Production scheduling for the reconfigurable modular pharmaceutical manufacturing processes

Abstract

The novel reconfigurable modular production system is expected to be the next breakthrough in pharmaceutical manufacturing. In these systems, the target product can be manipulated by changing the modules active on a certain production line, but optimal scheduling is a challenging problem because the on-demand operation of the modular system involves sequence-dependent changeover time/cost and competition of limited modules. Based on the characteristics of the modular production system, this work proposes a multi-stage hybrid discrete/continuous-time scheduling framework to fully utilize the advantages of the two formulations. A discrete-time lot-sizing MILP model is first solved to determine the solution structure, and then an information mapping algorithm extracts the necessary information from the discrete-time solution. Finally, a continuous-time LP model is constructed and solved based on the extracted information. The proposed model shows decent results in its application to a reconfigurable modular continuous production system with seven API products.