Replenishment Process Simulation and Analysis for Pharmacy Robotic Dispensing Systems

Nieqing Cao, Austin Marcus, Sang Won Yoon, Soongeol Kwon

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The objective of this paper is to exploit a discrete-event simulation model as a tool for analyzing the replenishment process for a large-scale Robotic Dispensing System (RDS) with an actual pharmacy-based dataset. The RDS is a critical automated system to realize pharmacy automation in the Central Fill Pharmacy System (CFPS), which is a prescription filling system to process large volumes of prescription demand. To guarantee the high productivity of the RDS, the replenishment process should be optimized under limited resources to ameliorate the detrimental impact of errors, which are caused by the shortage of pills in the dispenser by operational replenishment delays. Although the significance of replenishment process optimization has been recognized, there is still little research on it due to complex interactions between automated systems and operators in analyzing the replenishment process. To overcome these challenges and deal with the urgent need for modeling the replenishment process, a simulation-based approach is used to uniquely design the replenishment process with manual operations, including machine-to-machine, human-to-machine, and human-to-human interactions by reflecting real-world practice. This paper aims to develop simulation models for accurately capturing the replenishment process integrated with the RDS operations. Multiple performance metrics are used to analyze system performance, and proper priority and staff working strategies are discussed to improve the system performance. Insights for practitioners are provided to design and manage efficient replenishment operations under limited resources.

Original languageEnglish
Title of host publicationIISE Annual Conference and Expo 2022
EditorsK. Ellis, W. Ferrell, J. Knapp
PublisherInstitute of Industrial and Systems Engineers, IISE
ISBN (Electronic)9781713858072
Publication statusPublished - 2022
EventIISE Annual Conference and Expo 2022 - Seattle, United States
Duration: 2022 May 212022 May 24

Publication series

NameIISE Annual Conference and Expo 2022


ConferenceIISE Annual Conference and Expo 2022
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 2022 IISE Annual Conference and Expo 2022. All rights reserved.

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering


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