Intelligent process systems engineering (iPSE) in the era of artificial intelligence and process electrification

Le résumé fourni par la source

The growing complexity, integration, and sustainability demands of chemical processes increasingly call for a systems perspective. Process Systems Engineering (PSE) is a discipline that provides such a framework at the core of chemical engineering, enabling the understanding, design, and operation of chemical systems across scales. In the age of artificial intelligence (AI), PSE is evolving from a primarily modeling- and optimization-driven discipline toward a more adaptive framework that integrates data, models, algorithms, and human expertise. This shift is especially consequential for process electrification, where chemical processes must interact with variable renewable energy supplies, emerging electrified unit operations, and new forms of cross-sectoral and cross-scale uncertainty. Electrification is therefore more than a decarbonization pathway; it redefines the systems challenges of chemical engineering through process redesign and intensification. This Perspective frames this transition as the rise of intelligent PSE ( i PSE), an expanded methodological form of PSE that combines mechanistic models, data-driven generative methods, closed-loop optimization, and human intelligence to support coordinated decision-making across discovery, design, integration, and operation. The near-term challenge is therefore not to diminish the role of core PSE and human judgment, but to embed them within more adaptive, AI-enabled decision architectures for the future of electrified chemical processes.

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