
October 25, 2021
IKO International has unveiled its newest crossed roller bearing — the CRBT105A. This ultra-small, ultra-thin unit is designed to provide exceptional rigidity for space-constrained automated machine designs.
The CRBT105A features a 10 millimeter bore diameter, 21 millimeter outside diameter and a narrow width of 5 millimeters. Despite its compact size, the CRBT105A offers rigidity up to four times greater than double-row angular contact ball-type bearings. This combination of small size and high rigidity makes the CRBT105A suitable for robots with articulating arms as well as compact surveillance cameras.
With rollers alternately crossed at right angles to each other between inner and outer rings, the CRBT105A produces a greater contact surface to allow the bearing to handle heavy or complex loads from any direction simultaneously. This orthogonal roller arrangement results in a bearing that occupies just half the sectional area of rear-mounted, 45-degree contact angle single-row roller or ball-type bearings.
The CRBT105A also features:
- - Separators between cylindrical rollers to provide smooth rotation.
- - Dynamic load rating of 1,120N and static load rating of 811N.
- - Small coefficient of friction for high-speed rotation.
- - Lightweight design.
Crossed Roller Bearings are advanced products that are ideal for space-constrained automated machine designs. In addition to the ultra-small, ultra-thin CRBT105A, IKO also offers a wide range of rigid, compact crossed roller bearings that are well-suited for machine tools, industrial robots, medical equipment and other precision applications.
For more information, visit www.ikont.com.

The right tools and tech can enable advanced predictive maintenance, bottleneck prevention and optimization. Find out how digitalization is bridging the gap between legacy systems and Industry 4.0.
Without a doubt, digitalization is setting high standards for efficiency and throughput in production. Today, as manufacturers move ever closer to Industry 4.0, the question has increasingly shifted from ‘if’ to ‘when’ production companies will be able to make use of the data being generated with every piece that comes off the line. How do traditional companies take the first steps to digitalization and put that data to work? How do they make the move to unlocking the potential in every production system to improve and optimise their output? And what is the simplest way to harness the power of cloud computing and artificial intelligence at the edge?
As we know, not every modern factory is a greenfield high-tech showroom with pristine workers in lab smocks. In fact, many of them may not even be all that modern, but that doesn’t mean they shouldn’t benefit from the modern tools, processes and best practices that are the hallmarks of a productive and successful factory. In this journey to modernity, digitalization has become a vital bridge, enabling owners and production directors to begin harvesting the data that can provide vital clues to enhancing production.
Start with Sensors
As new standards of efficiency and quality become the norm, those seeking a competitive edge are turning increasingly to digitalization. Sensors (from very simple to highly complex) can be incorporated into all types of production lines, to measure everything from unit temperature and speed to output shape and size, weight and hardness and most everything in between. Sensors can form part of a wireless network, sending signals remotely, or can be connected directly into an existing production system, depending on the needs of the factory.
From Raw Data to Vital Information
The resulting output from these sensors is the raw data that can be transformed into information and insights to streamline efficiency, remove bottlenecks, reduce downtime and optimize production cycles—when used correctly. Before any data can be analysed, it has to be stored, either on an in-house server or using a cloud-based service for greater scope for expansion and off-site processing. Exactly how much storage is needed depends on the application, level of digitalization, output form and required analysis. For comparison, a production line with simple sensors attached to monitor throughput will generate significantly less data than one with quality-control cameras monitoring multiple types of product forms.
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