Mixed-integer programming models for simultaneous batching and scheduling in multipurpose batch plants

Modeling and techno-economic analysis of downstream manufacturing process intensification strategies for existing biopharmaceutical facilities

Downstream process (DSP) intensification technologies have the potential to provide faster, more sustainable, and more profitable processes. Nevertheless, the calculation of the possible benefits obtained from the implementation of these technologies is not always evident and usually depends on a particular production scenario. In the present work, we developed a framework for techno-economic feasibility analysis to assess the impact of changes in protein A capture, polishing, and viral filtration on process performance. The simulation used in this analysis is based on fundamental knowledge of the process and incorporates previously developed tools for calculating multi-column chromatography (MCC) and ultrafiltration-diafiltration variables. This framework was used to simulate production scenarios featuring intensified production schedules, increases in feed titers, MCC, integrated batch polishing, and high throughput viral filtration. These process alternatives were compared through key performance indicators that were selected to address specific questions on the suitability of these process intensification strategies in a particular context. Results were presented graphically for decision-makers to easily identify the best process alternatives for a given production scenario. For the conditions proposed in this work, we find that the scheduling practices, and not the unit operation processing times, have the greatest impact on process productivity. For instance, doubling the harvesting frequency resulted in a productivity increase of up to 61 %. Meanwhile, technological intensification strategies like MCC cause the greatest impact on operating costs, reducing cost of goods of the DSP by up to 27 %. Overall, intensification of individual unit operations can yield benefits from a sustainability and cost perspective, but to achieve higher throughputs, it is necessary to have fully intensified DSP and scheduling practices.

Optimization-Based Scheduling for the Process Industries: From Theory to Real-Life Industrial Applications

Scheduling is a major component for the efficient operation of the process industries. Especially in the current competitive globalized market, scheduling is of vital importance to most industries, since profit margins are miniscule. Prof. Sargent was one of the first to acknowledge this. His breakthrough contributions paved the way to other researchers to develop optimization-based methods that can address a plethora of process scheduling problems. Despite the plethora of works published by the scientific community, the practical implementation of optimization-based scheduling in industrial real-life applications is limited. In most industries, the optimization of production scheduling is seen as an extremely complex task and most schedulers prefer the use of a simulation-based software or manual decision, which result to suboptimal solutions. This work presents a comprehensive review of the theoretical concepts that emerged in the last 30 years. Moreover, an overview of the contributions that address real-life industrial case studies of process scheduling is illustrated. Finally, the major reasons that impede the application of optimization-based scheduling are critically analyzed and possible remedies are discussed.