Inline quality controls have become increasingly vital in manufacturing processes, helping reduce downtime and reject rates. This ultimately leads to lower costs and improved customer loyalty. Traditionally, implementing such solutions required complex projects, resulting in high expenses. The new OXM200 2D multi-tool profile sensors offer a quicker and easier alternative for inspecting numerous process steps. These calibrated profile sensors are simple to install, ready for immediate use, and can be configured through the integrated web browser without requiring external software.

The Power-over-Ethernet (POE) functionality allows these compact devices to operate with just one cable connection. By projecting a laser line onto objects, the OXM200 sensors capture reflected light via an internal camera to generate 2D surface profiles. Using built-in measurement tools, they can analyze dimensions along the laser line (X-Z). This enables detailed inspections for tasks such as height checks of assembled parts, collision detection during assembly, and robotic control functions like positioning feed components in pick-and-place operations or gap analysis in automotive bodywork.

The sensors’ user-friendly web interface supports flexible configuration of up to seven measurement parameters with graphical assistance. Beyond the integrated tools, users can link additional measuring instruments for more versatile analyses. Features like position tracking enable seamless inspection even when objects on conveyor belts shift positions, while live visualization allows real-time monitoring and adjustment directly within the web interface.

With extensive connectivity options including Profinet, Modbus TCP, UDP, IO-Link, analog outputs, and digital signals, these sensors integrate seamlessly into automation systems. They also support connections to IT infrastructure via OPC UA or image processing platforms through an SDK. Additionally, OXM200 sensors provide access to secondary metrics like temperature and operational hours, which are essential for process optimization and calculating overall equipment effectiveness (OEE).

Last Updated: 2025-09-04 22:56:54