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Large-scale industrial production processes face increasingly tight environmental constraints, which can be addressed through costly but relatively simple end-of-pipe solutions, or through cheaper but more subtle pollution prevention approaches. Achieving the process improvements necessary for pollution prevention is challenging due to the inherent complexity and unpredictability of several types of processes found in the food processing, pharmaceuticals, biotechnology, and specialty chemical industries. We propose an iterative procedure to achieve process improvements through model-based process redesign. This procedure is based on successive convex approximations of the process performance model, where product flows and process settings are optimized for a given configuration and the solution and dual variables of this optimization problem are used to update the process configuration following a greedy capacity reallocation procedure. We implemented this procedure over a five-year period at Cerestar, a major European producer of starch products, which led to a dramatic simplification in process configuration. Reduced energy and water consumption led to an estimated $3 million annual cost savings. Moreover, the reduction in environmental impacts allowed Cerestar to maintain current production levels without investing $100 million in additional wastewater treatment capacity to comply with new environmental constraints.

Achieving Environmental and Productivity Improvements Through Model-Based Process Redesign