Pumps, compressors, cranes, conveyor belts… hardly any branch of industry can survive today without electric motors. Drive trains offer huge potential for both power and carbon savings, which can be leveraged thanks to digital solutions in conjunction with the most efficient hardware components. Companies can remain competitive or bolster their market position when motors, drives, and smart digital solutions work together. The Digital Drive Train organization will enable Siemens to optimally manage the challenges faced by users and leverage the full potential offered in this area.
The key to more sustainable industrial motion lies in improving the energy efficiency of the system, which in turn is achieved by optimizing the system as a whole. Taking all individual optimization measures together, it is possible to achieve savings of 60 percent. Thanks to the Siemens portfolio for laying out drive trains, users can plan and simulate the performance of their industrial systems before they go into operation. This ensures that all drive components are correctly dimensioned and prevents excessive power consumption. By analyzing plant data in a completely networked system, energy efficiency can be taken to the next level and realize substantial conservation of carbon emissions and resource consumption – in addition to reducing lifecycle costs. The actual enablers of sustainable motion, however, are analytical tools and self-learning Industrial Edge and cloud applications.
Savings in a very short time
One example of the digitalization of factory infrastructure can be found at the Siemens Electronics Works in Erlangen. The goal was to reduce maintenance costs by minimizing manual intervention using condition-based maintenance, improving plant and system availability by identifying anomalies, and becoming carbon neutral through a combination of energy efficiency and decarbonization. An AI-based condition monitoring system for low-voltage motors was installed based on the plug-and-play SIMOTICS Connect 400 sensor module and the SIDRIVE IQ Fleet analysis app. Just a few weeks after it went into operation, the app detected an anomaly, and the maintenance measures that were applied prevented a machine outage. That improved availability by five percent. It was also possible to identify the uneven capacity utilization in a redundantly structured thermal energy recovery system and take appropriate actions to increase the machine’s product lifecycle by 33 percent. Optimized, condition-based maintenance cycles also reduced maintenance overhead by 15 percent. And the solution scores with a short return on investment of less than one year.
Potential in the future
In the future, the convergence of the real and the virtual drive train will be advanced using the digital IoT portfolio. What does that mean in concrete terms? Using trace data from the field device, the actual performance of the drive train and the load in question – for example, the load of a driven machine – are recorded and then the real values are compared to the simulation model. In the next stage, the real drive train data is fed into the simulation model, which is then trained with the properties of the entire system model. The real-world data can therefore be used to modify the system model to ensure that it precisely describes the entire system. A number of scenarios can be investigated by changing various parameters. A deviation between real and simulated output highlights the change and indicates that the system’s performance has changed and that maintenance is required. Applying these trained system models and digital twins to the development phase of new drive applications will result in a massive improvement in productivity and time efficiency.
SIMOTICS CONNECT 400 & SIDRIVE IQ FLEET – Digitalizing low-voltage motors
Whether it is pumps, fans, or compressors: For a rapid and comprehensive overview of the operational and condition data of their low-voltage motors, users can utilize the plug-and-play SIMOTICS Connect 400 connectivity module and the SIDRIVE IQ Fleet Industrial IoT Cloud analysis app to easily implement a low-cost, cloud-based solution for continuous condition monitoring of LV motors.
- Improved productivity thanks to reduced downtime and fewer system malfunctions
- Optimized level of maintenance activities to ensure a longer product service life and improved plant availability
- Energy savings thanks to artificial intelligence and data analyses
- Optimized maintenance-friendliness thanks to remote monitoring and cloud-based fleet management