Solutions / Machine Vision & AOI
Machine Vision & AOI Industrial Computing Solutions
Industrial edge computers for multi-camera acquisition, AI defect detection, PLC integration and 24/7 production inspection.
Tell us your camera setup and inspection workload — BITECH engineering sizes the CPU/NPU/GPU platform, the industrial I/O, and any frame-grabber expansion around it.
Multi-camera acquisition — GigE / USB3 / GMSL2 / frame-grabber architectures
AI + classical vision — x86, RK3588, Jetson and RTX GPU options
PLC-ready integration — LAN, isolated I/O, CAN and serial interfaces
Camera count, interface, resolution/FPS, AI model and PLC protocol are enough for an initial architecture recommendation.
Built for vision projects like these
Find your project below — if it’s here, we can size the compute for it.
Multi-Camera AOI
PCB · SMT · packaging · surface inspection
AI Defect Detection
scratch · crack · missing component · weld issue · incorrect assembly
High-Speed Image Acquisition
GigE Vision · USB3 Vision · CXP / frame grabber · triggered inspection
Vision + PLC Automation
PASS / FAIL · coordinates · sorting · reject · robot guidance
Do you actually need an industrial vision PC?
A smart camera and an industrial AI computer solve different machine-vision problems. Start here before choosing hardware.
| Requirement | Smart Camera | Industrial AI PC |
|---|---|---|
| One simple inspection | Excellent | Good |
| Standard OCR / presence | Excellent | Good |
| Multiple cameras | Limited–Medium | Strong |
| Custom AI models | Medium | Strong |
| Multiple AI jobs | Limited | Strong |
| Local database / MES integration | Limited | Strong |
| GPU acceleration | Limited | Strong |
| Flexible software stack | Limited | Strong |
| Complex PLC / I/O integration | Medium | Strong |
| Easier vendor-managed support | Strong | Depends on integrator |
A smart camera and an industrial AI computer solve different machine-vision problems.Not sure which architecture fits? Send us your camera list
What determines the computer?
The GPU is chosen last, after the workload is defined.
Camera Count + Resolution + FPS / Trigger Rate + AI Model + Cycle Time + Concurrent Tasks + PLC / MES Integration = Required Compute Platform
| Input | Why it matters |
|---|---|
| Camera count | Affects total acquisition bandwidth |
| Resolution | Affects image size and preprocessing load |
| FPS / trigger rate | Determines sustained throughput |
| AI model | Determines NPU / GPU requirement |
| Cycle time | Defines the maximum total processing window |
| PLC protocol | Affects automation integration |
| Storage | Determines NVMe capacity and endurance needs |
| Environment | Affects cooling and enclosure selection |
The production vision architecture
The industrial computer is one part of the complete vision chain — designing it in isolation is why demos fail in production.
Where standard PCs become a risk in production vision
A consumer or office PC can pass a demo and still be the wrong foundation for a line that runs continuously. In production, the risks are:
Sustained CPU/GPU load — continuous inference generates heat a short benchmark never reveals
Long-term thermal stability — throttling under sustained load degrades throughput hours in
Industrial I/O — real fieldbus and digital I/O for the PLC link, not just USB
Wide-voltage input — cabinet and machine power is rarely a clean, fixed rail
Unattended operation — no operator standing by to reboot a hung system
Hardware watchdog — automatic recovery when software or the OS hangs
Controlled BOM — the same validated board ships years later
Lifecycle — availability for the life of the machine it inspects
Connector retention — locking connectors that survive vibration and handling
Expansion — the right PCIe slot for a frame grabber or high-speed NIC
Real AOI applications
PCB / SMT
missing components · solder defects · wrong component orientation · connector presence · surface scratches
Packaging
label placement · OCR / date code · seal inspection · fill level · foreign-object detection
Automotive
weld inspection · paint defects · assembly verification · gap & flush · missing components
Surface / Material Inspection
scratch · crack · dent · corrosion · coating defects
Choose the compute architecture by workload
Camera count alone does not determine the platform. Resolution, FPS, model complexity, cycle time and concurrent workloads must also be considered.
| Workload | Cameras / Interface | Compute direction | BITECH platform |
|---|---|---|---|
| Classical vision / OCR / presence check | 1–4 GigE / USB3 | x86 CPU / iGPU | AX-130BT / AX-134BT |
| Compact AI defect detection | 1–3 camera streams | RK3588 NPU | AE-3588 family |
| Multi-camera deep learning | 4–8 GigE (workload-dependent) | x86 + discrete RTX | AE-760EBT |
| Robot / mobile vision | GMSL2 / mobile cameras | Jetson Orin | AE-NJ60BT |
| CXP / Camera Link | Frame grabber required | PCIe expansion | Engineering review |
| Multi-GPU / very high bandwidth | Custom | Custom GPU platform | Contact engineering |
Classical Vision — AX-130BT / AX-134BT
Best when: classical machine vision, OCR, presence/absence, PLC communication, multi-network industrial control, CPU/iGPU workloads, industrial I/O integration. These are x86 industrial control platforms — not high-TOPS discrete-GPU systems.
