Machine Vision & AI Inspection Industrial PCs - IPCtech
Edge AI and high-performance industrial PCs for machine vision: GPU acceleration, multi-camera support, and real-time inspection for quality control.
GPU-accelerated computing platforms for automated optical inspection, deep-learning defect detection, and real-time quality control on the production line.
Industry Challenges
Manual inspection cannot keep pace with high-speed lines
Impact: Human inspectors process 25-30 parts/minute. Modern production lines run at 120-300 parts/minute. The gap means either slowing production or accepting undetected defects.
IPCtech Solution: IPCtech Edge AI computers with NVIDIA GPU acceleration process multi-camera inputs at 200+ parts/minute with real-time AI inference.
Traditional rule-based vision fails on variable defects
Impact: Rule-based machine vision works for fixed patterns (presence/absence, measurement) but fails on scratches, dents, stains, and texture defects that vary in shape and severity.
IPCtech Solution: IPCtech AI vision computers run deep learning models (TensorFlow, PyTorch, ONNX) that learn defect patterns from training data — detecting variable defects that rule-based systems miss.
Multi-camera synchronization and bandwidth bottlenecks
Impact: A 4-camera inspection station generates ~2 Gbps of data. Standard PCs cannot ingest, process, and decide within the cycle time.
IPCtech Solution: IPCtech vision computers feature multiple independent GigE controllers (4-8 ports) with hardware-timestamped frame capture. GPU-accelerated preprocessing offloads the CPU.
Technical Requirements & Product Mapping
| Requirement | Specification | IPCtech Product Line |
|---|---|---|
| GPU-accelerated AI inference | NVIDIA GPU / Intel AI acceleration | B7100 Edge AI Box PC |
| Multi-camera GigE Vision | 4-8× Gigabit Ethernet ports | B7100 / P8000 high-spec |
| USB3 Vision camera support | 4-6× USB 3.0 high-bandwidth | P8000 Series / B5000 Series |
| Real-time operating system | Real-time Linux kernel / Windows IoT | All x86 models |
| High-speed storage | NVMe SSD for image buffering | P8000 / B7100 |
| Industrial protocols | RS232/485 for PLC trigger, GPIO for reject signal | All models |
Recommended Products
| Model | Product | Why This Model |
|---|---|---|
| QY-B7100 | Edge AI Vision Box PC | Purpose-built AI vision computer. NVIDIA GPU, 4-8× GigE for cameras, real-time inference for defect detection and classification. |
| QY-P8150 | 15" High-Performance Panel PC | Integrated HMI + vision processing. Intel 10th Gen i5/i7, multi-USB3, suitable for single-camera inspection stations with operator display. |
Typical Deployment Architecture
Production line cameras (GigE/USB3) → B7100 Edge AI computer (image capture + AI inference + defect classification) → P8150 operator HMI (results display + reject control) → GPIO reject signal → MES database
Frequently Asked Questions
Q: Can IPCtech vision computers run custom deep learning models?
Yes. IPCtech Edge AI computers support TensorFlow, PyTorch, ONNX Runtime, and OpenVINO. We can pre-install your AI framework and optimize the system for your inference pipeline.
Q: How many cameras can one IPCtech vision PC support?
Our B7100 Edge AI PC supports 4-8 GigE Vision cameras with independent controllers for hardware-synchronized capture. USB3 Vision support adds 4-6 additional cameras depending on resolution and frame rate.
Q: What AI inference speed can I expect for defect detection?
With NVIDIA GPU acceleration, typical inference time is 10-50ms per image for classification models and 50-150ms for object detection/segmentation — supporting line speeds of 120-300 parts per minute.
Q: Do you support GigE Vision and USB3 Vision standards?
Yes. IPCtech vision computers are compatible with all major industrial camera brands that follow GigE Vision 2.0 and USB3 Vision standards, including Basler, FLIR, Allied Vision, and Baumer.
FAQ
Can IPCtech vision computers run custom deep learning models?
Yes. IPCtech Edge AI computers support TensorFlow, PyTorch, ONNX Runtime, and OpenVINO. We can pre-install your AI framework and optimize the system for your inference pipeline.
How many cameras can one IPCtech vision PC support?
Our B7100 Edge AI PC supports 4-8 GigE Vision cameras with independent controllers for hardware-synchronized capture. USB3 Vision support adds 4-6 additional cameras depending on resolution and frame rate.
What AI inference speed can I expect for defect detection?
With NVIDIA GPU acceleration, typical inference time is 10-50ms per image for classification models and 50-150ms for object detection/segmentation — supporting line speeds of 120-300 parts per minute.
Do you support GigE Vision and USB3 Vision standards?
Yes. IPCtech vision computers are compatible with all major industrial camera brands that follow GigE Vision 2.0 and USB3 Vision standards, including Basler, FLIR, Allied Vision, and Baumer.