3D food printing: monitoring, quality assessment and adaption with machine vision

Samenvatting (Engelstalig)

The food industry is always looking for innovative ways to make food products that is safe, healthy, and delicious, and good for the environment. Lately, more consumers are interested in personalized foods which can be tailored to their specific tastes, textures, and nutritional needs. 3D printing stands out as a promising method to produce personalized foods. This PhD thesis focuses on creating methods to monitor, assess product quality, and adapt the 3D food printing process to achieve the “first-time-right” production goal. By using machine vision techniques and predictive models, technologies developed in this thesis improve the current performance of 3D food printing. With efficient 3D food printers, production of personalized food becomes more commercially viable and ready for the consumer market.