국립 부경대학교

Developing an automated system for production of seaweed, oysters, and fish cakes using AI and robots

Professor Suh Jin-Ho

The development of a smart automated production system that applies artificial intelligence (AI) and robots to the field of seafood processing, which is said to be a traditional labor-intensive industry, will be actively promoted. A research consortium (Chief Prof. Suh Jin-Ho · Mechanical System Engineering) centered on Pukyong National University in Busan has been selected for the smart technology development project for distribution of fresh marine products 2021 by the Ministry of Oceans and Fisheries (MOF). The research consortium will be selected for the 'Development Project of Smart Processing Technology for Marine products' of this business, and will receive 12.1 billion won in support for five years until 2025 to start R&D. This consortium is a large-scale research group in which universities such as Pukyong National University, National Fisheries Research & Development Institute, Korea Institute of Robonics & Technology Convergence (KIRO), Korea Institute of Ocean Science & Technology (KIOST) HyunJeon Co., Ltd, KyungHan Co.,Ltd, OPENIN, BK Instruments Inc., universities such as Chonbuk National University, and researchers, suppliers, consumer companies for each development item participate as joint research institutes. Particularly, it is planned to develop a strategic commercialization system by directly participating in the project by demanding companies according to each development item and jointly conducting field empirical experiments on the development results.

The goal of this research project is to develop an automation system for production core processes △such as pretreatment, selection, processing, and packaging for marine products, △an intelligent information-based data management and smart inspection system, and △an autonomous recognition smart process control system especially for seaweed, oysters, and fish cakes. Previously, the pre-processing and manufacturing stages of seafood depended on the skill level of workers, but through this research, it is possible to develop a system that determines the movement and mixing ratio of raw materials and apply an automated system by using atypical raw material data, knowhow data base, and quality data screening. At the same time, in the inspection stage, AI technology is used to develop quality inspection algorithms, quality inspection sensor technology for high-speed processes, and optimal data management and quality inspection platform technology for each product. Accordingly, it is expected that a system that can inspect in real time not only foreign substances in seafood but also radioactive contamination, which is a recent growing concern, will be developed. In addition, in the packaging and sorting stage, a smart process system based on packaging automation process technology for each item, such as laver, oyster, and fish cake, and the optimal movement trajectory algorithm for trays by weight, classification and packaging automation technology will be applied using robots and IoT technology.

연구진

  서진호 교수 suhgang@pknu.ac.kr

  공과대학 필드로보틱스연구실