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EcoStruxure Asset Advisor (EAA) Solution For Motors
More than 64% of production interruptions are caused by explosions and fires, mostly due to shortcomings in the maintenance and monitoring of electrical equipment. So how to minimize unfortunate incidents as well as maintain continuity for machinery and engine systems?
1. The importance of predictive maintenance
Predictive maintenance is a method of assessing the actual condition of equipment to predict problems that are likely to occur. From there, businesses can reduce unplanned system downtime as well as avoid unpredictable damage due to critical engine failures.
According to a survey by the US Department of Energy, on average, a predictive maintenance program can increase the return on investment (ROI) by 10 times, save 30% on maintenance costs, eliminate 75% of incidents, and reduce up to 45% of downtime of machinery and equipment.
2. Why should we continuously monitor engines?
From data centers to machinery and electrical equipment systems around the world, they must operate continuously and non-stop to meet the needs of daily life, and production, and maximize the productivity of machinery and equipment. With continuous operation, the system will always have potential risks and incidents that can lead to interruptions in operations. Any interruption can affect the operation and efficiency of the business.
Therefore, 24/7 engine monitoring with IT systems helps businesses closely control risks, maintain continuity, optimize operating performance, save maintenance costs, and ensure the safety of human resources.
3. Operating principle of motor monitoring solution at OTECH
With the desire to contribute to improving production and operation quality for businesses, OTECH provides Schneider Electric’s predictive maintenance and motor monitoring solution, including 3 main stages as follows:
Phase 1: Installation
We will install specialized IoT sensors to measure current and voltage, signal converters, and gateways in the MCC cabinet to collect and upload data to the cloud as well as evaluate the motor status in real-time.”>
Phase 2: Machine learning
After installation, the system begins to learn the characteristics of the monitored motor. From there, abnormalities and failure risks will be quickly detected through artificial intelligence (AI) and machine learning (ML).
Phase 3: Putting EcoStruxure Asset Advisor (EAA) into use
The system monitors objects 24/7, customers will receive warnings via EAA web portals when there are foregrounds detected. Based on the level of importance and current status, the system will provide a detailed chart of the motor’s health.
4. Abnormality warning process
First, motor data is collected and sent to Schneider Electric’s EAA Portal via the Internet. Next, the EAA system will secretly monitor the parameters until it detects an abnormality. Information about the abnormal event is immediately sent to Schneider Electric experts for analysis and confirmation. When the expert confirms that there is an abnormality, EAA will issue a specific warning to the customer about the affected object. Finally, the customer performs the inspection and confirmation.
In addition, when registering for a system-wide periodic reporting package. Customers will receive a comprehensive report on the health information of all motors, an analysis of problems of motors with low health index as well as solutions proposed by Schneider Electric experts.
5. Outstanding advantages of the solution
Using MCSA technology
Motor Current Signature Analysis (MCSA) is a proprietary technology that analyzes current and voltage waveforms to provide information on the status, performance, and energy consumption of AC motors.
The outstanding benefits of MCSA include:
- Predicted fault accuracy is up to 90%
- Specifically indicate the type of fault
- Detect both mechanical and electrical faults
- Easy and quick sensor installation
- Sensors are installed directly in the MCC cabinet
- Can be applied in explosive environments
- Providing energy information and optimizing equipment
Comparison between MCSA technology and vibration analysis technology
24/7 motor monitoring
With the 24/7 online motor monitoring capability of the EAA system, motor failure risks can be detected quickly within just 2 weeks to 5 months. Thus, customers can promptly recognize and fix the problem right from the moment it starts.
Optimizing execution time
Not only providing solutions, OTECH also wants to bring customers absolute satisfaction with fast implementation progress, taking only 30 minutes for engine installation and 2 – 6 weeks for the machine learning phase.
High Accuracy
Along with speed, we will still ensure our customers in terms of service quality and expertise. With the motor monitoring solution, the correct pre-warning rate is up to 90%. Not only that, the system can detect more than 30 types of pre-warning errors, of which more than 20 types can be specifically predicted:
- Power supply: current or voltage imbalance, current or voltage harmonic problems, power quality problems, voltage drop or overvoltage
- Motor: phase imbalance, damaged rotor, eccentric rotor, worn bearing, stator short circuit, loose stator winding, eccentricity, soft motor mounting foot, mechanical imbalance.
- Transmission: gearbox wear, worn drive belt or chain, misaligned pulley, unbalanced drive gear, eccentric or unbalanced coupling
- Load (compressor or pump): cavitation (pump), damaged impeller (pump, fan), mechanical imbalance, worn bearings
Reference: Schneider Electric
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For more information about the EcoStruxure Asset Advisor (EAA) solution for motors, please contact us through the information below:
OTECH JOINT STOCK COMPANY
- Hotline: 1800 9472
- Phone number: (+84) 28 6686 3565
- Email: service@otech.com.vn
- Address: 02 Street 15, Van Phuc 1 Residential Area, Hiep Binh Phuoc Ward, Thu Duc City, Ho Chi Minh City, Vietnam.
