An interior view of a Switch Edge MOD 15 modular data center. (Image: Switch)
Carsten Baumann, Director of Strategic Initiatives and Solution Architect at Schneider Electric, explores therole of edgecomputing in handling todays big data explosion in themanufacturing sector.
The rise of Industry 4.0 is taking manufacturing plants to the next level, not only in how it is enabling manufacturers to automate and connect devices, but in how they apply data and analytics to make more informed, real-time decisions. Manufacturers are generating high fidelity Industrial Internet of Things (IIoT) data to create a more connected production ecosystem and generate the insights needed to increase efficiency and reliability.
The growth of IIoT data has been dramatic and our reliance on it is growing. In fact, McKinsey & Company estimates that companies will spend between $175 billion and $215 billion on IIoT hardware by 2025, including computing hardware, sensors, firmware and storage.
As the amount of IIoT data being produced increases, so too does the amount of data that needs to be processed and stored. This is driving many manufacturers to rethink traditional strategies involving regional enterprise, colocation or cloud data centers and shift to also include industrial edge computing.
When choosing between industrial edge computing, larger regional enterprise or colocation data centers and cloud data centers, what considerations should manufacturers keep in mind?
Businesses need to explore four main factors about the data in question: volume, variety, value and veracity. Once they do so, itll be easier to determine what IT solutions to invest in to best fit your IIoT applications.
Once businesses evaluate how the above characteristics affect their IIoT applications, theyll be able to determine where their data should be processed, stored and transported. Most modern industrial processes require real-time analysis, meaning it should be done locally in edge data centers rather than the analysis taking place in offsite cloud platforms.
While the hype around edge computing has been growing across industries for years now, theres no denying that the COVID-19 pandemic is acting as a forcing function to get industrial companies more interested in the benefits edge computing provides in supporting remote operations, real-time control and enhanced data-crunching capabilities.
While real-time processing and analytics are a must for most businesses these days, bandwidth, network capacity and cost are also large factors that are driving more industrial companies to the edge as they realize the benefits that enhanced real-time control offers enterprises in todays increasingly complex environment. Analytic results and additional process data may then be transported and stored elsewhere for record keeping, such as traceability and compliance.
As we rely more heavily on IIoT applications, industrial enterprises will require storage and processing solutions that support the agility and efficiency needed in todays increasingly complex and challenging business environment. Theyre turning to edge computing to do just that. In fact, a recent Frost & Sullivan report found that 90% of industrial enterprises will utilize edge computing by 2022. Thats a dramatic shift from a few years ago when the vast majority of enterprises didnt account for edge in their IT strategies.
While the hype around edge computing has been growing across industries for years now, theres no denying that the COVID-19 pandemic is acting as a forcing function to get industrial companies more interested in the benefits edge computing provides in supporting remote operations, real-time control and enhanced data-crunching capabilities. We predict that as we get deeper into the Industry 4.0 era, the industrial edge will only continue to accelerate.
Manufacturers are operating in two different domains the edge control layer, where data is analyzed and decisions are made in real-time, and the apps and analytics layer using Cloud, where data is gathered to create data lakes that can be mined to create further insights and comparisons.
To address the challenges brought on by Industry 4.0 and those that were accelerated because of the COVID-19 pandemic manufacturers should consider leaning more heavily into the industrial edge to improve real-time analysis, reduce latency and improve the amount of data being processed from across the enterprise. By combining the computing power of the apps and analytics layer with the speed of the edge layer, manufacturers can access high-quality insights in real-time to improve reliability, efficiency and, ultimately, operational profitability.
Carsten Baumann is Director of Strategic Initiatives and Solution Architect at Schneider Electric.
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