Production Optimization considering Processing Time Uncertainty and Cell Viability in Tissue Engineered Medical Products Manufacturing

Abstract

Tissue-engineered medical products (TEMPs) are gaining significant attention for their potential to address organ shortages and improve public health. However, as the field grows, optimizing production to achieve appropriate biofunctionality (e.g., high cell viability) remains a critical challenge. Each TEMP has its unique process plan, precedence requirements, and critical constraints on cell viability, which dictate its overall success. The waiting time spent by a work-in-progress TEMP is a significant factor in dictating viability of cells at each production stage and in the final product. In order to achieve a better control while manufacturing TEMPs and maintain the desired level of cell viability, we investigated the problem of assigning and scheduling of operations required by these products on different machines. This problem is akin to a flexible job-shop scheduling problem. We present a mixed-integer linear programming (MILP) model formulation for assigning and scheduling TEMP operations in a deterministic environment that ensures both the stage-wise sequencing, and also, machine-wise sequencing of the operations of an order, while ensuring the desired viability of cells by controlling the waiting time of each order. The outcome of the model gives insights into planning the capacity of different facilities as well as their effective utilization by appropriately assigning orders to these facilities. We also extend our methodology to a stochastic environment where the processing times follow different distributions.