Nippon Shokubai and NTT Communications (NTT Com) announced on February 18 that they have successfully automated a chemical manufacturing process, which has been considered difficult to achieve until now, using AI. This is expected to reduce the burden on operators and make it more efficient to transfer skills. In this initiative, AI was trained to learn the operation data of the continuous distillation process, the operation history of the operators, and operation know-how. By incorporating a trained AI model into NTT Com’s “AI Autopilot System,” automated operation of the continuous distillation process, whose conditions change in complex ways, was achieved. A wealth of knowledge and experience is essential to operate a chemical manufacturing plant. A wealth of knowledge and experience is required to operate a plant that manufactures chemicals, whose conditions such as temperature, pressure, and concentration are constantly changing, and automated operation has been considered difficult. In particular, the continuous distillation process, which increases the purity of chemicals, is easily affected by the composition of the reaction liquid, the amount of recycled distillate that flows out, and weather, and skilled operators had to operate it manually at all times with high concentration.
また、安定操業の維持には技能伝承が重要な課題であり、オペレーターの育成には多くの時間を要します。連続蒸留プロセスにおける温度制御の精度は、単位時間当 たりの廃液量で評価されます。蒸留液は連続蒸留工程から流出するだけでなく、断続的に再利用されるため、レベル計で測定される理想的な蒸留液面(理想液面)は常に変化しています。
しかし、学習させたAIモデルを組み込むことで、レベル計の実測値と理想液面との誤差は、手動操作時の平均2.38%からAI操作時の平均2.06%に低減。これは、熟練オペレータによる手動操作と比較して13.5%の改善に相当し、手動操作と同等以上の操作品質が得られることを確認しました。
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日本触媒 今後、この取り組みを他の工場にも拡大し、DXによる変革を推進していきます。 NTTコム will continue to expand the system’s functions to realize automated operation of plants where manual operation remains, such as batch plants and small-lot, multi-product production plants. In addition, the company plans to expand this technology beyond chemical plants to a wide range of industrial fields, contributing to solving issues such as labor shortages.
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