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Home > Open calls > Smart subsystems in service to process and condition monitoring (SMARTSUBSYSTEMS_ICON)

Smart subsystems in service to process and condition monitoring (SMARTSUBSYSTEMS_ICON)

Currently, component suppliers often provide hardware without sufficient knowledge on how the hardware will behave when it is integrated in a full machine design. This implies that the dimensioning/selection of the provided hardware is predominantly in the hands of the purchaser who needs to ensure that the component behaves in accordance to a predefined set of requirements. If the suppliers would continuously monitor the KPIs, they could make guarantees on uptime and performance but also advise the machine/vehicle designer on how much margin there is left to downsize/optimize the components. To generate such an intelligent component that monitors KPIs, the interaction (electrical or mechanical) of these components with the interfacing subsystems needs to be identified, i.e., the loading conditions of the subsystems under investigation need to be known at each time instant. This requires high fidelity models in combination with virtual sensing techniques such as external force estimation.

This project offers an approach to embed local intelligence to components to monitor their health and performance as well as their interaction with the other components within the system.

As such, companies adopting this approach would be able to switch to servicing contracts (XaaS) because the uptime and quality can be guaranteed through continuous monitoring of KPIs such as energy efficiency, component loading, transmission errors, etc. and generate recurrent income rather than limit aftersales activities. Moreover, they would know how the products are integrated into a machine design. This provides insights in the customers’ needs and an improved customer-supplier relationship. It allows the component supplier to approach the customer with a stronger value proposition and customers trust in the tailored products. And lastly, the amount of generated information can be fed back to the design process as it provides knowledge for next generation products and component design.

The main target groups are the machine and vehicle OEMs and their component suppliers, more specifically component suppliers who build mechanical transmissions or electrical actuators and machine builders who integrate them in a larger system.

The project has originated from the small validation cases of the SBO project MoForM. Companies that are interested to join the ICON-project (Interdisciplinair Coöperatief Onderzoek – Interdisciplinary Cooperative Research) will be asked to specify a case. Based on the concrete cases, the research challenges and project scoping is done to ensure that the project outcome for each partner is a ‘smart’ version of the subsystem of their choice. 


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