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As manufacturers implement IIoT ecosystems that connect their machines, equipment, and production systems to the digital enterprise, embedded systems technology will provide the intelligence “at the edge.” In today’s connected factories and plants, embedded systems provide the foundation for the next generation of smart connected IoT devices and the digital enterprise. These intelligent edge devices can aggregate and analyze sensor and other data and stream information to support predictive analytics platforms and the concept of the digital twin.
Embedded systems power intelligent edge devices and smart sensors provide actionable information to support asset monitoring, data analytics, process alarming, process control, machine learning, and the emerging AI ability for machines to make sense of and act on complex data patterns. Increasingly, the computational capabilities in on-site servers and cloud computing are migrating into the gateways and edge devices for IIoT networks.
It comes as no surprise that the first phase of IIoT will be the proliferation of intelligent edge devices. If industry is to move to ecosystems of smart connected machines and production systems, the first step is to create a digital environment that securely connects factories and plants using intelligent devices that can access, capture, aggregate, and analyze data at the production process and provide actionable information to enable operations, maintenance, and plant and product engineering and support groups to optimize how products are designed, manufactured, and supported. Embedded systems technology will be a prime enabler for this.
Embedded Systems in Automation Evolve to IIoT
Manufacturing automation is a market sector for embedded technology suppliers. However, until recently, it was somewhat limited. This is largely due to the traditionally proprietary nature of much current automation equipment, devices, and software. However, with today’s trend toward open automation systems, new embedded systems platforms and new programming standards are gradually replacing the proprietary environments of the past.
For manufacturing and other industrial applications, the automation systems are typically used to monitor, control, and optimize the production processes. Process data retrieved by control systems can be combined with other data sources (including both engineering and product design data) and analyzed to improve the process. These data then become part of the digital history. For these production systems, the current focus for IIoT is to access data to power predictive and prescriptive analytics and to help improve both product design and the associated manufacturing and support processes, rather than for actual, real-time process control.
Embedded Systems for IIoT Must Be Secure
As embedded systems enable intelligent edge devices for machines, equipment, and production systems, cybersecurity is a critical factor in software and hardware development. While the Internet affords a way to connect factory ecosystems, products and equipment in the field, and even manufacturing supply chains; this smart, connected world must be made secure and reliable or manufacturers will not adopt IIoT and the enabling edge technology.
A presentation at the 2017 Embedded Systems Conference (ESC) in Boston, by Michael Barr of Barr Associates discussed the results of a recent survey of embedded system software development engineers. Nineteen percent of embedded developers claimed they did not use any security standards to build the software, and 18.5 percent claimed they had security standards, but these were not followed due to the intense pressure to quickly create inexpensive devices for the consumer market. However, IIoT-embedded devices must be built with the appropriate standards for the application. The major caveat to this digital transformation to the intelligent edge is simply that it must be secure.
The primary function of IIoT is to create connected ecosystems in factories and plants that allow data to flow across the digital enterprise and to the cloud. As industrial companies make the transformation into digital enterprises, they will be able to adopt and implement a range of technologies like predictive/prescriptive analytics, the digital twin, and operational intelligence. The clear trend is to move connectivity and intelligence to the edge, where a new generation of smart sensors and intelligent devices will discover, access, aggregate, and analyze operational data. These smart edge devices will be powered by embedded systems software and advanced multi-processors computing at the source.
Embedded systems power intelligent edge devices and smart sensors provide actionable information to support asset monitoring, data analytics, process alarming, process control, machine learning, and the emerging AI ability for machines to make sense of and act on complex data patterns. Increasingly, the computational capabilities in on-site servers and cloud computing are migrating into the gateways and edge devices for IIoT networks.
It comes as no surprise that the first phase of IIoT will be the proliferation of intelligent edge devices. If industry is to move to ecosystems of smart connected machines and production systems, the first step is to create a digital environment that securely connects factories and plants using intelligent devices that can access, capture, aggregate, and analyze data at the production process and provide actionable information to enable operations, maintenance, and plant and product engineering and support groups to optimize how products are designed, manufactured, and supported. Embedded systems technology will be a prime enabler for this.
Embedded Systems in Automation Evolve to IIoT
Manufacturing automation is a market sector for embedded technology suppliers. However, until recently, it was somewhat limited. This is largely due to the traditionally proprietary nature of much current automation equipment, devices, and software. However, with today’s trend toward open automation systems, new embedded systems platforms and new programming standards are gradually replacing the proprietary environments of the past.
For manufacturing and other industrial applications, the automation systems are typically used to monitor, control, and optimize the production processes. Process data retrieved by control systems can be combined with other data sources (including both engineering and product design data) and analyzed to improve the process. These data then become part of the digital history. For these production systems, the current focus for IIoT is to access data to power predictive and prescriptive analytics and to help improve both product design and the associated manufacturing and support processes, rather than for actual, real-time process control.
Embedded Systems for IIoT Must Be Secure
As embedded systems enable intelligent edge devices for machines, equipment, and production systems, cybersecurity is a critical factor in software and hardware development. While the Internet affords a way to connect factory ecosystems, products and equipment in the field, and even manufacturing supply chains; this smart, connected world must be made secure and reliable or manufacturers will not adopt IIoT and the enabling edge technology.
A presentation at the 2017 Embedded Systems Conference (ESC) in Boston, by Michael Barr of Barr Associates discussed the results of a recent survey of embedded system software development engineers. Nineteen percent of embedded developers claimed they did not use any security standards to build the software, and 18.5 percent claimed they had security standards, but these were not followed due to the intense pressure to quickly create inexpensive devices for the consumer market. However, IIoT-embedded devices must be built with the appropriate standards for the application. The major caveat to this digital transformation to the intelligent edge is simply that it must be secure.
The primary function of IIoT is to create connected ecosystems in factories and plants that allow data to flow across the digital enterprise and to the cloud. As industrial companies make the transformation into digital enterprises, they will be able to adopt and implement a range of technologies like predictive/prescriptive analytics, the digital twin, and operational intelligence. The clear trend is to move connectivity and intelligence to the edge, where a new generation of smart sensors and intelligent devices will discover, access, aggregate, and analyze operational data. These smart edge devices will be powered by embedded systems software and advanced multi-processors computing at the source.