This paper provides a perspective on model-data based solution approaches for chemical product-process design, which consists of finding the identity of the candidate chemical product, designing the process that can sustainably manufacture it and verifying the performance of the product during application. The chemical product tree is potentially very large and a wide range of options exist for selecting the product to make, the raw material to use as well as the processing route to employ. It is shown that systematic computer-aided methods and tools integrated within a model-data based design framework can manage the complexity associated with product-process problems very efficiently. Three specific computer-aided tools (ICAS, Sustain-Pro and VPPDLab) have been presented and their applications to product-process design, highlighted.
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