(144g) Evaluation of Sustainability Metrics During Early Process Design Stages Using Statistical Methods

Process design is a complex activity which requires expertise from a variety of disciplines. Previously there had been many chemical plants which were specially designed for maximizing economical efficiency, however nowadays new regulations oblige more responsibility to the industry in terms of Environmental, Health, and Safety issues. This emphasizes the importance of EHS calculation to be considered beside economical estimates as early during process design as possible. One of the most promising ways for introducing these sustainability metrics into chemical process design is through an index. The main reason is the simplicity of index-based approaches which allocates a number to each sustainability category and makes it attractive for the industry use. Nevertheless, when aggregating Environmental, Health, and Safety scores to decide about the most sustainable process option; index-based approaches typically suffer from subjective scaling and weighting of factors. This study focuses on a freshly introduced approach for comparing process routes during early process design using a statistical methodology called ?Principal Component Analysis? (PCA). Two case studies namely the methyl-methacrylate (MMA) and the 4-(2-mthoxyethyl)-phenol production processes are considered to demonstrate the robustness of the evaluation procedure. Furthermore, since PCA is highly dependent on the number of process routes and the number of effect categories, a sensitivity analysis is performed to detect the applicability limits of the method in extreme cases of a high-dimension in effect categories and small number of process alternatives.