Components that are used in systems, such as bearings in machines, are often replaced significantly before they reach the technically possible service life and are sent too early to material recycling or disposal. Using selected applications, the partners in the consortium want to show that a decentralised condition assessment with a prognosis of the remaining service life can lead to longer use and thus make a contribution to improved resource efficiency.
Sustainability instead of short-term effects
Components in technical systems, such as bearings, are regularly replaced according to a maintenance schedule, although they could still be used in some cases several times longer. One reason for this is often the uncertainty regarding the actual condition of the components and their expectable remaining service life, because such information cannot be obtained with existing means and data or the cost-benefit ratio is unacceptable. A further barrier is that the business models of the companies involved are often not geared to such extended use of the components. For example, a manufacturer often has an interest in selling new products rather than supporting the re-use of used products, not least due to warranty issues and margins. As a result, this leads to unnecessarily high costs and burdens the environment through increased resource consumption.
Less uncertainty regarding the actual remaining service life
The partners of the "LongLife" consortium want to remove the barriers to a longer use of technical components and thus contribute to a significant saving of resources. This is to be achieved by combining technical and business management elements. On the one hand, methods and tools will be developed for the most reliable possible prognosis of the remaining service life of used technical components. On the other hand, innovative reference business models are to be developed that build on these results to make circular economical models economically interesting.
The motivation of the application partners is to quickly obtain an assessment of the condition of the components under consideration when problems occur with an overall system. Based on this, it can then be decided, for example, whether the component can be used for a longer period of time and whether costly deployment of service personnel, especially abroad, can be avoided. In addition, the users of the components should be provided with additional information as a service, if necessary, for emergency operation until the next service.
The innovation of the project approach
Three characteristics in combination distinguish the "LongLife" approach from existing methods for component analysis: The option for decentralized deployment; a platform based on Artificial Intelligence that determines the remaining lifetime; and business models that support access to data and make the continued use of the component lucrative for those involved such as component manufacturers, system suppliers and system users.
The result should effectively contribute to achieving the objectives of the funding measure "ReziProK". The aim is to achieve an optimum service life for the components as well as to maintain the value of products, components and the like as long as possible and to generate as little waste as possible. The research team expects its findings to have a high business potential, particularly in Germany, where there is a high level of competence in mechanical and plant engineering.
In Longlife, suitable sensor technology and, in combination with information technology issues such as data technology, evaluation algorithms, prediction models etc., software will be developed. This should make it possible to make a real assessment of the respective condition of the components under consideration with a view to the remaining service life. Accordingly, the project consortium consists of mechanical engineering companies, experts for artificial intelligence, data technology, smart sensor components as well as embedded systems and a scientific partner who contributes know-how on design and analysis of technical systems, business models and sustainability.
Project sheets - in German (August 2019)
The project sheet provides a clear overview of the research project.
Contributions to the ReziProK Kick-off event in December 2019
Poster No.1 - in German (December 2019)
Poster No.2 - in German (December 2019)
Presentation - in German (December 2019)