Beginners Guide to Selecting Embedded Computers in the Accelerated Wave of Automation

Manufacturers are racing to automate. Businesses are digitizing their operations and leveraging edge computing to increase productivity by building systems of machines that work accurately and consistently around the clock to improve quality and output. Evolving into an automated, Industry 4.0 factory also enhances safety, enabling equipment, not people, to perform dangerous tasks.

Furthermore, automation reduces the labor hours required to do a job, enabling manufacturers to control costs and weather labor shortages. Additionally, automation can cover monotonous and unchallenging work, resulting in greater job satisfaction among employees who can spend their time on higher-level tasks.

Businesses keeping pace with this fourth Industrial Revolution by creating systems of connected devices, including both information technology (IT) and operational technology (OT), are realizing that it’s not practical to process all data in the cloud. Internet of Things (IoT), big data analytics, artificial intelligence (AI)-powered, robotics, and other advanced systems often require minimal latency for subsecond responses. Therefore, solution builders are moving some computing workloads to the edge to provide automated systems with the effectiveness and reliability they need.

Edge Computing in the Automotive & Logistics Industries

Connected vehicles, electric vehicles, and autonomous vehicles are gaining popularity. These advanced technologies require sensor fusion, wireless connectivity, power management, security, and other advanced driver-assistance systems, making automotive production more complicated. As a result, manufacturing processes must evolve as well.

For illustrations of how embedded computers are enabling Industry 4.0 functionality today, look no further than vehicle manufacturing and fleet management. For example:

• Collaborative Robots in Manufacturing

Robots have a decades-long history of making automotive manufacturing more efficient. However, with advanced technologies supported by edge computing, manufactures, such as, automotive makers can leverage robots to build vehicles with more advanced designs that require more complex assemblies. Collaborative robots also give manufacturers more flexibility than industrial robots, allowing them to move capabilities where they’re needed without building costly new infrastructure.

• Fleet Management

Embedded computers give transportation and logistics enterprises the ability to track assets and provide advanced telematics that monitors driver behavior, idling and fuel use, vehicle performance, and indications that the vehicle requires maintenance. Autonomous mobile robots (AMRs) are another uprising applications in warehouse and logistics.

• Autonomous Vehicles

Edge computing is key to autonomous vehicle operation, providing the capacity to run power-hungry driving algorithms and process data quickly so that the vehicle can safely respond to unexpected situations. Additionally, embedded computers in autonomous vehicles can receive data from nearby vehicles to enable smooth traffic flow through an intersection and maintain safe distances between cars and trucks on a highway in inclement weather.

Embedded Computer Checklist

Whether your use case is in automotive manufacturing, transportation and logistics, or any of numerous other industries that benefit from edge computing, solution builders need to choose precisely the right hardware for their application. Start with these key considerations for selecting embedded computers:

• Power
  • First and foremost, the platform you choose must have the computing power required by your use case. Look for options with the latest Intel® Xeon®, Core™ and Atom® processors.
• Function Expansion
  • Evaluate options for the functionality they deliver, such as hardware-accelerated processing and precise motion control
• Heterogeneous computing solutions
  • Embedded computers can perform a wide range of tasks. Consider platforms that give you the ability to use embedded MXM GPU modules, PCI Express graphics cards or that integrate more than one computing cores like edge AI platforms, GPU computing platforms and other embedded systems.
• Quality Design
  • In addition to considering what the embedded computer will do, also take into account how well it will perform in the conditions in which it will be used:
    • Heat dissipation: Consider all options for cooling, including embedded computers with fanless design. Fanless embedded computers enhance durability.
    • High EMC standard: Electromagnetic compatibility (EMC) enables an embedded computer to perform in its electromagnetic environment and prevent negative effects, including electromagnetic interference (EMI).
    • Rugged and hardened: Embedded computers suited for a wide range of use cases are typically hardened, enabling them to perform in harsh environments where they could encounter shock, vibrations, temperature extremes, humidity, and dust.
• AI enablement
  • Optimizing AI at the edge includes using embedded computers with support for high performance, power-efficient GPU acceleration or a GPU platform that delivers the required AI engine availability.
• Wireless connectivity
  • The embedded platform you choose should support wireless connection with radio frequencies certified for different regions where your solution will be used and to provide steady and reliable connections.
• Ease of integration
  • Choose hardware that offers a comprehensive or configurable I/O set to simplify integration and interfacing with auxiliary devices.
• Support
  • Don’t overlook the importance of vendor support, including technical and longevity support to reduce costs with end-of-life (EOL) critical parts. Also, consider whether your use case can benefit from semi-customization or private labeling.