As industry aims to improve its sustainability performance, it really represents just one more variable in what has long been a compelling multivariable, model-based optimization problem. But the accuracy of first-principle models can be tricky to maintain, what with the changing state of equipment over time, changing weather conditions and variations in raw material inputs. Might AI be just the tool to tweak models on fly, such that productivity, profitability and sustainability can all be balanced in concert?  Chemical Processing contributor Sean Ottewell takes a stab at the state of the art in this issue's lead article.

  — Keith Larson, Market Leader