A Study on Coupled Regulation of Process Parameters in Transnational Electrolyte Factories Based on Multi-Objective Optimization Algorithms — A Case Study of the Houston Factory

Abstract

Transnational electrolyte factories face intractable challenges, including divergent regional environmental regulations, high process adaptation costs, and the intricate trade-off among production capacity, energy consumption, and volatile organic compound (VOC) emissions. Taking a 200,000-ton-per-year electrolyte factory in Houston as the research object, this study proposes a novel multi-objective optimization model embedded with regional compliance factors and develops an improved Non-dominated Sorting Genetic Algorithm III (NSGA-III) for the coupled regulation of key process parameters (reaction temperature, stirring rate, vacuum degree, and reflux ratio). Systematic validation via Aspen Plus full-process simulation, ANSYS Fluent flow field optimization, and industrial-scale empirical tests shows that the optimized parameter scheme reduces unit product energy consumption by 22.7%, cuts VOC emissions to 0.026 kg/h (complying with both US EPA and EU REACH standards), and boosts production capacity by 15.2%, with a model prediction error ≤3.5%. A standardized operating procedure (SOP) for transnational process adaptation is formulated, shortening compliance audit preparation time from 48 hours to 15 minutes. This research fills the technical gap in synergistic optimization of compliance and efficiency for transnational electrolyte production, providing a replicable theoretical and engineering paradigm for global electrolyte enterprises’ overseas layout, with substantial technological innovation value and economic-environmental benefits.