SESI
Sensor-based real-time simulation for machine part specific analysis and evaluation in the context of a synchronized and condition-based maintenance
The aim of this research project is to propose a suitable maintenance strategy for manufacturing SME so that they might anticipate machine failures.
Machine downtime poses a huge economic risk, in particular, for small and medium-sized enterprises (SME). Unable to compensate for machine downtime because of lack of resources and experience, SME often fail to develop and implement a cost-efficient maintenance strategy. Thus, the aim of this research project is to propose a suitable maintenance strategy for manufacturing SME so that they might anticipate machine failures. Here, two methods were developed which integrate a condition monitoring and simulation tool on the one hand and a tact-based maintenance planning and control system on the other hand. Combined, these two methods allowed SME to increase their machinery capacity by forecasting their maintenance tasks. In conclusion, the devised condition-based maintenance strategy, built on sensor-based real-time simulations, raises machine resource capacities, boost on-time delivery and reduce machine maintenance costs. This proposed strategy is a key to success for small and medium-sized manufacturing companies.
Project partners
Topic Area
- Service Management
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Projectinfos
Duration
Funding no.
17650 NFunding information
Das IGF-Vorhaben 17650 N der Forschungsvereinigung FIR e.V. an der RWTH Aachen, wurde über die AiF im Rahmen des Programms zur Förderung der industriellen Gemeinschaftsforschung und -entwicklung (IGF) vom Bundesministerium für Wirtschaft und Technologie aufgrund eines Beschlusses des Deutschen Bundestages gefördert.