Quality assurance on all levels
Discom uses high-precision acoustic measurement methods to locate production-related errors
Our technical world lives by the drive. Drives in electric cars pose special requirements for end-of-line testing systems: In the case of quiet electric cars with eDrives, electric motors and their power transmissions possible production inaccuracies can cause significant disturbing noise. To avoid this both the individual components and their correlation has to be analysed. The background noise can be transferred to the interior acoustics and perceived as significant static noise.
Acoustic quality control
Thanks to the seamless integration of hardware and software, Discom acoustic testing is able to analyze the causes of errors in production precisely and provide high-precision quality control. Errors are pinpointed exactly down to the smallest gear wheel. Thanks to the “early warning system,” these errors will no longer continue into series production. The use of acoustic measurement technology thus increases production efficiency and manufacturing quality in the direction of zero errors.
High-precision measurement methods
As a technology leader, Discom monitors safety with high-precision measurement methods in the production of modules including
eDrives and EDUs (Electronic Drive Units)
Transmissions and MGUs (Motor-Gear-Units).
The acoustic measurement method unravels noises, making them “visible” with the aid of software and precisely pinpointing the source of error. Discom measures all operating states (ramping up rotational speed, braking, etc.), analyzes the background noises and compares the measurement results with a large number of parameters from its extensive database and self-learning algorithms. Automated operation of the measurement sequences keep the use of personnel low.
Goals of testing
Discom acoustic quality control filters out the components and parts that are “too loud” at the test bench. This can be the result of faulty acoustic quality due to production errors or assembly errors – for example a faulty surface of a gear wheel in the transmission or the wrong winding for the electric motor.
For industrial applications and end-of-line tests
Conversion of analog sensor signals to digital data
ROTAS software suite
Comprehensive analysis of measured data
New possibilities with Artificial Intelligence (AI)
Early warning system for production
- Error trends are detected early and prevented; suppliers can be warned
- Error cause analysis: the exact component causing a noise is identified – production errors are found
- Top measurement quality: highly reliable, stable and reproducible measurements
- Big Data: Solutions based on the largest noise database in the world and experience gained in a wide range of different companies and applications
- Self-learning process/AI: self-learning algorithms organize the data that has been derived and refine the search for causes
- Production monitoring
- Documentation of measurement results
Optimizes process costs
- 100% inspection
Increased productivity by shortened testing
- Optimized production costs
- Fewer returns
- Lowered need for resources
- Fast cycle times of 2-3 minutes per measurement
- Powerful: high production volume
- Automated, traceable measurement sequences
- Testing even in harsh production environments
- Individual solutions possible
- Optimized process costs
Additional insight information:
Power meter and data acquisition system for testing electric drives
The combination of acoustic and electrical analyses provides additional information about the test specimens during the durability test. Marathon can be connected with the transient recorder “Genesis HighSpeed” from HBM. This is a modular DAQ system for fast measurements of electrical and mechanical quantities. It combines a transient recorder, data recorder and data acquisition system in one device. This makes it possible to measure and analyze electrical parameters of the motor. For example, it can be used to measure how much power the electric motor feeds into the drive and how much heat is lost. This information is supplied to the software and integrated into its analyses and evaluations. More information can be found here.