Monitoring systems

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Schaeffler OPTIME

Simple integration
Complete automation
Scalable wireless IoT solution
Machine learning and AI-algorithms
Maintenance cost savings up to 50%

Comprehensive and automated machine unit condition monitoring system. Based on IoT technology, this system provides early warning of damage to machine components. Consisting of a wireless (NFC) sensors and gateway, this solution can be scaled in any way. All captured data is analyzed in cloud, using machine learning and other AI solutions designed by Schaeffler and then visualized in the special app. Such solution allows you to monitor all units using just one computer or smartphone.

For cost reasons, permanently installed continuous condition monitoring is typically used only for production machines that are directly process-critical. In the process manufacturing and automation industries, it is therefore not uncommon for up to 95 percent of all assets in a production facility to be either totally unmonitored or monitored only periodically by means of route-based, manual measurements.

With Schaeffler OPTIME, however, comprehensive and automated condition monitoring is now a cost-effective IoT proposition for maintenance personnel and facility operators. This is an efficient and easy-to-use low-cost solution designed specifically for the comprehensive condition monitoring of all indirectly process-critical assets across entire machine and equipment parks.

OPTIME is an easily scalable system that consists essentially of wireless, battery-powered vibration sensors, a gateway, and an app to visualize the resulting analysis data. The data captured by the sensors are analyzed using specially developed algorithms that draw on Schaeffler’s technical expertise, its extensive storehouse of physical models developed and refined over many decades, and the experience in condition monitoring that it has built up in the course of its bearing servicing operations.

OPTIME can be installed and initial operation carried out without any prior condition monitoring expertise, and several hundred measuring points can easily be set up in the space of a single day. The vibration sensors are attached to the monitored assets by means of screws or adhesive, and are activated by the accompanying app, which connects to them via near-field communication (NFC). All installed sensors communicate autonomously with each other and the gateway, thereby forming a dedicated mesh network that ranks among the most reliable and energy-efficient types of IoT networks in use in industry today. The sensors in the mesh network transmit machine KPI data and raw vibration and temperature data via the gateway to the Schaeffler IoT Hub. The hub analyzes the data, and the results are displayed in the app, which supports a very wide range of end devices commonly used by maintenance teams and plant operators. Alternatively, the analysis results can be made available for integration into the customer’s own IT environment via a REST API.

System provides several weeks’ early warning of damage to machine components such as electric motors, fans, and pumps. It also provides early warning of imbalances, misalignments, and knocking. The app presents trends in graph form and visualizes the severity of incidents using traffic light colors, alarm states, and other information. Assets can be grouped according to users’ requirements, and their condition can be presented in a range of user group-specific views. With OPTIME, in-house maintenance crews and external service contractors receive specific recommendations on the remedial steps required, so they can easily plan their maintenance work, manpower requirements, and spare parts procurement in a timely and cost-efficient manner.

OPTIME can yield cost savings of around 50 percent compared with monthly offline measurements made using hand-held devices. It also provides better-quality monitoring than most wireless online CMS systems thanks to its complex, algorithm-based analytics. Moreover, OPTIME can be used for a multitude of assets for which condition monitoring was previously not commercially viable, which makes it the first solution capable of providing an overview of machine states that is truly comprehensive and encompasses all subsystems and auxiliary assets.