Tray dryer design under feed uncertainty: A case study on a nutraceutical beverage. (March 2023)

• Record Type: Journal Article
• Authors: Espinoza-Vasquez, Alexander P.; Galatro, Daniela; Manzano, Patricia; Choez-Guaranda, Ivan; Cevallos, Juan M.; Salas, Santiago D.; Gonzalez, Yris
• Is Part Of: Journal of food engineering. Volume 341(2023)
• Publication Date: 2023-03
• Subjects: Tray dryer -- Sizing -- Feed uncertainty -- Nutraceutical beverage; Food industry and trade -- Periodicals; Food -- Analysis -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Analyse -- Périodiques; Aliments -- Recherche -- Périodiques; 664.005
• DOI: 10.1016/j.jfoodeng.2022.111341
• Languages: English
• ISSNs: 0260-8774

Abstract

Abstract: Feed characterization in the food industry has significant variability due to the complexity of its composition. This variability influences the product quality and the process equipment sizing. Uncertainty analyses permit to assess such variations when designing food processing equipment. Because standalone codes are built to run the system's simulation, computational solutions are limited to specific feed characterizations. In this work, a framework for sizing equipment including feedstock uncertainty in food engineering applications is proposed. A tray dryer which dries a mixture of plants to produce a nutraceutical beverage is evaluated. This approach integrates a commercial process simulation software to generate physicochemical properties of complex compounds and a scientific computing environment to evaluate uncertainty in the feed stream. For the case study, considerable variability was observed in terms of the dryer volume (6.68–29.95%), energy consumption (5.72–25.43%), and CAPEX (3.52%–14.00%) when compared to the base case. The integrated platform provides a reliable operational envelope that can be used for sizing, monitoring, and optimization purposes and it can be adapted to other unit operations in the food industry. Highlights: Feed characterization in the food industry has significant variability. Variability influences the product quality and process equipment sizing. Uncertainty analyses are useful to assess variability in food characterization. A framework for sizing equipment including feedstock uncertainty is proposed. The integrated platform provides a reliable operational envelope.