Overview
The Manufacturing AI Suite enables industrial and manufacturing customers to optimize AI workloads and ensure seamless deployment onto the factory floor. This collection of pre-built, AI reference applications and pipelines accelerates time to value to extend AI-driven automation for existing deployments with power efficiencies to scale performance at the edge.
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Beyond Automation: How Intelligent Robots Will Change the Factory
IWatch Ricky Watts recent A3 Webinar to learn about intelligent systems that can perceive, decide, and act dynamically and how these systems drive measurable value for manufacturers.
Watch the WebinarTAIROS Highlights
Watch Intel’s Ricky Watts keynote at TAIROS – a masterclass in purpose-driven industrial leadership — blending education, inspiration, and strategic vision for AI transformation in manufacturing.
Watch the keynoteTechnology & Performance
Leverage Intel’s long-standing industrial robotics expertise, advanced compute to power real-time controls and AI acceleration on a single processor, and an open ecosystem to adapt next-generation robotics and scale physical AI-based robotics faster.
Advanced Compute
Intel delivers integrated, optimized hardware performance across a range of silicon form factors and systems to power AI acceleration with low-latency and scalability at the edge.
Intel® Core™ Ultra Processors
Power both real-time performance and AI acceleration on Intel® Core™ Ultra Series 2 and Series 3 processors to deliver efficiency and cost savings.
GPUs for AI Acceleration
Stream media analytics and deep learning pipelines at the edge with powerful GPU to accelerate advanced physical AI and fast model inference at the edge.
AI Systems Extend x86 Performance
Extend AI for robot systems with pre-built AI systems designed with best known hardware configurations and flexible form factors for delivering physical AI at the edge.
Build with an open ecosystem
Intel integrates across a broad ecosystem of hardware partners to enable freedom of choice and flexibility for building robots with best-known hardware configurations for cameras, sensors, and hardware connectivity to enable rugged, long-lasting performance.
Camera and Sensor Integration
With support for high-speed image data transfer technologies like MIPI CSI-2, robot builders have high bandwidth to capture high-resolution video and images with integrations for RealSense® cameras.
Controllers and actuators
Intel’s robotics platform supports many types of actuators including motors and servo-drives to control heavy duty and light weight robotic arms, wheeled platforms, and end effectors for gripping, picking, and placing.
Fast Connectivity
Leveraging industry-standard industrial automation protocols for high speed and low latency, like EtherCAT and CANopen, Intel’s hardware configuration supports high precision, high-speed connectivity and device interoperability for cost-effective device integration.
Automation and Real-time Control Recipes
Extending real time performance with repeatable efficiencies for predictable, scalable, and adaptable performance and real time control across rugged industrial deployments at the edge.
Intel Time Sensitive Networking
Optimized network and ethernet contols streamline robot operations for efficiency and low latency.
Intel Time Coordinated Computing (TCC)
A processor technology that prioritizes workloads to optimize performance for time-sensitive, real-time applications to reduce jitter, improve determinism, and synchronize tasks with microsecond-accuracy.
Virtualization and Application Management
Right-size robotics solutions to ensure scalability, compatibility, and performance tuned for physical AI workloads, and suitable to scale industrial robotics operations.
Real-time controls, manageability and deployment
Enable containerized and virtualized applications in edge deployments to process AI pipelines with speed and efficiency on CPU, NPU, and iGPU.
Intel® ACRN
A lightweight hypervisor used in autonomous mobile robots (AMRs) to consolidate multiple operating systems and workloads onto a single computing platform. It uses virtualization to securely and reliably run a mix of critical real-time tasks (like navigation) and general-purpose workloads (like AI) on the same hardware.
Kernel-based Virtual Machine
Intel brings special features for Kernel-based Virtual Machine to consolidate compute-intensive tasks to ensure real-time performance and robust remote management for edge devices and reduce latency.
Evaluation, qualification, and benchmarking
Deploy and scale robotics applications with near zero-touch deployment and enable remote management to quickly evaluate AI workloads using performance monitoring, repeatable benchmarks, and optimization tools to ensure efficiency and optimized performance.
Visual Pipeline and Performance Evaluation Tool (ViPPET)
Evaluate hardware for AI workloads to benchmark CPU frequency, GPU power usage, memory use, and temperature with hardware-aware tuning to fine-tune performance.
