With the rapid advancement of Industry 4.0 technologies, intelligent manufacturing and big data platforms are profoundly transforming the production models of the traditional edible oil industry. The edible oil production process involves multiple complex unit operations such as refining, decolorization, and deodorization, which impose high requirements on process control and product quality monitoring. This paper presents a systematic review of key technological advances in the field of intelligent manufacturing of edible oil, establishing a comprehensive technical framework encompassing four dimensions: smart sensing, artificial intelligence applications, IoT communication, and big data platforms. The review begins by analyzing the global background and driving factors for digital transformation in the edible oil industry. It then focuses on the current state of research in online detection and smart sensing technologies, followed by a review of AI applications in process parameter optimization, equipment predictive maintenance, and quality prediction. Based on this, the development trends of IoT communication networks and identification and resolution technologies are examined. Finally, the role of big data platforms in traceability and decision support is discussed, along with future research directions. This review provides a theoretical reference for the intelligent upgrading of the edible oil industry.
Jiang et al. (Thu,) studied this question.
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