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AI-powered concept, aiming to revolutionize gelcoat application by using advanced video detection to prevent blockages at the spray tip in real-time


TRYGONS is a privately owned and innovative composite parts manufacturer, mainly active in the marine and automotive sectors. Leveraging its internal Research & Development capabilities, the company employs cutting-edge technologies to design and fabricate intricate reinforced parts of medium to large sizes, primarily catering to high production volumes.

The organization offers a comprehensive range of services, including composite part manufacturing, collaborative product development, encompassing initial conceptualization, detailed design, and rigorous testing, as well as material and product certification. TRYGONS ensures end-to-end support, from production to continuous improvement throughout the product’s lifecycle.

Recently, the company has initiated the use of AI for the improvement of its manufacturing processes. We are particularly interested in the digitization of our processes, for reasons of sustainability, flexibility, and overall efficiency.


The challenge we aim to address revolves around automating the gelcoat application process. The primary obstacle to automating this process lies in the frequent occurrence of spray tip blockages, which significantly impede the consistency of the layup thickness and overall product quality. A blockage of the spray tip leads to the production of heavily defective items, necessitating extensive repairs or direct scrapping.

Spray blockage represents a prevalent issue encountered within the Glass Fiber Reinforced Plastics (GFRP) sector, particularly in gelcoat application, a widely adopted manufacturing process for producing large composite parts like midsize to large yachts, automobile cabins, and wind blades.

For manufacturing companies, these blockages have direct implications, including increased production of defective products, escalated repair costs, material wastage, amplified environmental impact, and reduced operational efficiency.

Presently, the responsibility of assessing the correctness of the spraying pattern lies with the operator initiating the painting process, relying on their experience to evaluate the test shots. Errors in the spraying pattern are indiscernible during the painting process, with only blockages exceeding 90% detectable through a pump speed sensor, as substantial blockages lead to alterations in the gelcoat machine’s pumping speed. Unfortunately, by that point, irreversible damage has typically occurred.

Our motivation to address this problem encompasses several facets. Primarily, a significant economic impact is expected for manufacturers within our sector upon implementing this solution. Concurrently, it offers an avenue to reduce the environmental footprint by minimizing material waste. Lastly, it represents a substantial leap toward automation, particularly for medium-sized industries operating within the sector, as the gelcoat application process traditionally relies heavily on manual labour.


This Challenge is not eligible for the InnoBuyer programme co-creation phase.