Abstract
Cassava flour producers express a need for assistance in designing and operating more energy-efficient and thus more profitable units. A process simulator would be an effective tool to meet this demand. However, no existing tool allows to simulate this process. More generally, no commercial multi-product, multi-operations simulator is available for food matrices. This is mainly due to the lack of process models and generic properties. This work contributes to the development of multi-products, multi-operations, multi-technologies agri-food process simulators, based on a concrete case: cassava flour. The simulator developed takes into account the local context in which the simulated process takes place.The models needed to simulate cassava flour processing were first defined. Multi-products first-principal models were selected from the literature and adapted to cassava for the dehydration operations (filtration-consolidation and diffusive-convective drying). They are based on models of product properties, some of which are essential but unavailable in the literature for cassava (e.g. diffusivity, specific filtration resistance). In order to be as generic as possible, these property models were identified on measurements made under multiple experimental conditions and on multiple cassava forms (origin, geometry, level of processing). The other models (costs, manual and fragmentation operations) were deduced from data collected or measured in the field.A process simulator at the scale of the processing unit was developed. Aiming to be accessible to multiple actors, it was developed in Python, an open source language. In addition, it is intended to be a functional foundation, into which elements (operations, products, criteria) can be easily added. To this end, it has been developed according to a modular approach used in commercial chemical engineering software such as ProSimPlus, AspenPlus.The models chosen, developed and fitted during this thesis have been implemented in this simulator. The costs, energy consumption and the state of the flows (products, utilities, coproducts) can thus be predicted at each stage of the cassava flour production process, depending on the design and settings of the operations.