第398回化学システム工学専攻公開セミナー Process Systems Engineering in an Area of Big Data and AI: Challenges and Opportunities
- 日時
- 2023年10月12日（木）14:15～15:45
- 場所
- 工学部2号館211講義室
| 講演題目 | Process Systems Engineering in an Area of Big Data and AI: Challenges and Opportunities |
|---|---|
| 講演者 | Prof. Marianthi Ierapetrigou Department of Chemical & Biomolecular Engineering Bob and Jane Gore Centennial Chair of Chemical & Biomolecular Engineering University of Delaware |
| 概要 | The data revolution demands the Process Systems Engineering (PSE) community to adapt the methodologies to fully leverage the additional resources for accurate representation of processes and detailed analyses. The approaches can facilitate process development, system analysis, and optimization, supporting goals in areas like sustainability, circular economy, and public health. Process modeling remains a critical PSE tool to describe complex physical processes based on system understanding. With data revolution, there are challenges in incorporating information of different scales, and in the extent of data involvement. To acquire comprehensive process understanding, efficient PSE tools such as sensitivity analysis, feasibility analysis, life cycle assessment (LCA), and technoeconomic analysis (TEA) can be applied for analysis with data from experiments, pilot plants, databases, and/or models. Using the developed models, optimization can be performed to identify optimal conditions of the most important variables identified using sensitivity analysis, while satisfying important operability and product quality constraints. Such in silico optimization results can provide insights to the experimental work, but as model complexity increases, the optimization task becomes computationally demanding. In the implementation of all these tools, data uncertainty is a critical issue and uncertainty quantification (UQ) approaches can be applied to address this issue. In this talk, we will discuss our group’s work towards developing these tools and highlight their application in pharmaceutical advanced manufacturing and towards sustainable chemical production. |
| 世話人 | 杉山 弘和（内線27227） |