4.7 Article

Multi-objective optimization of a clean, high-efficiency synthesis process of methyl-ethyl-ketone oxime from ammoximation

期刊

JOURNAL OF CLEANER PRODUCTION
卷 315, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2021.128176

关键词

Methyl-ethyl-ketone oxime; Reaction kinetics; Multi-objective optimization; Exergy; Total annual cost

资金

  1. National Natural Science Foundation of China [21776145, 21808117]

向作者/读者索取更多资源

The study investigates the ammoximation of methyl ethyl ketone to methyl ethyl ketone oxime, with an economic evaluation resulting in a minimum annual total cost of 2.41 x 107 USD/yr. Through multi-objective optimization, the total annual cost increased to 2.55 x 107 USD/yr while reducing the exergy loss rate to 64%.
The ammoximation of ketones is an important chemical reaction, as oximes have a wide range of industrial applications. In this study, the process of preparing methyl ethyl ketone oxime by ammoximation of methyl ethyl ketone was studied. The modeling of the reaction unit was based on the kinetic data, and the reaction conditions were analyzed. Based on the total annual cost, an economic evaluation of the process was carried out, and a sequential iterative optimization algorithm integrating the reaction conditions was used to complete the process optimization. The minimum annual total cost was 2.41 x 107 USD/yr. The exergy of methyl ethyl ketone ammoximation to methyl ethyl ketone oxime process was analyzed, and the unit with the largest exergy loss was determined. The exergy loss rate was 65% for the minimum annual total cost. Considering exergy and annual total cost as the two optimization objectives, the process was comprehensively optimized by a multi-objective optimization algorithm. The annual total cost after multi-objective optimization was 2.55 x 107 USD/yr, which is 5.8% higher than minimum total annual cost, and the exergy loss rate was 64%, which is 1.54% lower than maximum exergy-loss rate. Compared with single-objective optimization, multi-objective optimization has a better comprehensive performance.

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