Enormous amounts of data are already generated today in the production of products. At the same time, sensors and actuators are becoming increasingly powerful and cost-effective, so that an exponentially increasing amount of data can be expected in the coming years. Now it is important to process the data correctly and use it in such a way that it can benefit from this wealth of data.
Through machine learning and artificial intelligence, raw data can be processed into information that forms the basis for modern condition monitoring and predictive maintenance systems.
With SWMS, you make the right decisions when selecting ML and AI tools and the architecture of your software systems. We develop the algorithms in such a way that they work comprehensibly and transparently for you.
Customer: Manufacturer of electric linear actuators for the aerospace industry
Topic: Implementation of a Condition Monitoring System
Challenge: Evaluation of existing data without internet connection and implementation within an aircraft cabin
Solution: Development and evaluation of architecture options
Recording of the data in a test enviroment and evaluation of data quality
Conventional data analysis
Machine Learning (Tensorflow)
Development of an embedded Linux system