Distributed or centralized? A novel supply chain configuration of additively manufactured biomedical implants for southeastern US States

Abstract The fabrication of biomedical devices close to hospitals using Additive Manufacturing (AM) technology has been garnering a lot of attention due to the many potential benefits it provides. Unlike biomedical devices fabricated via Traditional Manufacturing (TM), usually available from suppliers out of the immediate region, biomedical implants manufactured through AM enables surgeons to receive more customized, sophisticated, and patient-specific parts on-demand with faster response, lower inventory level, and reduced delivery costs. However, the AM deployment approach which determines how close the manufacturing point is to the hospitals has a huge impact on the supply chain, and influences the amount of these benefits reaped by the patient, hospitals, and also the AM providers. The choice of deployment approach (central, distributed, or hybrid) remains an open question requiring careful investigation due to the relatively high AM machine and personnel costs, as well as uncertainties in the future. This study proposes a Continuous Approximation (CA) model that quantifies the supply chain network cost associated with AM-produced biomedical implants. We present an optimization algorithm that calculates the locations of the AM machines and the hospitals that they serve (otherwise known as the AM facility’s influence area), the quantity of raw materials to be kept in inventory at a central raw material warehouse (CRW), and the number of distributed AM facilities to minimize the total network cost and achieve a satisfactory patient satisfaction. We apply the cost model to a real-world case study that focuses on the use of biomedical implants in hospitals in 12 states of southeastern USA. Moreover, to demonstrate the effect of different parameters affecting the optimal decision, a number of different sensitivity analysis have been conducted.