Edge-computing adoption continues to grow significantly. In research we conducted with Espalier, we found that edge-computing adoption will increase by more than 45% through 2026.
Driving the demand is the need from manufacturing organizations for simple, autonomous edge-computing solutions as a component of software and hardware architectures that simplify workflows, ensure uptime and provide key insights and visibility into daily processes at the location where products are being made and customers are being served, according to survey respondents. As organizations digitally transform, these results are increasingly important to manufacturers, particularly as they face supply-chain issues, inflation and an economic downturn.
Edge-computing use cases driving adoption include monitoring and control with human-machine interface (HMI) supervisory control and data acquisition (SCADA); supply-chain visibility and automated material handling (AMH); manufacturing execution and batch management; asset performance management (APM); and access control and building management.
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Monitoring and control with HMI SCADA: Edge-computing platforms deliver the performance and fault tolerance required to run and scale HMI SCADA and historian applications reliably for critical equipment and processes. With compute capability at the edge, operators can eliminate the need for learning and managing multiple interfaces. Instead, they can view data through standardized HMI screens, which speeds up data acquisition and enables real-time processing and data storage for visibility and analysis, resulting in faster decision-making.
Supply-chain visibility and AMH: Among other applications, supply-chain visibility is critical for manufacturing execution, inventory management and point of sale. Edge computing brings together the right combination of computing power, performance and reliability to support warehouse automation and automated material handling, including tracking and tracing assets to avoid data blind spots in the supply chain and the elimination of system downtime to avoid revenue loss.
Manufacturing execution and batch management: Manufacturers run manufacturing execution systems (MES), batch and quality applications close to production lines and critical equipment for real-time data acquisition and control, supporting operational resiliency and driving manufacturing excellence while connecting the shop floor to the top floor. A good MES ensures that manufacturing operations run effectively and improves production output.
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APM: Edge data from critical equipment and processes provides a foundation for APM solutions. Edge computing enables the capture, organization and processing of data sets locally and then delivers data to the cloud for deeper analysis, while also providing remote operation and mobile access to data and performance.
Access control and building management: Edge computing enables building management to consolidate systems, including security, access control and utilities onto a single platform.
Where is edge computing being implemented most?
With those use cases driving adoption, we also did some analysis on where the adoption is happening. We found that the industries rapidly implementing edge computing for the primary use cases were oil and gas; digital manufacturing for discrete and complex discrete industries; life sciences and pharmaceutical manufacturing; and smart infrastructure and renewables.
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Oil and gas: Edge computing meets key operations goals for remote operation, efficiency and safety upstream and midstream with the ability to develop smart, connected oilfield equipment and enable terminal automation and pipeline assets. Loginet, an Italian petroleum company, is using edge computing to deliver a comprehensive terminal automation solution that automates depot operations, connects transaction data to ERP systems, manages shipping requests and tracks customs information, all running on a single compute platform backed by fault tolerance.
Digital manufacturing for discrete and complex discrete industries: Broadly, edge computing is a foundational technology for Industry 4.0 manufacturing initiatives in a range of manufacturing areas such as electronics, semiconductor, automotive and consumer goods. Russian River Brewing, which brews Pliny the Elder, seven-time winner of the national best beer competition, uses edge computing for continuous operation.
Life sciences and pharmaceutical manufacturing: Production execution, reliability, quality and compliance are critical processes powered by edge computing to eliminate data loss and unplanned downtime for life sciences. One of Canada’s largest acute-care hospitals, Humber River Hospital, leverages edge-computing to keep a video-surveillance solution running continuously without failure.
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Smart infrastructure and renewables: Edge-computing deployment is ideally suited for monitoring and control and access control toward development of smart transportation systems, renewable power generation, building automation, and water and wastewater for smart cities. Dynamic Controls, a system integrator that specializes in building automation and security systems integration, decided edge computing was the way forward for ensuring uptime in its data center.
Areas of growth for OT
As they evaluate use cases and how they fit with the needs of their businesses, operational-technology (OT) professionals need to reach across the aisle and work with their counterparts in information technology (IT) to deliver on the promises of Industry 4.0 and the technologies driving it, such as Internet of Things (IoT) devices and platforms, artificial intelligence (AI) and analytics, cybersecurity and augmented reality (AR)/virtual reality (VR).
The research identified three areas of growth—OT workloads, edge OT workloads and edge IT workloads—for OT professionals as they partner with IT.
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OT workloads: Software-running machine and equipment processes at edge locations in industrial environments governed by OT teams with a focus on PLCs and safe operations are projected to grow more than 45%. This includes software for real-time data monitoring and network security, both of which can be run at the edge.
Edge OT workloads: Applications for monitoring and control of machines and equipment focused on analytics, maintenance and AR are projected to grow more than 10%. These applications are not only increasing automation opportunities for edge adopters, but enabling those companies to better control it, freeing up workers to focus on other responsibilities.
Edge IT workloads: Software running site-wide industrial applications such as distributed control systems (DCS), batch management, analytics and asset performance with significant oversight by IT are forecasted to grow by nearly 30%.
