transformation easier to implement, change and maintain while eliminating the complexity of accidental architectures. HCI combines server, storage, networking and software into pre-integrated packages that deliver proven benefits. It can help your organization improve operational efficiency, reduce costs and increase scalability. At the same time, HCI helps you prepare for rapidly emerging technologies, including 5G networks, AI, augmented and virtual reality (AR/VR), and even digital twins — the virtual representations of real-life physical assets used to optimize the operation and maintenance of the assets.
Modern storage architecture
In comparison to years past, manufacturers are creating exponentially more data — which is a good problem to have, because this data is a business asset. To gain the greatest value from this data, your organization needs a modern, scalable storage architecture that will consolidate and share data with every smart manufacturing application, including those for AI, computer vision and data analytics. At the same time, this storage architecture needs to incorporate capabilities for data protection and recovery, because lost data equates to lost business value.
Hybrid cloud architecture
With the proliferation of public cloud IoT solutions, no single vendor will have all of the best applications for your particular organization — interoperability is key. This means that a hybrid cloud architecture is a required foundational building block that allows your organization to seamlessly and transparently move data and workloads between on-prem, private and hosted cloud environments as computing needs and costs change.
For example, I worked with a global manufacturer of industrial robots to connect to all 1,000 of their assembly robots in an automobile plant to their cloud-hosted predictive maintenance application. This resulted in more than $30 million in savings for the manufacturer in just the first six months. When we approached another company to deploy the same solution, they demanded that NO data will leave the plant and go to any cloud. The right hybrid cloud infrastructure makes this a “click-simple” switch to implement an on-premises cloud solution.
True digital transformation is required to compete in the smart manufacturing future. Industrie 4.0 and smart factory manufacturing processes, guided by Edge Computing, hyperconverged infrastructures, and artificial intelligence are now essential capabilities for manufacturing success. To get there, manufacturers can’t simply add on to the accidental architectures of the past. Instead, they need to rethink their IT-OT environment, and transition to an enterprise-grade, next-generation infrastructure that capitalizes on Edge Computing, hybrid cloud capabilities, and modern, software-defined infrastructure concepts.