To deliver a solution for a variety of smart factory workloads, such as machine automation, manufacturing equipment, and autonomous robotics needs to be ruggedly designed. Industrial-grade computers are defined as with the ability to operate with high reliability in the harshest environment, and can smoothly integrate into a connected automation control system. For different uses, the design of a rugged computer for a smart factory may vary. Today we will introduce one of the popular applications, rackmount computers.

A rackmount PC for your Industry 4.0 intelligent manufacturing is thoughtfully designed for advanced data processing and longevity. Using racks can help protect the hardware from being knocked over or liquid spilled on. As well as benefiting from cooling, organizing, and better power management. A variety of sizes are available to suit your rack and project requirements. Sizes include 1U, 1.5U, 2U, 4U, and 5U.

In the scenarios for a smart factory for intelligent manufacturing and AIoT computing applications, rackmount computers are constructed from strong, durable sheet metal and efficient thermal management. And they suit even complex computing tasks such as ‘Artificial Intelligence (AI) and machine learning requiring the processing and analyzing of huge amounts of data. They also offer a variety of features to ensure optimal performance and the flexibility to adapt to the surrounding environment. Also, rackmount PCs accommodate diverse connectivity and expandability, with support for up to seven full-height PCI or PCI Express cards – making it a high-capacity intelligent edge computer.

1.  Some common solutions for a smart factory are,

2. Machine Learning- solve real business challenges with powerful processing and high-end features. For example, retailers can use machine vision to track customers’ movements across the store to identify their purchase patterns to make informed decisions about product placement, store layout, and staffing.

3. Data Acquisition and Processing- collect and analyze data quickly for actionable insights for example in healthcare where massive amounts of data are collected.