Inventory Optimization in Pharmacy Using Inventory Simulation-Based Model During the Covid-19 Pandemic

Authors

DOI:

https://doi.org/10.30656/intech.v9i2.5820

Keywords:

EOQ, Inventory, Monte-carlo Simulation, Pharmacy, Warehouse

Abstract

The problem that often occurs in raw material inventory is overstock or stockout conditions. The healthcare industry, including pharmaceuticals, has been experiencing uncertainty since the Covid-19 pandemic. Then impacts panic buying and stockpiling, which can lead to unpredictable spikes in demand, stockouts, and disruptions to the inventory system. The research was conducted at ABC Pharmacy in Yogyakarta, which experienced this problem. In this study, optimization of drug supply was carried out by measuring ware­house capacity, and safety stock, increasing the number of orders and reorder points using the Min-Max and the economic order quantity models. A simulation of inventory optimi­zation planning was carried out using Monte Carlo to see inventory projections for the next three months. Overall, the EOQ model simulation shows the most optimal results by showing the average total inventory cost of Rp. 103,579, where this number represents the lowest number of total inventory costs when compared to other simulation models. It also shows that the EOQ model is 86% more efficient in inventory cost than the Min-Max model. Comparison of the total cost of inventory The results of the three methods are calcu­lated according to current demand and simulation of the EOQ method, which produces the minimum total inventory cost, followed by the company's initial model and the Min Max inventory method.

Downloads

Download data is not yet available.

References

Asana, I. M. D. P., Radhitya, M. L., Widiartha, K. K., Santika, P. P., & Wiguna, I. K. A. G. (2020). Inventory control using ABC and min-max analysis on retail management information system. Journal of Physics: Conference Series, 1469(1), 12097. https://doi.org/10.1088/1742-6596/1469/1/012097

Dcode. (2020). Dcode EFC Expectations in March 2020. Dcode Economic & Financial Consulting. https://img1.wsimg.com/blobby/go/2cdd937c-6619-4712-8b7c-e0cc3b5ce6a5/Dcode EFC- Economic Sectors More than One Year.pdf

Fadhil, M., & Suryani, E. (2021). Inventory Planning for XYZ Mart using EOQ and Monte Carlo. IPTEK Journal of Proceedings Series, 233–237. https://doi.org/10.12962/j23546026.y2020i3.11217

Friday, D., Savage, D. A., Melnyk, S. A., Harrison, N., Ryan, S., & Wechtler, H. (2021). A collaborative approach to maintaining optimal inventory and mitigating stockout risks during a pandemic: capabilities for enabling health-care supply chain resilience. Journal of Humanitarian Logistics and Supply Chain Management, 11(2), 248–271. https://doi.org/10.1108/JHLSCM-07-2020-0061

Heinrich, S. (1998). Monte Carlo Complexity of Global Solution of Integral Equations. Journal of Complexity, 14(2), 151–175. https://doi.org/10.1006/jcom.1998.0471

Hidayatuloh, S., Febriani, A., Samodro, G., & Indarwati, T. (2022). Improved Warehousing Performance Using the Frazelle Model in Pharmacies During a Covid-19 Pandemic. Jurnal Ilmiah Teknik Industri, 21(1), 83–90. https://doi.org/10.23917/jiti.v21i1.17182

Jufriyanto, M. (2020). Peramalan Permintaan Keripik Singkong Pada UMKM Difaa dengan Simulasi Monte Carlo. Jurnal Teknik Industri: Jurnal Hasil Penelitian Dan Karya Ilmiah Dalam Bidang Teknik Industri, 6(2), 107–113. https://doi.org/10.24014/jti.v6i2.10452

Kinanthi, A. P., Herlina, D., & Mahardika, F. A. (2016). Analisis Pengendalian Persediaan Bahan Baku Menggunakan Metode Min-Max (Studi Kasus PT.Djitoe Indonesia Tobacco). PERFORMA : Media Ilmiah Teknik Industri, 15(2), 87–92. https://doi.org/10.20961/performa.15.2.9824

