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Which industrial PC should I choose for a vision machine?

Requirements from the field

Size the complete chain, from sensor to decision

A vision application requires a continuity of performance. Acquisition rate, memory copy, preprocessing, inference, decision, and machine control must fit within the same time budget.

That is why we start from your cameras, your cadence, and your software before defining the CPU, GPU, connections, and format of the PC.

Size the complete chain, from sensor to decision

01

Cameras, resolution, frame rate, color depth

Image stream

Cameras, resolution, frame rate, color depth

02

Maximum latency, synchronization, and triggering

Cycle Time

Maximum latency, synchronization, and triggering

03

Classic vision, 3D, AI, training or inference

Treatment

Classic vision, 3D, AI, training or inference

04

Temperature, dust, vibrations, and clutter

Terrain

Temperature, dust, vibrations, and clutter

5 points to validate for choosing the right chassis

Each criterion influences the others. An additional camera can change the network, storage, computing power, and thermal dissipation.

01 Acquisition

Camera interfaces and bandwidth

GigE Vision, USB3 Vision, Camera Link, CoaXPress, PoE, GMSL or FAKRA: the interface determines the data rate, cable length, synchronization capabilities and, in some cases, the need for a dedicated frame grabber.

02 Processing

CPU, GPU and algorithm requirements

The CPU remains essential for orchestration and sequential processing. A GPU becomes relevant for deep learning, 3D processing, parallel data streams or when inference time is critical.

03 Control

Real-time I/O and synchronization

The PC must communicate with lighting systems, encoders, sensors and PLCs. Isolated GPIO, serial interfaces, CAN or industrial networks make it possible to trigger, timestamp and process each capture at precisely the right moment.

04 Integration

Mechanical and thermal architecture

A fanless design reduces maintenance requirements and dust ingress, while tower or rack-mounted systems support more PCIe cards and provide greater heat dissipation. The actual ambient temperature remains the starting point.

05 Lifecycle

Long-term availability and maintenance

Component availability, operating system stability, storage accessibility, GPU replacement and configuration reproducibility help secure series deployments and ensure reliable operation over many years.

Frame dimension

4 architectures, a choice always guided by use

There is no universal "best vision PC." The right format is one that reserves the necessary power, interfaces, and room for useful evolution – without unnecessary overkill.

Types of chassis for industrial PC
01

Fanless CPU

Conventional vision and demanding environments

Deterministic processing, low maintenance and installation as close as possible to the machine.

02

Fanless + GPU

AI inference and parallel edge computing

NVIDIA GPU in PCIe or MXM format when the algorithm requires hardware acceleration.

03

Tower / Shoebox

Scalable projects with specialized expansion cards

The right balance between compactness and expansion for frame grabbers, I/O, networking or GPUs.

04

2U / 4U Rackmount

Multi-camera systems and high expansion density

Multiple PCIe slots, controlled cooling and easy access in a rack or industrial cabinet.

With or without a graphics card?

A GPU is only necessary if it creates a measurable advantage

A GPU is only necessary if it creates a measurable advantage

A graphics card is not an automatic prerequisite.

For a well-optimized conventional inspection, a recent Intel Core processor may be the most economical and simplest solution. There are 4 formats of GPUs usable today in the industrial vision sector:

  • Graphics card or GPU on PCIe port (standard graphics card) - Very high performance
  • MXM format GPU (Dedicated chip for compact fanless PCs) - High performance
  • AI accelerators (Dedicated chip for small AI computations) - Low performance
  • Nvidia Jetson GPU (Dedicated chip for local AI) - Medium performance

CPU preferred

  • Sequential algorithms
  • Conventional preprocessing
  • Limited thermal budget

GPU recommended

  • Deep learning and inference
  • 3D and massively parallel computing
  • Multiple high-resolution streams

Discover the content written by the industrial vision experts at Integral System directly on our blog

Your project is our starting point

Do you know your cameras, your setup, and the requirements related to the production rate of your activity?

We size the ideal vision PC to optimize your productivity!

We size the ideal vision PC to optimize your productivity!

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