A key challenge for the future, biorefineries are challenged by supply and demand variability. Indeed, biorefineries structures are traditionally centralised, with static processes where inputs and outputs are strictly defined and cannot be adapted (regarding quantity, quality, purity, etc.). This paper proposes a new approach where the process is decentralised to face the challenge of the agility of biomass processing. It leads defining virtual biorefineries, in which the stakeholders (farmers, industrials) are involved in a collaborative process, where they provide operation units as services and where existing plants and equipment are reused. The design of this collaborative biomass processing should also take into account functional and non-functional factors, such as the socioeconomic context, weather conditions, etc. supported by information and communication technologies. Therefore, the biomass treatment process could be quickly designed and adapted, according to the detected changes of the ecosystem
Processing biomass requires four major steps (pretreatment, fermentation, separation and purification) achieved by dedicated plants called biorefineries. These highly specialized structures cannot cope with the high variability of the whole biomass supply chain. Thus, providing agility to biorefineries is a key challenge to foster biomass processing. The goal is to design a virtual biorefinery as a collective network supported by the servitization of unit operations and the reuse of existing devices. In this regard, the first step described in this paper aims to gather and organize knowledge about a given local area (stakeholders, services) and the existing transformation process operations (inputs, outputs) through a framework. To this end, two metamodels are proposed: one to collect and structure the required information about the local area; one to organize the knowledge about the transformation processes. Their use is illustrated by a use case provided by a municipalities community located in South-West France.
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