The most-used method for essential oil extraction is steam distillation due to its simplicity and low investment requirements. Due to the importance of this extractive method, technological updates represent an immense opportunity for improving this component of essential oil production. In order to evaluate how such updates have been applied to essential oil production, in this study, we conducted a technological prospection. A total of 490 patent documents were retrieved and indicators were evaluated, which included publication trends, main applicants and inventors of the prospected technologies, main depositing countries and potential markets for the inventions, and classification codes assigned to the patent documents. The results indicated that steam distillation is used by different sectors and that it is an important industrial process that has been growing in recent years. In terms of associated technological updates, we observed that only some patent documents referred to the application of technological updates, indicating that processes could still be investigated and incorporated into the technology. Thus, the advancement of studies to improve this process could contribute even more to its visible growth, increasing its application potential and process yield.
Introduction: Digital twins are becoming a powerful tool to enhance industrial processes worldwide. This paper proposes a model for the creation of industrial processes’ digital twins using a steam distillation process for essential oil extraction as a case study. Case Description: A grey box modeling is suggested combining a machine learning based model with physical modeling to improve the process. Real time simulation and a hybrid control strategy are used, linked to reinforcement learning and proportional integral derivative control, focusing on the yield increase and optimization. Computer Vision and Artificial Intelligence enhancements were suggested. Discussion and Evaluation: Digital twins, in combination with Artificial Intelligence can be of great help to support companies with the decision-making challenges. Furthermore, some benefits that Artificial Intelligence can bring to the process were enlightened. Computer Vision approaches were also discussed. Conclusions: A creation method is elaborated to support other applications of digital twins in industrial processes in the future. In order to apply it to different processes, generalization capabilities must be proved.
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