Companies benefit from reduced downtimes, extended machine lifespans, and significant cost savings. Seamless integration into existing IT systems and scalability across various machine types make this solution particularly attractive for diverse industries. In the energy, pharmaceutical and manufacturing sectors in particular, numerous companies already rely on automated monitoring by aiomatic.

In today's industrial landscape, companies face the challenge of preventing unforeseen machine failures that can lead to production disruptions and delivery delays. Traditional maintenance approaches, such as reactive repairs or regular preventive measures, are often inefficient and costly. This is where aiomatic's Predictive Maintenance software comes into play.

By continuously analyzing sensor data and employing advanced AI algorithms, the software monitors machine conditions in real-time. A Health Score ranging from 0 to 100%, developed by aiomatic, provides precise information about the current state of equipment. This enables maintenance teams to identify potential issues early and take targeted actions before costly breakdowns occur.

Implementation of the software is straightforward, thanks to standardized interfaces like OPC UA. It integrates seamlessly into existing IT infrastructures without the need for extensive IT projects or expensive hardware investments. Additionally, the solution is highly scalable and can be easily applied to various machine types and models.

A new basic package, a compact, cost-effective solution developed specifically for smaller companies and SMEs, enables companies to easily get started with proactive maintenance - with fast implementation, minimal effort and transparent costs.