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Use cases for maxon MIND
situations. This creates a robust model tailored to the customer’s application. Anonymized data Data handling also plays an important role in maxon MIND. By default, data processing takes place in the cloud. Customers can view and download their data. No personal information is re- quired, and all data can be anonymized by the customer. The solution is minimally invasive: existing motors, electronics, and con- trollers remain unchanged. The only requirement is installing a software package on the master controller that transmits data via a protocol. In the market, maxon MIND posi- tions itself as a highly specialized solu- tion for demanding applications. maxon pursues a focused approach that deeply analyzes the physical properties of the drive system. This combination of tech- nical focus, industrial robustness, and open architecture makes maxon MIND a solution that not only collects data but delivers real insights. In automated laboratory systems, the reliability of the drives is crucial for sample integrity and throughput. With historical trend analysis and predictive alerts, laboratories can fine-tune system performance, reduce mainte- nance efforts, and ensure consistently high quality. → Medical devices Ensuring operational readiness in life- critical systems: In medical technology, even brief interruptions can jeopardize patient safety. maxon MIND enables early detection of anomalies in drive systems used in surgical, diagnostic, Avoiding downtime on the production line: In high-throughput environments, the failure of a single motor can bring the entire operation to a halt. maxon MIND provides real-time insights that help detect wear early and prevent failures before they disrupt production. This improves overall equipment effectiveness (OEE). → Laboratory automation and life-support devices. → Industrial automation
time. It also identifies issues that remain hidden in traditional tests. Explainable, optimized AI Technologically, maxon MIND is based on explainable artificial intelligence. This ensures that all diagnoses and predic- tions are traceable – a key requirement for safety-critical and highly regulated applications. The machine learning model devel- oped by maxon also requires minimal data and can run on simple hardware. The advantage: minimally invasive inte- gration into the application and low time investment for model training. Further- more, the model does not require GPU infrastructure, which is a cost advantage for new developments. Retrofits in exist- ing applications are also possible. Data processing follows a clearly structured workflow. First, raw data is collected during machine operation. It is then preprocessed before entering the machine learning model. The model checks the data and analyzes any devia- tion from a healthy operating state. The
result is then visualized in the frontend. Glassbox instead of black box: every processing step is traceable. A key feature of maxon MIND is the integration of domain-specific expertise into the model. The physical relationships of a mechatronic system flow directly into the modeling process. This achieves high prediction quality with minimal data requirements. The system also learns from real-world applications: during machine commissioning, an initial state is re- corded that describes the motor in the context of its environment. During op- eration, new data is regularly fed in and compared with the model. Depending on the application, this happens hourly, daily, or simply as needed. Data quality plays a central role. To achieve valid results, the recorded signals must sufficiently represent the machine’s operating state. That’s why maxon works closely with customers to define suitable measurement cycles. These may include standardized mo- tion sequences that reflect typical load
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