Evolving maintenance practices have improved asset management effectiveness in recent years and now our technology can provide operators with real time insights into asset performance and advanced warning of potential problems, before damage is caused or breakdowns occur.
A reliable asset is critical to overall system uptime just as operating efficiency is also vital in ensuring that design process conditions are met and running costs are optimized. It is not uncommon for process demands to change over time and the Elmodis system enables operators to easily identify when assets are operating outside their best efficiency zone and to take corrective action. These improvements usually limit wear, increase asset lifetime and reduce energy consumption, providing significant recurring savings.
Annual Service subscription, including system features and functionality:
- detection of a process change, overloads,
- statistical data – number of starts, operation time,
- detection of phase failure, asymmetry,
- overview of parameters measured in continuous online mode.
Features as for MONITORING package and additional functionality:
- detection of misalignment,
- detection of imbalance of the motor rotor,
- diagnosis of motor electrical condition,
- detection of anomalies,
- tracking parameter trends.
Features as for DIAGNOSTIC package and additional functionality:
- benchmark reporting for operating parameters of all monitored assets to enable abnormalities to be recognised more quickly,
- overview of measured parameters in continuous online mode,
- notification when warning and alarm limits are exceeded,
- operational conditions regarding RPM, Best Efficiency Point,
- operational problems e.g. Cavitation and Dry Run.
Equipment installation, system implementation, collection of technical machine data, checking that sensors are installed correctly.
Verification that the sensor data corresponds to the rated data (electrical data), that the process and vibration data corresponds to the actual behavior of the machine and its environment.
ANALYTICS LAUNCH & LEARNING PHASE
Detection of machine operating states and performance characteristics of the system in which the machine operates. Determination of threshold values, data clustering and labeling, development of KPIs, training of the created model and implementation within the device.
MONITORING AND PREDICTION
Monitoring and prediction of complete machinery parameters and performance. Verification of models and algorithm parameters.