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Optimization in Pharmacy Automation System

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Systems Collaboration and Integration (ICPR1 2021)

Part of the book series: Automation, Collaboration, & E-Services ((ACES,volume 14))

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Abstract

Prescription demand and the complexity of patients’ pharmaceutical protocols have significantly increased during the last decade. To achieve greater effectiveness of the overall prescription fulfillment process, the development and deployment of modern pharmacy automation systems, known as mail order pharmacy (MOP) or central fill pharmacy (CFP) systems, have been accelerated in recent years. Such advanced systems adopted automated robotic dispensing systems (RDS) and collation systems that can prepare more than tens of thousands of prescriptions per day. Designing and operating large-scale pharmacy systems are very complicated and expensive to ensure their expected throughputs and patient safety consideration. Therefore, a thorough system evaluation and investigation for potential improvement regarding the performance and operational efficiency should be conducted. This chapter aims to provide the detailed working mechanisms of pharmacy automation systems and introduce five important optimization problems in pharmacy automation, which include the RDS planogram design optimization, RDS replenishment optimization, collation system analysis, order scheduling optimization, and pharmacy database mining. To better demonstrate the optimization modeling in the context of pharmacy automation, a case study of the RDS replenishment process optimization based on modeling and simulation approaches is presented. The chapter also provides several research and development directions, which can potentially facilitate the realization of smart pharmacy automation solutions in the era of Industrial 4.0.

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Acknowledgements

This study was supported by the Watson Institute of Systems Excellence (WISE) at Binghamton University and by iA. The authors would like to thank the anonymous reviews for their valuable comments in improving the quality of this manuscript.

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Authors and Affiliations

  1. Department of Systems Science and Industrial Engineering, Binghamton University, State University of New York, 4400 Vestal Pkwy E, Binghamton, NY, 13902, US

    Nieqing Cao, Mohammad Sa’eed Alattar, Yu Jin & Sang Won Yoon

  2. Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea

    Soongeol Kwon

Authors
  1. Nieqing Cao
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  2. Mohammad Sa’eed Alattar
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  3. Yu Jin
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  4. Soongeol Kwon
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  5. Sang Won Yoon
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Corresponding author

Correspondence to Yu Jin .

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Editors and Affiliations

  1. Industrial Engineering and Enterprise Information, Tunghai University, Taichung, Taiwan

    Chin-Yin Huang

  2. Department of Systems Science and Industrial Engineering, State University of New York at Binghamton, New York, NY, USA

    Sang Won Yoon

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Cao, N., Alattar, M.S., Jin, Y., Kwon, S., Yoon, S.W. (2023). Optimization in Pharmacy Automation System. In: Huang, CY., Yoon, S.W. (eds) Systems Collaboration and Integration. ICPR1 2021. Automation, Collaboration, & E-Services, vol 14. Springer, Cham. https://doi.org/10.1007/978-3-031-44373-2_19

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