Industrial automation is entering its most transformative phase since the introduction of PLCs and SCADA in the 1970s. Driven by advancements in connectivity, artificial intelligence, and digital engineering, automation is evolving from programmed control to predictive, adaptive, and autonomous systems. Over the next five years (2025–2030), six core technology trends will reshape the operations, scale, and adaptability of factories, warehouses, utilities, and processing plants. This article explores these trends and their implications for OEMs, system integrators, and industrial product developers, with a focus on the role of ARM-based industrial PCs in enabling these advancements.
What’s Happening: Artificial Intelligence (AI) has shifted from cloud-based systems to edge devices, enabling real-time processing of sensor data on embedded platforms like ARM-based industrial PCs.
Key Benefits:
Reduced latency for time-critical decisions.
Predictive maintenance using behavioral models.
Enhanced resilience by minimizing reliance on cloud infrastructure.
Real-World Applications:
Anomaly detection in rotating equipment using vibration sensors and machine learning (ML) models.
Predictive quality control on production lines with computer vision.
Adaptive process optimization in chemical and food manufacturing.
Technology Enablers:
ARM-based industrial PCs (e.g., those powered by NXP i.MX 9, Rockchip RK3588J, or NVIDIA Jetson) provide energy-efficient, high-performance platforms for edge AI.
Frameworks like Edge Impulse and TensorFlow Lite for microcontrollers.
Integration of Real-Time Operating Systems (RTOS) with model inference pipelines.
Outlook (2025–2030): Factory equipment will increasingly become AI-native, leveraging ARM industrial PCs for on-device model retr --
ARMxy BL450 series Rockchip RK3588J supports 6Tops NPU to promote the development of Edge AI
System: aining via federated learning or MLOps practices, enabling continuous improvement and adaptation at the edge.
The Challenge: Traditional systems rely on proprietary fieldbuses, vendor-specific integrations, and siloed architectures, limiting scalability.
Trend: Open, vendor-neutral communication protocols are gaining traction:
OPC UA over TSN for deterministic communication.
MQTT + Sparkplug B for lightweight messaging.
EtherCAT + Ethernet-APL for real-time, deterministic Ethernet.
Benefits:
Plug-and-play device integration.
Cross-vendor communication in brownfield and greenfield environments.
Simplified migration to Industry 4.0 and digital twin ecosystems.
Key Development: Adoption of IEC 61499 for event-driven automation logic, interoperating with cloud APIs for remote control and monitoring.
Role of ARM Industrial PCs: ARM-based industrial PCs, with their support for modern networking stacks and low-power, high-throughput processing, serve as gateways or controllers to bridge legacy and modern protocols, enabling seamless interoperability.
BLIoTLink supports multiple industrial protocols, such as Modbus, MQTT, OPC UA, etc., and can be adapted to ARMxy series industrial computers and other ARM architecture hardware devices for data acquisition and protocol conversion.
Concept: Digital twins are real-time virtual representations of physical systems, used for simulation, monitoring, and optimization.
Why It’s Growing:
Enables remote debugging and system tuning.
Supports predictive diagnostics and process optimization.
Simplifies training, testing, and certification.
Enabling Technologies:
3D CAD and simulation tools (e.g., ANSYS Twin Builder, Siemens NX).
IoT platforms for real-time data synchronization.
Open standards like Functional Mock-up Interface (FMI).
Trends to Watch:
Integration of PLC code and physics-based models in unified runtimes.
Digital twin ecosystems across OEMs, integrators, and end-users.
Coupling digital twins with AI models for next-generation control systems.
Role of ARM Industrial PCs: ARM-based industrial PCs provide the computational power and connectivity needed to host digital twin runtimes locally, ensuring low-latency synchronization with physical systems.
Challenges: Ensuring data quality, sensor integration, real-time synchronization, and model maintenance as systems evolve.
Shift: Unlike traditional caged industrial robots, collaborative robots (cobots) and Autonomous Mobile Robots (AMRs) operate in shared spaces with human workers.
Key Advancements:
Safety path planning using 3D sensors and AI.
Flexible reprogramming for dynamic tasks.
Real-time integration with Manufacturing Execution Systems (MES) and Warehouse Management Systems (WMS).
Applications:
Bin picking and assembly on hybrid production lines.
Autonomous material transport in smart warehouses.
Inspection and maintenance in hazardous areas.
Technology Drivers:
ROS 2 and MoveIt for motion planning and control.
EtherCAT-based motion control systems.
AI-enhanced vision and grasping libraries.
Role of ARMxy Industrial PCs: ARM-based industrial PCs power the control and AI processing for cobots and AMRs, offering compact, energy-efficient platforms for real-time decision-making and sensor integration.
Outlook: Cobots will evolve to learn and adapt through reinforcement learning and shared datasets, with ARM industrial PCs enabling scalable, on-device intelligence.
Why It Matters: The growing connectivity of industrial systems increases vulnerability to cyberattacks, as seen in incidents targeting water utilities, pipelines, and factories.
Key Regulatory Frameworks:
IEC 62443 (Industrial Cybersecurity).
NIST 800-82.
ISO/SAE 21434 (for automotive applications).
EU Cyber Resilience Act (effective 2025+).
Emerging Strategies:
Security-by-design at the chip and firmware levels.
Zero-trust architectures with identity-based access.
Secure boot, over-the-air (OTA) updates, and encrypted logging.
Role of ARM Industrial PCs: ARM-based industrial PCs, with built-in security features like TrustZone and secure boot, provide robust platforms for implementing cybersecurity measures at the edge, ensuring compliance and protection.
Outlook: Cybersecurity will become an embedded product feature, integrated into PLCs, drives, HMIs, and sensor nodes, with ARM industrial PCs serving as secure hubs.
Trend: As edge devices like ARM-based industrial PCs become smarter, seamless, secure, and real-time data flow between edge and cloud is critical, representing the convergence of Operational Technology (OT) and Information Technology (IT).
Key Developments:
Data preprocessing at the edge to reduce cloud payloads and costs.
Cloud-native microservices for SCADA/PLC integration.
Real-time feedback loops between factory sensors and cloud-based AI engines.
Use Cases:
Cloud-to-edge synchronization for production planning and quality control.
Dynamic model deployment from cloud AI platforms to edge accelerators.
Visualization dashboards powered by Azure IoT, AWS Greengrass, or private Kubernetes clusters.
Benefits:
Agile production systems.
Unified data lakes for analytics.
Reduced latency for mission-critical control.
Role of ARM Industrial PCs: ARM-based industrial PCs act as edge gateways, performing preprocessing, local analytics, and secure communication with cloud platforms, enabling efficient closed-loop systems.
Adoption Challenges: Managing latency, ensuring cybersecurity, and addressing data model fragmentation.
The next five years will redefine industrial automation by integrating real-time control with AI, connectivity with cybersecurity, and physical systems with digital twins. ARM-based industrial PCs will play a pivotal role as versatile, power-efficient platforms that enable edge computing, interoperability, and secure, scalable automation.
OEMs, system designers, and technology providers that embrace these trends early will build more adaptive, scalable, and future-ready platforms. Let’s shape the future of automation together.
