Efficient and secure use of machine data with PlatonaM

The PlatonaM research project pursued the goal of enabling the secure and legally compliant utilization of machine data. An innovative platform ecosystem was developed to reduce data interfaces, uncover previously hidden correlations in machine usage and optimize the forecasting and prioritization of maintenance measures.

Challenges in maintenance and data usage

The intelligent analysis of machine data offers considerable potential for increasing efficiency in maintenance. Studies show that predictive maintenance can increase the operating times of systems by up to 20% and reduce maintenance costs by up to 10%. Nevertheless, there are numerous challenges, particularly in the area of secure data usage and a lack of standardization.

Machine data is often provided via various proprietary interfaces, which makes comprehensive analysis difficult. Many companies are also reluctant to share their data as data protection and legal compliance are unclear. This is where PlatonaM came in to develop a centralized solution for secure and efficient data usage.

Technological implementation and solution approaches

PlatonaM created a platform that makes machine data usable in a secure and legally compliant manner while maintaining data sovereignty. The innovative approach reduced the number of individual data interfaces and enabled comprehensive analysis of distributed data sources. With the help of machine learning, patterns and correlations in the data could be recognized and precise predictions for maintenance measures could be made.

A particular focus was on the development of a marketplace for data-driven services. Companies were able to use the platform to develop new digital business models based on the storage, analysis and visualization of machine data, for example.

Benefits and areas of application

PlatonaM enabled optimized maintenance planning and improved the prediction of machine failures. Companies were able to plan and prioritize maintenance measures, which reduced machine downtime and increased productivity.

Thanks to the platform's open architecture, various sectors were able to benefit from the solutions developed, including the manufacturing industry, logistics companies and energy suppliers. The scientific exploitation of the developed technologies also facilitated the transfer of innovative approaches into practice.

Project partners and cooperation

PlatonaM was implemented in an interdisciplinary consortium. In addition to Fraunhofer IML, InfAI Management GmbH (consortium leader), Simba n3 GmbH, SITEC Industrietechnologie GmbH and the University of Hohenheim were also involved. The close cooperation between science and industry ensured practical solutions and a high relevance of the results for various fields of application.