Computer aided mixture design with specified property constraints

Advances in chemical product design

The nature of chemical product design problems is diverse and multidisciplinary. It involves many design issues such as project management, market study, product design, process design, and economic analysis for better organizing the product design project and achieving better products. This article provides an overview of chemical product design with a multidisciplinary hierarchical framework including all the design issues and tasks. Each of the design issues and tasks are introduced and discussed, methods and tools are summarized and compared, challenges and perspectives are presented to help the chemical product design researchers on finding more novel, innovative and sustainable products, by the combined effort from academia and industry to develop a systematic generic framework, and tools including product simulator, process simulator, database manager, modeling tool, and templates for design problems.

New Vistas in Chemical Product and Process Design

Design of chemicals-based products is broadly classified into those that are process centered and those that are product centered. In this article, the designs of both classes of products are reviewed from a process systems point of view; developments related to the design of the chemical product, its corresponding process, and its integration are highlighted. Although significant advances have been made in the development of systematic model-based techniques for process design (also for optimization, operation, and control), much work is needed to reach the same level for product design. Timeline diagrams illustrating key contributions in product design, process design, and integrated product-process design are presented. The search for novel, innovative, and sustainable solutions must be matched by consideration of issues related to the multidisciplinary nature of problems, the lack of data needed for model development, solution strategies that incorporate multiscale options, and reliability versus predictive power. The need for an integrated model-experiment-based design approach is discussed together with benefits of employing a systematic computer-aided framework with built-in design templates.