The goal of the provided service is to keep the manufacturing process for recognized European automotive manufacturer running smoothly and detect failures that often arise with the automatic feeding system moving baskets around.

Prague subway transports a million passengers every day and the escalators are essential. So the mechanical components of the escalators are constantly used and worn. The operator needs to know when maintenance and replacement of the damaged component are required to avoid their failure. Neuron soundware has a predictive maintenance solution for such a problem.

What inspired the founders of Neuron Soundware to focus on this area, and how does your AI-driven technology offer a unique approach compared to traditional methods of maintenance

Many customers ask us how artificial intelligence works in detecting audio anomalies. We have prepared an article with an illustrative example of escalator monitoring.

Neuron Soundware technology, based on evaluating the health of the machine according to its sounds with AI and machine learning algorithms, is applicable not only to the prevention of production downtime but also in process control within production processes such as verification of the quality of the material in the grinding process. Let us dive into a recent use case.

Neuron Soundware detected an impending fault in the piston helium compressor for hardening gearboxes in the automotive industry. In March 2021 our AI detected an impending critical fault in the piston compressor, which later culminated in machine downtime. Early detection of this fault represents a concrete result and proof of how machine learning algorithms can assist in predictive maintenance.