Active image-based feeding of small parts using aerodynamic chicanes

• Applicant: Professorin Dr.-Ing. Annika Raatz
• Subject Area: Production Automation and Assembly Technology
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 528450120

Modern production systems are exposed to a variety of requirements with regard to variant flexibility and planning uncertainties, as well as an increased cost pressure. The feeding technology as a decisive component of automated assembly systems must meet these requirements. The aim of this project is therefore to research methods for an active, image-based feeding of components using aerodynamic orientation modules. The active method allows for high feeding rates, while the use of image processing and aerodynamic actuators provides a high degree of flexibility with regard to the component shape. Within the scope of the proposed project, the development of a simulation model for planning the orientation process and the training of the image processing with the aid of CAD data is intended to drastically reduce set-up time and thus significantly increase the flexibility and plannability of the feeding system. Due to the use of aerodynamic chicanes, no changes to the hardware will be necessary to convert the system, which in addition to increased flexibility also contributes to resource conservation and thereby increased sustainability. There is a concrete need for research in the development of a simulation model that can calculate stable component positions and derive the necessary orientation steps. Likewise, the number, type and position of the aerodynamic chicanes must be derived from the component spectrum to be defined, so that maximum flexibility on the hardware side is guaranteed. In order to enable the image processing to be trained offline with the aid of CAD data, a robust method for generating the necessary training data sets in the form of rendered images must also be developed. A particular challenge is to close the domain gap between the artificially generated images of the workpieces and those captured by the real image processing. Finally, the researched methods are combined in a functional model that meets the requirements of modern production systems. The methods and functional model will be evaluated with the help of previously derived validation workpieces, based on defined criteria.

• DFG Programme: Research Grants