Unplanned failures of individual machine components frequently disrupt production processes in many factories. The AI-based maintenance assistant from ai-omatic solutions monitors the condition of machines and detects deviations from normal operation in real-time, helping to prevent potential breakdowns and address their causes. This solution exemplifies the potential that artificial intelligence holds for manufacturing companies. As a new member of SEF Smart Electronic Factory e.V., ai-omatic solutions GmbH brings its AI expertise to joint use cases that benefit German small and medium-sized enterprises.
According to a 2023 study by Siemens, unexpected machine downtimes result in approximately 3.3 million lost working hours per year. Economic efficiency in production heavily relies on the availability of equipment, which can only be ensured with effective maintenance. AI methods enable the early, automated detection of anomalies and potential problems, explains Lena Weirauch, Managing Director and Co-Founder of ai-omatic solutions GmbH.
ai-omatic solutions has developed AI-based maintenance software that functions as a digital maintenance assistant. Unlike traditional reactive maintenance strategies, this preventive approach allows for the timely planning of maintenance actions. Through real-time analysis of machine data, companies can implement a predictive maintenance strategy, minimize downtimes, and extend the lifespan of their equipment.
As a new member of SEF Smart Electronic Factory e.V., the AI specialist will promote the use of artificial intelligence in factories. The specific aim is to establish joint use cases to optimize machine processes, reduce error costs, and develop self-learning machines in line with Industry 4.0 principles.
“We aim to make the potentials of artificial intelligence accessible to German SMEs. In the Smart Electronic Factory e.V., we can test and validate new solutions and technologies under real conditions in the smart electronics factory of member Limtronik, ensuring they meet industrial requirements,” says Lena Weirauch.
Initial joint use cases include the development of a system for optimizing maintenance planning and the further development of data analysis to identify bottlenecks and optimize production processes.