Use Cases
Accelerate time-to-market through simplified design and faster deployment with reduced system cost and footprint via workload consolidation. Measure ROI gains from optimized performance and energy efficiency.
The manufacturing AI Suite provides a comprehensive toolkit to build, deploy, and scale AI applications for industrial environments including tools and software for AI acceleration, such as IoT protocol support (MQTT/OPC UA), accelerated libraries for data analytics, and system software for multi-interface cameras and sensors.
Vision AI
Enables machines to interpret and understand information from images, videos, and other visual data through image recognition, object detection, and scene understanding...
LLM inference and Agentic AI
Leveraging advanced LLM models and retrieval-augmented generation, GenAI enhances decision-making, streamlines troubleshooting, and delivers real-time, actionable insights for continuous improvement, reduced downtime, and safer manufacturing operations.
Multimodal media analytics pipelines
Simultaneously analyze camera feeds and sensor data for abnormal patterns. Fusion analytics combines insights from sensors and cameras to enhance detection accuracy, reduces false positives, and enable early identification of potential issues.
Sensor data and Time Series Analysis
Using data simulators, time series AI and Model Registry microservice, manufacturers can ingest, store, process, and visualize data at the edge using IoT protocol support (MQTT/OPC UA).
Pre-configured, modular media and AI pipelines, IoT frameworks and LLM applications enable system integrators and solution builders with to test performance of AI workloads to build, deploy, and scale AI applications for industrial environments.
HMI Augmented Worker
A RAG enabled HMI application deployed on Type-2 hypervisors delivers a user-friendly interface for troubleshooting advice, data summarization, and planning, utilizing a knowledge base tailored to specific deployments, including telemetry data, support logs, machine manuals, and production plans to improve operational efficiency, decision-making, and overall productivity.
Wind Turbine Anomaly Detection
Time Series predictive maintenance use case to detect the anomalous power generation patterns relative to wind speed for the wind turbines. Detect anomalous trends indicative of wear or failure, and alert operators to schedule maintenance proactively. This enhances productivity, reduces costs, and extends equipment lifespan.
Pallet Defect Detection
A use case that connects multiple video streams to AI pipelines to detect defects using foundational vision AI for object and anomaly detection with open telemetry and DL Streamer, an interoperable containerized microservice to accelerate video and deep learning inferencing.
PCB Anomaly Detection
Detects anomalies in printed circuit boards running inference workflows across multiple AI models using multi-camera inputs.
Weld Porosity Detection
Uses AI and machine vision to detect welding defects in real time with precision and reliability.
Worker Safety Gear Detection
Enable real-time safety gear monitoring of workers with inference workflows and multiple camera media analytics pipelines for safety and compliance.
Benefits
Efficient, powerful, affordable compute, to accelerate high-value manufacturing use cases and build future-ready AI
AI and Real-time control on one platform
Run AI inference and deterministic control together, reducing complexity, cost, and integration time compared to multi-CPU/GPU setups. Power-efficient performance at every tier – right-sized Intel® SoCs optimized for industrial edge environments.
Open Ecosystem
Open architecture and interoperability enable connectivity between legacy and new systems to extend longevity and value of industrial x86 deployments with a wide range of form factors and open-source solutions from partners for scalable integration and co-innovation.
Software Defined Digital Transformation
From low-power robots to high-end autonomous systems, with dynamic workload orchestration, remote updates, and hardware abstraction for faster deployment.
Insights And Resources
Research Intel’s expertise and perspectives on extending AI to the factory floor and building efficiencies at scale to increase yield, assure quality, and accelerate throughput.
Read about the AI libraries and reference applications in the Manufacturing AI Suite.
Quality assurance and defect detection with Anomalib
Ensure that every product meets quality assurance standards with Anomalib, an open-source AI library in the Open Edge Platform used for visual anomaly detection.
What is Machine Learning?
Computer vision and machine learning are pillars of modern manufacturing and industrial automation. Gain a foundational understanding on ML and the core use cases it brings to manufacturing.
Artificial Intelligence in Manufacturing
Production facilities already use technologies to help automate routine tasks. Learn how AI/ML pair to enable advanced manufacturing use cases at the edge for automating processes and enabling intelligent and efficient operations.
