An integrated tool for semi-automatic repair of CFRP laminates and non-destructive quality control

Simone Pio Negri; Giuseppe Lastilla; Maria di Summa; Massimiliano Nitti; Carmelo Antonio Ardito; Vito Renò

doi:10.1117/12.2677382

9 August 2023 An integrated tool for semi-automatic repair of CFRP laminates and non-destructive quality control

Simone Pio Negri, Giuseppe Lastilla, Maria di Summa, Massimiliano Nitti, Carmelo Antonio Ardito, Vito Renò

Proceedings Volume 12621, Multimodal Sensing and Artificial Intelligence: Technologies and Applications III; 126210E (2023) https://doi.org/10.1117/12.2677382
Event: SPIE Optical Metrology, 2023, Munich, Germany

Abstract

Carbon Fiber Reinforced Plastic (CFRP) is an important material in manufacturing, in particular in automotive and aerospace industry. Its relevance is due to its lightness, resistance and rigidity. In particular the lightness/resistance ratio is the property that will give to CFRP a favourable future in more and more applications, especially where the lightness and resistance are essential. On the other end CFRP is expensive and difficult to produce. During the production process of CFRP’s artefacts some defects may occur (e.g. material inclusions or bubbles), making the component not usable. When applicable, CFRP repair process is structured in: defect removal (scarfing), cleaning and patch application. Actually, scarfing is a slow process manually performed by human operators, strongly dependent on the workers’ skills, that generates a lot of toxic nano dusts. The present paper deals with the implementation of a (semi)automatic robotic cell to repair large CFRP aeronautic components. The robotic cell is composed by a collaborative robot equipped by a custom scarfing tool due to the context-specific constraints to be implemented. Under these constraints, the machining got is not as perfect as in a traditional milling process, thus requiring additional quality control and inspection after scarfing takes place. The paper describes the designed scarfing tool, examines the trajectories generated to execute the scarfing and illustrates some preliminary results in terms of accuracy of the shape got by the designed tool.

Conference Presentation

Citation Download Citation

Simone Pio Negri, Giuseppe Lastilla, Maria di Summa, Massimiliano Nitti, Carmelo Antonio Ardito, and Vito Renò "An integrated tool for semi-automatic repair of CFRP laminates and non-destructive quality control", Proc. SPIE 12621, Multimodal Sensing and Artificial Intelligence: Technologies and Applications III, 126210E (9 August 2023); https://doi.org/10.1117/12.2677382

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