Process Systems Decision Tool for Flow Chemistry Applications

适用于流动化学应用的过程系统决策工具

• 批准号: 2459910
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2459910
• 关键词: Process; Systems; Decision; Tool; Flow

Underlying Scientific Challenge/Scientific Approach: Multi criteria, (transparent) decision making (MCDM) tree ensembles are a challenge to model and set up in a way that subjective decisions are by-and-large eliminated. Particularly, the development of a quantitative tool to take into account multiple discrete criteria, such as Safety, Economics, Time to Registration Sample, Environmental Impact, Toxicology, process safety; economical factors including investment, raw-material, and operational cost; impact on development effort; yield and selectivity; Sustainability is hampered by the apparent dimensional incompatibility of these criteria. Approach: Based on a Pareto efficiency approach we will seek to identify a set of optimal synthesis/process design solutions (Pareto front) that allows for efficient, comprehensive, and unbiased trade-off analysis. This will be important for the analysis of whether to use batch processing or Flow Chemistry in agrochemicals synthesis R&D up to registration scale.Optimal design solutions and decisions can be found based on various criteria that may or may not be quantitative and objective. For example, different stakeholders will subjectively weigh (value) criteria differently and thus contribute to a set of Pareto fronts. Various decision tools and algorithms in the family of MCDM and MADM (multi-attribute decision making) will be implemented and compared to develop a user friendly and transparent decision making tool. This tool will aid in making objective AND trusted decisions as the outcome can be tracked back through the various decision nodes. Initially a semi-quantitative approach will be taken but efforts will be made to identify figures of merit (e.g. reducing most criteria to cost factors) to move towards complete quantification of decisions. It is recognized that process scale will have a significant effect on the performance of such a tool and it is envisaged that two methodologies will need to be developed: one at lab scale and one at production scale. Time permitting the methodology will be expanded to synthesis route selection.Deliverables: A PhD thesis in which the student start by developing an onthology (hierarchical, decision-tree type approach taking into account the various distinct optimization criteria) based on BASF's agro-needs. A Pareto front based methodology (MCDM) to make and represent transparent decision making process for effective (agro) chemical synthesis and production.

潜在的科学挑战/科学方法：多标准，（透明）决策（MCDM）树集成是一个挑战，建模和建立的方式，主观决策是由和大部分消除。特别是，开发定量工具以考虑多个离散标准，例如安全性、经济性、注册样品时间、环境影响、毒理学、工艺安全性;经济因素，包括投资、原材料和运营成本;对开发工作的影响;产量和选择性;可持续性受到这些标准明显尺寸不兼容性的阻碍。方法：基于帕累托效率的方法，我们将寻求确定一组最佳的合成/工艺设计解决方案（帕累托前），允许有效的，全面的，公正的权衡分析。这对于分析在注册规模的农药合成研发中是否使用批量处理或流动化学非常重要。可以根据各种标准找到最佳设计解决方案和决策，这些标准可能是定量的，也可能不是客观的。例如，不同的利益相关者主观上会对标准进行不同的权衡（价值），从而对一组帕累托前沿做出贡献。各种决策工具和算法在家庭的MCDM和MADM（多属性决策）将实施和比较，以开发一个用户友好和透明的决策工具。该工具将有助于做出客观和可信的决策，因为结果可以通过各个决策节点进行追溯。最初将采取半定量的办法，但将努力确定优值（例如将大多数标准简化为成本因素），以逐步实现决定的完全量化。人们认识到，工艺规模将对这种工具的性能产生重大影响，预计需要开发两种方法：一种是实验室规模，一种是生产规模。时间允许的话，该方法将扩展到合成路线的选择上。可行性：一个博士论文，其中学生根据巴斯夫的农业需求开发一个本体论（考虑到各种不同的优化标准的分层决策树型方法）。基于帕累托前沿的方法（MCDM），用于制定和代表有效（农业）化学品合成和生产的透明决策过程。