Industrial

Programmable Logic Controller (PLC) is an industrial computer used for controlling the automation of industrial processes. PLC is a computer-based solid-state device that is designed to withstand harsh factory conditions and carry out real-time monitoring and control of different industrial processes.

PLCs are used extensively in almost all industrial processes, but current systems are typically optimized for a specific domain as a closed system. As Industry 4.0 drives further automation across multiple domains over the network, PLCs are getting integrated into larger computing platforms (like edge computers) as a software function to enable workload consolidation.

FPGAs are commonly used for I/O expansion, industrial Ethernet, and field bus communication devices to enable deterministic, low-latency parallel computing of PLC. Also, FPGA is used for functional safety as some PLCs are used for safety-critical applications. Intel and its partners offer a variety of IP cores as well as safety certified SKUs and Functional Safety Data Package.

Machine vision technology is rapidly evolving to achieve higher image resolution, higher frame rates, the adoption of new interfaces, and the adoption of AI.

Cameras and other equipment used in machine vision perform a variety of different tasks, such as Image Signal Processing (ISP), format conversion, analytics and video transport. [CJ1] Because of the frequent technological improvements to camera sensors, the advancement of artificial learning and deep learning-based video analytics, Altera FPGAs play a key role in industrial cameras[CJ2] , frame grabbers, and vision controllers:

• Flexibility to interface with many types of image sensors and Machine Vision system devices.
• Fast processing to incorporate a full image sensor pipeline (ISP) that includes techniques such as defect pixel correction, gamma correction, dynamic range correction, and noise reduction.
• Support for AI deep learning frameworks, models, and topologies to implement FPGA-based convolutional neural network (CNN) inferencing accelerators.

Motors and drives power countless industrial processes in production, assembly, packaging, robotics, computer numerical control (CNC), machine tools, pumps, and industrial fans. These motor-driven systems account for more than two-thirds of industrial energy consumption, making their efficient operations vital to factory profits.

Designing motor control and motion control systems with Altera FPGAs and SoC FPGAs can result in a significant reduction in the overall cost of ownership through:

• System Integration: Lower Bill of Materials (BOM), power consumption, and reliability challenges by integrating industrial networking, functional safety, encoder, and power stage interfaces, and digital signal processing (DSP) control algorithms in a single device.
• Scalable Performance: Use a single scalable platform across entire product lines. Achieve higher performance with faster and more advanced deterministic control loops.
• Functional Safety: Reduce compliance time and effort with devices and tools that meet Machinery Directive IEC61508 safety standards.

Robots are becoming more and more prevalent in the industrial workplace. Super high-speed industrial robots handle difficult and hazardous tasks like assemblies, welds, and pick-and-place. Collaborative robots, or cobots, work hand-in-hand with humans, requiring a functionally safe environment. Autonomous Mobile Robots (AMRs), many vision–guided, function individually and in cloud-control swarms.

Altera FPGAs provide the needs for industrial robots through:

• Deterministic computing: Brings precision and multi-axis motor control benefits to robotics, significantly lowering the cost of bill-of-materials and reducing latency to improve accuracy.
• Connectivity: Time-sensitive networking (TSN) coordinates the multiple axes of a single robot and between multiple robots.

• Functional Safety: The Functional Safety Data Package (FSDP) and TÜV Rheinland-certified CAT3 PLD Safety Concept provide FuSa functionality and accelerate time-to-market by compressing certification cycles for customers.

  Together with Altera® FPGA Video and Vision Processing IP Suite, OpenVino™ toolkit, and the FPGA AI Suite, you can deploy vision functionality beyond color and shape inspection, such as safety hazard detection and object recognition/classification.

The use of FPGAs in smart energy applications brings benefits such as improved performance, flexibility, real-time processing, energy efficiency, integration capabilities, scalability, and enhanced security. These advantages contribute to the development of efficient, reliable, and intelligent energy systems that can support sustainable and optimized energy generation, distribution, and consumption

Technology Trend:

• EVs are forecasted to be more than 2B in 2023.
• EV charging L3 DCFC stations are forecasted to be 942M+ by 2025.
• As regulations evolve, power conversion, battery management, cost savings, user experience, edge analytics, safety, and security are key market drivers in EV charging stations.