Priority-based replenishment policy for robotic dispensing in central fill pharmacy systems: a simulation-based study.

In recent years, companies that operate pharmacy store chains have adopted centralized and automated fulfillment systems, which are called Central Fill Pharmacy Systems (CFPS). The Robotic Dispensing System (RDS) plays a crucial role by automatically storing, counting, and dispensing various medication pills to enable CFPS to fulfill high-volume prescriptions safely and efficiently. Although the RDS is highly automated by robots and software, medication pills in the RDS should still be replenished by operators in a timely manner to prevent the shortage of medication pills that causes huge delays in prescription fulfillment. Because the complex dynamics of the CFPS and manned operations are closely associated with the RDS replenishment process, there is a need for systematic approaches to developing a proper replenishment control policy. This study proposes an improved priority-based replenishment policy, which is able to generate a real-time replenishment sequence for the RDS. In particular, the policy is based on a novel criticality function calculating the refilling urgency for a canister and corresponding dispenser, which takes the inventory level and consumption rates of medication pills into account. A 3D discrete-event simulation is developed to emulate the RDS operations in the CFPS to evaluate the proposed policy based on various measurements numerically. The numerical experiment shows that the proposed priority-based replenishment policy can be easily implemented to enhance the RDS replenishment process by preventing over 90% of machine inventory shortages and saving nearly 80% product fulfillment delays.