Sectors that rely heavily on operational technology (OT), such as manufacturing, transportation, energy, and mining, are embracing digital transformation as a way to streamline their operations — an evolution commonly referred to as “Industry 4.0.”
And it’s easy to see why: The potential benefits range from automated logistics and predictive maintenance in manufacturing, to improved fuel efficiency and better inventory tracking in transportation, to smart energy grids. And in the public sector, this evolution is driving the move to smart cities. With the help of data and analytics, industries are becoming safer, more efficient, and more productive.
But companies operating in these OT-focused industries face challenges around digital transformation that other types of organizations may not. Namely, physical assets lie at the heart of their operations, while fields such as finance and retail rely more heavily on their digital systems. Consequently, digitizing operations in these sectors is often a slow and complicated process. Organizations working in these vertical industries typically manage a wide range of physical operational technologies – ranging from manufacturing equipment to tractor trailer trucks — that may be older, difficult to integrate, and siloed from traditional IT systems and oversight.
Connecting mission-critical OT with traditional IT can be complex, time-consuming, and even potentially disruptive. As a result, some industrial organizations have been slow to embrace industrial automation. According to 451 Research, only 34% of industrial companies have a formal digital transformation strategy to actively digitize business processes and assets — 10 percentage points less than non-industrial organizations.
To fully reap the benefits of Industry 4.0, industrial-focused organizations must link OT with IT, embrace emerging technologies, and build out networks that can securely support and bridge both types of technologies. This blog – and the forthcoming blogs in this series – will explore the reasons, the challenges, and the potential solutions.
The Building Blocks of Industry 4.0
To glean insights that lead to business benefits, industries must gather data from their physical assets and connect often silo’d systems. This requires investment in a number of emerging technologies, as well as a strong, intelligent IT network.
The following technologies are powering industrial automation:
- Industrial Internet of Things – IIoT systems incorporate people, machinery, computing hardware, software, and the physical environment around them. By connecting physical assets with the IT network, IIoT lets companies collect, analyze, and integrate data that can lead to real-time business insights, improved efficiencies, greater productivity, and more.
- Cloud Infrastructure – The agility and elasticity of cloud computing enables organizations to quickly scale out resources for storing and processing the new, large volumes of data generated from IIoT investments.
- Edge Computing and Fog Computing – As IIoT and IoT sensors are deployed in far-flung physical locations, the edge (made up of locales near industrial machines and devices) is often a better location for processing industrial workloads. Today, IoT gateways often come equipped not only with storage and compute, but also with analytics and application execution capabilities. When data is stored and processed at the edge, organizations can reduce the bandwidth needed to power industrial automation, improve the speed of critical applications, and increase efficiency.
- AI and Machine Learning – The sheer volume and complexity of new data that accompanies Industry 4.0 initiatives can be overwhelming. But machine intelligence can help organizations gain insights that lead to tangible business value by processing enormous volumes of data quickly and efficiently. Both AI and ML can also automate actions based on specific data so employees can focus on more complex decisions or processes. Organizations often use their historical IIoT data to “train” ML and AI models.
- Digital Twins and AR/VR – Digital representations of physical assets often serve as an interface for IIoT systems. A digital twin is a digital representation of the “state” of a physical device or system, and it feeds data and insights both in and out of physical assets. When the digital twin is adapted, the physical machine itself can also be tuned accordingly, giving organizations the ability to optimize industrial processes.
- Augmented reality (the overlaying of digital images onto the physical world via headset, glasses, smartphone, or other device) and virtual reality (navigable, 3D virtual instances of the physical world) have both emerged as critical user interfaces. These technologies allow workers to gain information about and manipulate the IIoT world, leading to more efficient maintenance and operations of physical systems.
Network Strength: The Missing Piece
Given the increasingly important role that data plays in industrial automation, it is clear why the network is so important. However, what’s often missing in today’s digital transformation is a high-performance, dynamic, and intelligent network infrastructure, which can act as the “connective tissue” that brings the various components of Industry 4.0. This network goes beyond W-Fi, Ethernet, and narrowband cellular links to provide business-critical connectivity and completely link IT and OT.
Even many organizations that have already invested in IIoT sensors and cloud platforms have overlooked or under-deployed the networking aspects of industrial automation. To ensure that no site, employee, or system is left behind, organizations in industrial-focused fields will need to leverage technologies including 5G, private LTE, mobile edge computing, and network function virtualization and software-defined networking.
To interconnect a company’s OT and IT in ways that drive productivity gains, an IIoT network must be:
- Accessible — Various wireless, fixed, IP, optical, and microwave technologies must work together to extend to every part of the business.
- Elastic — As workloads are added and demand fluctuates, a network should automatically adjust to optimize resource utilization.
- High-performance — The network should deliver seamless performance that meets stringent guidelines for each set of applications.
- Resilient — Networks must ensure availability at all times, particularly in fields where human lives and safety are at stake.
- Secure — A network with more connections has more potential vulnerabilities. A smart network fabric should minimize threats, rather than exacerbate them.
- Scalable — Networks must be designed with expansion of bandwidth, processing, and other capabilities in mind.
The Bottom Line
In many cases, the new demands on networking infrastructure that result from industrial automation will outstrip what even the largest enterprise networks have historically seen. This change will require companies to interconnect all of their assets, sites, applications, and industrial systems without compromising availability, performance, or security.
It’s no small task, but organizations that invest in networking now will position themselves to use data to improve operations and create new value for years to come and turn their Industry 4.0 visions into reality.