Project requirements: Avoidance of unplanned downtime and reduction of maintenance costs for industrial machinery and equipment
In industrial plants, the reliable operation of rotating machinery is a key prerequisite for stable production processes. However, components such as motors, pumps, conveyor belts, bearings, gears and compressors are subject to continuous wear, which is only visible to a limited extent during operation. Condition information is often only available selectively and is mainly based on fixed maintenance intervals or manual inspections. Unexpected malfunctions and failures therefore lead to production interruptions, increased maintenance work and additional costs. At the same time, there is a lack of consistent, manufacturer-independent transparency regarding the actual condition of the systems, particularly in the case of older or heterogeneous machinery.
Partner solution : IIoT-based condition monitoring with WIKA Rotating Machinery Manager
The solution is aimed at industrial and plant operators who require a qualitative assessment of the machine condition in addition to simple condition monitoring. It is particularly suitable for maintenance, reliability and operations managers who operate a large number of rotating machines and want to assess risks at an early stage without having to rely on manual inspections.
The central element is an anomaly score that converts complex sensor data from vibration, ultrasound and temperature into a comprehensible status indicator. This score enables users to clearly prioritize deviations from normal operation and plan maintenance measures based on data. Expert tools are also available to support a detailed analysis of individual machines using trend curves, raw data analysis, FFTs and root cause analysis of detected anomalies.
The solution is suitable for companies with limited maintenance resources that need a clear basis for decision-making, as well as for experienced maintenance teams that want to carry out in-depth diagnostics using the Expert tools. Regardless of industry, asset age or manufacturer, the solution creates transparency, reduces complexity and supports the sustainable transition to a predictive, condition-based maintenance strategy.
The solution is based on the use of the WIKA Rotating Machinery Manager, a universal and autonomous IIoT solution for the predictive maintenance of rotating machinery. The core of the solution is a wireless multi-sensor beacon that records temperature, ultrasonic and vibration data and detects even the smallest deviations from the normal condition at an early stage. The sensors are battery-operated, require no cabling and can be installed quickly and without interfering with ongoing operations. Wireless data transmission takes place via LoRaWAN®, which enables long ranges and easy integration into existing or newly built infrastructures.
The collected data is analyzed by an integrated machine learning algorithm that identifies anomalies at a very early stage, evaluates possible causes and relieves the maintenance teams through automated condition assessments and intelligent alarm management. The results are available via a web application in the form of a clear dashboard and offer full transparency about the machine status. In addition, the data can be integrated into existing IT systems via standardized APIs. The solution thus supports the transition from corrective to predictive maintenance and sustainably increases system availability, efficiency and operational reliability.
Effects and benefits: Early detection of deviations through anomaly score as a clear status indicator
- Prioritization of critical machines without evaluation of complex raw data
- Machine learning algorithms detect damage long before failure
- Expert tools enable detailed root cause analysis and trend evaluation
- Reduction in unplanned downtime and maintenance costs
- Wireless, simple retrofitting without interrupting production
- Transparent machine status via dashboard and APIs
Philipp Lausberger, IIoT Application Specialist
WIKA's IIoT solution condenses temperature, ultrasonic and vibration data into a clear condition assessment of rotating machines and enables early, data-based maintenance.
