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

Area of Science:

• Operations Research
• Supply Chain Management
• Pharmacy Automation

Background:

• Central Fill Pharmacy Systems (CFPS) utilize Robotic Dispensing Systems (RDS) for efficient, high-volume prescription fulfillment.
• Timely replenishment of medication pills in RDS is critical to prevent shortages and prescription delays.
• Existing replenishment processes lack systematic approaches due to complex system dynamics.

Purpose of the Study:

• To develop an improved, priority-based replenishment policy for RDS within CFPS.
• To address the need for systematic control policies in automated pharmacy fulfillment.
• To enhance the efficiency and reliability of medication replenishment in automated systems.

Main Methods:

• Development of a novel criticality function to assess refilling urgency for RDS canisters.
• Implementation of a priority-based replenishment policy using inventory levels and consumption rates.
• Utilizing 3D discrete-event simulation to emulate RDS operations and evaluate the policy.

Main Results:

• The proposed policy effectively generates real-time replenishment sequences for RDS.
• Numerical experiments demonstrated prevention of over 90% of machine inventory shortages.
• Significant savings of nearly 80% in product fulfillment delays were achieved.

Conclusions:

• The priority-based replenishment policy offers a practical and effective solution for RDS.
• The policy enhances RDS replenishment processes, improving overall CFPS efficiency.
• This approach is easily implementable and significantly reduces operational disruptions.