Following the journey of a new polymer development project from screening via optimisation and onto value delivery, this paper examines how design of experiments, modelling, and functional data tools in JMP can both improve efficiency and enhance outcomes in chemical product and process development.

Based (primarily) around a single project use case, we explore how implementating DOE and associated tools has improved Synthomer's ability to elucidate and understand the complex interactions that drive polymer performance and convert these into value-adding product innovations.