Intel and Elementary Partner to Deliver Self-Learning Quality Inspection for Manufacturing
Manufacturing struggles with operational burden with many initiatives requiring weeks of setup and costly downtime. Learn how OpenVINO, Elementary Vision Stream, and Canonical’s Ubuntu Core solve these challenges with purpose-built edge AI for manufacturing.
Watch videos on how intelligent systems, automation, and AI are addressing tough manufacturing challenges and extending value with scalable efficiencies.
Real-world Manufacturing Applications for AI and Autonomous Machine Learning
Discover the transformative power of AI in manufacturing using visual AI for defect detection and autonomous machine learning to enhance product yields and quality. Gain insights into real-world applications of AI technology and machine learning.
Intel AI: Powering the Future of Innovation in Manufacturing
The integration of AI at the edge is heralding a new era of innovation and efficiency. Learn about how AI at the edge is shaping the future of manufacturing and how Intel’s products and technologies are driving this transformation.
How Precision Manufacturing Gets Done
Audi and Intel partner to produce precision engineering with automation to perform quality control on spot welds.
See how partners and customers are addressing tough manufacturing challenges with Edge AI based solutions.
Solution Brief: Software Defined Industrial Automation System
Intel, Schneider Electric, RedHat and Hewlett Packard Enterprise introduced a Software Defined Industrial Automation System to modernize legacy controls.
Case Study: BMW Group: AI on Every Employee’s Laptop
Using machine vision to detect defects in production and quality control, BMW applies deep learning to efficiently process and analyze visual data using OpenVINO, Intel’s AI inference engine and part of the Open Edge Platform.
Evaluate real-world manufacturing reference applications and pipelines with everything you need to get started.
Human Machine Interface (HMI) Application
Connect users with machines and run AI inference using Retrieval Augmented Generation(RAG) pipelines and Chat QandA Core to train AI with sensor data.
Pallet Defect Detection
Enable real-time pallet condition monitoring by running inference workflows across multiple AI models, connecting multiple video streams from cameras via AI-powered pipelines.
PCB Anomaly Detection
Automated quality control with AI-driven vision systems that use real-time anomaly detection in printed circuit boards by running inference workflows across multiple AI models. Using streaming media analytics from multiple cameras and sensors.
Weld Porosity Detection
AI machine vision detects welding defects, ensuring immediate corrective action before issues escalate. Leveraging cameras and computing hardware, a trained AI model monitors the weld - halting the process when defects are detected with deep learning AI processing video data at frame rates beyond human capability.
Worker Safety Gear Detection
Run inference workflows across multiple AI models by connecting multiple video streams from construction site cameras to AI-powered pipelines for construction site safety and compliance monitoring.
Wind Turbine Anomaly Detection
Time series predictive maintenance detects anomalous power generation patterns relative to wind speed to prevent equipment failures. Gathers inputs over time to compare deviations to optimize maintenance schedules.
Developer Tools
Accelerate development with tools and tutorials to enable robot solutions with advanced Vision AI, spatial intelligence, and optimizations and transformers for AI model inference.
Build and optimize embodied intelligence models and workflows with tools to optimize performance on Intel.
Intel® OpenVINO Training Extensions
Libraries to accelerate PyTorch, ML, and LLM models for optimized performance and fine-tuning on Intel® hardware
Geti™ Computer Vision Models
Simplify and accelerate computer vision model training with an intuitive end-to-end seamless workflow. Optimize models for speed and fine grained precision to detect objects and key points for pose estimation.
Intel® oneAPI
A unified programming model that enables developers to write code that can be executed on a variety of hardware accelerators.
SceneScape
Create dynamic 4D digital twins of real-world environments using data from various sensors to inform situational awareness and robotic perception.
Get advice for arranging heterogeneous computing, and models used for embodied intelligence with helpful tutorials
Heterogeneous Computing
Learn about the various software workloads integrated to enable autonomous systems to perform complex tasks in dynamic edge environments.
AI Model Tutorials
Discover deep learning models commonly used in embodied intelligence solutions and how to run them on Intel platforms complete with benchmarks and Jupyter notebooks.
OpenVINO™ Toolkit
Get started with the OpenVINO™ Toolkit to simplify the development of AI inference, computer vision, automatic speech recognition, and NLP on Intel® hardware.
Support
Provides comprehensive support for Edge AI and Intel technologies, delivered by global professional technical experts.
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