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The fourth industrial revolution, better known as Industry 4.0, is now happening – and the Industrial Internet of Things (IIoT) and edge computing are at the epicenter of this transition. IIOT adoption has been steadily increasing globally, accelerated in part by the pandemic; manufacturers realized the importance of digital transformation in the face of supply chain issues and staff shortages.
Leveraging machine learning (ML), AI, and big data, IIoT’s potential to power global manufacturing, support remote operations, and optimize production and analytics is well understood. In fact, the global IIoT market size was $263.52 billion in 2021 and is expected to achieve a compound annual growth rate (CAGR) of 23.1% between 2022 and 2030.
How are the two connected and why should companies act now or risk falling behind? Organizations of all types are beginning to understand the real value generated by IIOT: expanding capabilities and providing a critical competitive advantage.
From accelerated innovation and better efficiency to increased uptime and reduced operating costs, IIOT technology is revolutionizing industries such as manufacturing, aerospace, retail and healthcare. Implementing the right IoT technology can increase production, reduce waste and improve safety. It has been found to improve the growth rate of companies 25%.
The status quo
We are in the nascent stages of radical industrial transformation. Like any revolution, Industry 4.0 has winners and losers. Adoption of IIoT has become a necessity for manufacturers, but it has to be done right. Those without a clear IIoT strategy will be left behind.
Currently, increasingly powerful hardware coupled with recent advances in AI and ML capabilities have accelerated adoption and use cases. These are diverse and increase business value: from IoT sensors that monitor an asset’s condition (temperature and vibration) to alerting owners of potential problems to real-time data collection.
Edge computing underpins and enables IIOT applications and delivers use cases with tighter latency, bandwidth, and security requirements.
Challenges that stand in the way of progress
Today, the IIoT space remains quite fragmented and many challenges must be addressed to reach its full potential for Industry 4.0.
One of the biggest challenges for IIOT adoption is scalability. MIT Technology Review reports that 95% of companies are struggling to adopt IIoT solutions at scale and/or use them to gain a competitive advantage. The complexity of IIoT and the sheer scale of operations make operational simplicity a fundamental necessity if IIoT is to deliver reliable and resilient results.
The main challenges are deep technical and organizational issues. As McKinside notes that security comes first — as computers under management reach hundreds of thousands in geographically diverse locations, the threat landscape expands and new attack vectors emerge alongside the technical challenges of maintenance and patching.
The amount of data generated by IIoT devices makes them — and the architecture behind them — attractive targets for cybercriminals. Their use in critical infrastructure makes the consequences of a failure significant.
High initial investment costs and the complexity of managing IIoT devices are also barriers. Even with lightweight versions of Kubernetes facilitating deployment and scale, a lack of know-how and tight budgets are barriers to entry for many enterprises that would see the benefits of IIoT.
How edge computing addresses these challenges
Edge technologies are already solving these problems and making room for significant acceleration. Driven by cost savings in computing power, better bandwidth, and the ability to provide faster access to automation data, IIOT’s potential grows every day. Today, edge is the reliable and cost-effective way to ensure data quality, timeliness, accuracy and speed of delivery for many applications that would traditionally have been at heart.
Organizations tackling IIoT value propositions are gaining traction. Some companies have their customers as investors, indicating that IIoT is driving business value for industrial and manufacturing companies. It’s also becoming more mainstream and current, as evidenced by the recent Linux Foundation event ONE Summit, which focused on Industry 4.0 and edge.
Together, edge and IIoT can be seen as the connective tissue and gateway between the physical world and the computing world. The first step is to bring workloads into one management system; then the workload can be split as needed and placed in containers. This enables an organization to adopt key underlying platform technologies and development practices that form the foundation for functionality enhancements, cost-effective operations, and deployment at scale. This prepares them for AI workloads that are inevitable when closing the control loop that IIoT devices provide access to.
By laying the groundwork for edge computing, Industry 4.0 use cases have a clear runway for implementation and improvements. The edge computing foundation gives Industry 4.0 the ability to compute at the edge, ensure that workloads are containerized, applications are based on microservices, and that OS and Kubernetes are hardware independent and centrally managed. This can ensure that new devices are deployed with minimal on-site expertise as and when required.
The IIoT space is a major battleground for enterprises and industries pursuing digital transformation. The next 12 months will be critical for those looking to optimize their operations, improve their supply chain and gain a competitive advantage. Companies must seize the opportunity presented by the latest edge developments and renew the transition to Industry 4.0 or else they will be left behind.
Keith Basil is an edge GM at SUSE.
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