a b s t r a c tThis work addresses the optimal planning and campaign scheduling of biopharmaceutical manufacturing processes, considering multiple operational characteristics, such as the campaign schedule of batch and/or continuous process steps, multiple intermediate deliveries, sequence dependent changeovers operations, product storage restricted to shelf-life limitations, and the track-control of the production/campaign lots due to regulatory policies. A new mixed integer linear programing (MILP) model, based on a Resource Task Network (RTN) continuous time single-grid formulation, is developed to comprise the integration of all these features. The performance of the model features is discussed with the resolution of a set of industrial problems with different data sets and process layouts, demonstrating the wide application of the proposed formulation. It is also performed a comparison with a related literature model, showing the advantages of the continuous-time approach and the generality of our model for the optimal production management of biopharmaceutical processes.

A simulation-optimization approach to integrate process design and planning decisions under technical and market uncertainties: a case from the chemical-pharmaceutical industry.Computers and Chemical Engineering

This work deals with the optimal short-term scheduling of general multipurpose batch plants, considering multiple operational characteristics such as sequence-dependent changeovers, temporary storage in the processing units, lots blending, and material flows traceability. A novel Mixed Integer Linear Programming (MILP) discrete-time formulation based on the State-Task Network (STN) is proposed, with new types of constraints for modeling changeovers and storage. We also propose some model extensions for addressing changeovers start; nonpreemptive lots; lots start and sizes; alternative task-unit and task-unitlayout assignments. Computational tests have shown that the proposed model is more effective than a similar model based on the Resource-Task Network (RTN).