DetailsCompact Edge AI — AE-3588 family
Best when: low-power AI, local detection, moderate camera count, fanless deployment.
DetailsMulti-Camera GPU AI — AE-760EBT
Best when: custom deep learning, multiple cameras, high-resolution images, complex preprocessing, higher GPU workload. Built around a discrete RTX MXM GPU.
DetailsMobile / Robot Vision — AE-NJ60BT
Best when: GMSL2 cameras, robot/AMR, compact embedded AI, Jetson Orin software stack.
DetailsFrame-Grabber / CXP / Camera Link — Engineering review
Best when: PCIe expansion is required, or specialized acquisition cards are used. Engineering review required.
DetailsHigh-end multi-GPU inspection — Custom architecture
BITECH does not position a standard catalog product as a multi-GPU inspection platform. Custom architecture — engineering review required.
DetailsEngineering capability — sized to your project
We don’t publish blanket performance guarantees. Instead, the relevant numbers are validated against your camera topology, workload and environment.
Low-latency vision architecture
Platform and I/O architecture can be sized around project-specific cycle-time targets.
Sustained frame acquisition
Camera bandwidth, buffering, PCIe resources and thermal performance are validated against the customer’s actual camera topology and sustained workload.
Sustained-load thermal design
Thermal sizing is validated according to the selected CPU/GPU configuration, installation method and ambient environment.
Isolation options
Optional isolated serial, CAN and digital I/O configurations are available for high-EMI production environments. Isolation level depends on the selected platform.
What BITECH can validate before your sample order
Before you commit to a sample, we can review and test:
- Camera / network bandwidth review
- Frame-grabber compatibility
- GPU / NPU workload test
- Sustained CPU/GPU thermal test
- PLC / industrial I/O communication test
- BIOS auto power-on
- Watchdog behavior
- OS / driver compatibility
- Storage configuration
- Interface verification
Test reports and lab documentation from the BITECH validation lab are shared with the configuration proposal.
Project delivery
Requirement -> Sample -> Validation -> Production
OEM/ODM · sample evaluation · 24-month warranty · long-lifecycle platform options.
Engineering guide
Why Factory Vision Fails Outside the Lab
Lighting, dataset shift, false positives, cycle time, PLC integration and sustained thermal performance — the reasons an AI vision demo fails on the floor, and how to design around them.
Read engineering guideMachine Vision & AOI
Frequently asked questions
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Start with camera count, interface, resolution, FPS, AI model, cycle-time target, PLC protocol and environmental conditions. The GPU should be selected after the complete workload is defined.
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No. Classical vision, OCR and simple inspection may run well on CPU or integrated graphics. Deep-learning workloads and multi-camera systems may require an NPU or discrete GPU.
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A smart camera is often suitable for one-camera, standard inspection such as OCR, presence/absence and basic measurements. An industrial AI PC becomes more useful for multiple cameras, custom AI models, databases, MES integration or scalable GPU compute. They solve different problems — not one better than the other.
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The correct platform depends on camera count, bandwidth, drivers and software stack. Camera topology should be reviewed before the final system configuration is selected.
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Yes, depending on the selected platform and protocol. Integration methods may include Ethernet-based protocols such as EtherNet/IP, PROFINET, Modbus TCP or OPC UA, as well as serial communication and digital I/O.
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Cycle time defines the total allowed window for acquisition, preprocessing, inference and communication. GPU selection should be based on sustained end-to-end workload rather than model TOPS alone.
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Production vision systems run continuously. Short benchmarks may not reveal thermal throttling, fan behavior or long-term throughput changes, so sustained-load testing against the real camera topology and environment is what matters.
Get a platform recommendation
Tell us your camera setup. We'll size the compute.
Send your camera count, interface, resolution/FPS, AI model, cycle-time target and PLC protocol. BITECH engineering recommends the closest CPU/NPU/GPU platform and identifies any required I/O or frame-grabber expansion — the GPU is chosen last, after the workload is defined.
Send us six things
- Camera count
- Interface (GigE / USB3 / GMSL2 / CXP)
- Resolution & FPS / trigger rate
- AI model (or classical / rule-based)
- Cycle-time target
- PLC protocol & I/O
We come back with
- CPU / NPU / GPU architecture
- Camera / network topology
- Required industrial I/O
- Thermal / power assumptions
- The closest BITECH platform
- A sample configuration
OEM / ODM · Sample evaluation · 24-month warranty · Long-lifecycle platform options