PlatonaM

Platform ecosystem for innovative management through predictive maintenance

The increasing IT networking of machines in the industrial sector (Industry 4.0) represents an important information technology basis for the far-reaching optimisation of production processes. For example, sensors and Internet-based process and machine data (Internet of Things, IoT) can be used to increase the quality, performance and availability of individual machines or entire plants as a result of predictive maintenance. At the moment, however, there are no solutions on the market that allow data to be viewed across manufacturers and customers. This ensures that promising potentials, for example improved forecasts of required maintenance intervals as a result of a broader database, have so far remained unused. In addition, high investment costs and concerns about secure and lawful data usage are the most common barriers to adopt Industry 4.0 applications in German companies.

Against this background, the PlatonaM project aims to ensure that machine data can be safely used as an independent asset and across all manufacturers and customers. On the basis of the project results, the direct and indirect network effects known from platform economics are to be transferred to the area of application of predictive maintenance management, thereby creating the conditions for a market for machine data.

As part of PlatonaM, the project partner InfAI Management GmbH is pursuing the overall goal of designing and developing a process-oriented IoT platform that methodically and technically supports the integration, manipulation, analysis and service-based provision or use of machine data while maintaining business privacy. As a central result, architectural models are developed, prototypically implemented and evaluated using the example of predictive maintenance management.

Duration: 01/2019 – 12/2021
Funding programme: „Smarte Datenwirtschaft“, Bundesministerium für Wirtschaft und Energie (BMWi)
Funding number: 01MT19005A

Project website