Kwak, J.-K. (2021). An Order-Up-to Inventory Model with Sustainability Consideration. Sustainability, 13(23), 13305. https://doi.org/10.3390/su132313305

Lihui, W., Liwei, T., Shenyang, L., & Yan, L. (2020). Inventory Optimization Models of Equipment Spare Parts Based on Computer Simulation. 2020 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS), 235–237. https://doi.org/10.1109/ICPICS50287.2020.9202064

Mapes, J. (2015). Economic Order Quantity. In Wiley Encyclopedia of Management (pp. 1–2). John Wiley & Sons, Ltd. https://doi.org/10.1002/9781118785317.weom100101

Nemtajela, N., & Mbohwa, C. (2017). Relationship between Inventory Management and Uncertain Demand for Fast Moving Consumer Goods Organisations. Procedia Manufacturing, 8, 699–706. https://doi.org/10.1016/j.promfg.2017.02.090

Norhadibah Azman, S., Suzana Jaafar, H., Alam, P., & Author, C. (2018). Supply Chain Disruptions That Impact on Factors of Supply Chain Efficiency Performance and Competitiveness. In Advances in Transportation and Logistics Research (Vol. 1). https://proceedings.itltrisakti.ac.id/index.php/ATLR/article/view/34

Patriarca, R., Di Gravio, G., Costantino, F., & Tronci, M. (2020). EOQ inventory model for perishable products under uncertainty. Production Engineering, 14(5-6), 601–612. https://doi.org/10.1007/s11740-020-00986-5

Profita, A. (2017). Optimasi Manajemen Persediaan Darah Menggunakan Simulasi Monte Carlo. Journal of Industrial Engineering Management, 2(1), 16–24. https://doi.org/10.33536/jiem.v2i1.101

Putra, I. M. A. D., & Rahyuda, A. G. (2018). Analisis Kinerja Manajemen Persediaan Di Barjaz Company Menggunakan Pendekatan EOQ. E-Jurnal Manajemen Universitas Udayana, 8(1), 7163–7190. https://doi.org/10.24843/EJMUNUD.2019.v08.i01.p08

Rambitan, B. F., Sumarauw, J. S. B., & Jan, A. H. (2018). Analisis Penerapan Manajemen Persediaan Pada CV. Indospice Manado. Jurnal EMBA, 6(3), 1448–1457. https://ejournal.unsrat.ac.id/index.php/emba/article/view/20228

Sabah, B., Nikolay, T., & Sylverin, K.-T. (2019). Production planning under demand uncertainty using Monte Carlo simulation approach: a case study in fertilizer industry. 2019 International Conference on Industrial Engineering and Systems Management (IESM), 1–6. https://doi.org/10.1109/IESM45758.2019.8948112

Shafi, M. (2014). Management of Inventories in Textile Industry : A Cross Country Research Review. Singaporean Journal of Business , Economics and Management Studies, 2(7), 45–59. https://doi.org/10.12816/0004017

Utama, I. T., & Siswanto, N. (2017). Inventory System Planning of Margarine and Shortening Ingredient With Monte Carlo Simulation in Addition To Economic Order Quantity (EOQ) Method on PT . Smart Tbk. E-Jurnal SPIRIT PRO PATRIA, 3(September), 2. https://jurnal.narotama.ac.id/index.php/patria/article/view/425

Zhang, T., Chen, X., Yu, Z., Zhu, X., & Shi, D. (2018). A Monte Carlo Simulation Approach to Evaluate Service Capacities of EV Charging and Battery Swapping Stations. IEEE Transactions on Industrial Informatics, 14(9), 3914–3923. https://doi.org/10.1109/TII.2018.2796498

Downloads

Published

2023-07-01

How to Cite

Hidayatuloh, S., Winati, F. D. ., Samodro, G. ., Qisthani, N. N. ., & Kasanah, Y. U. . (2023). Inventory Optimization in Pharmacy Using Inventory Simulation-Based Model During the Covid-19 Pandemic. Jurnal INTECH Teknik Industri Universitas Serang Raya, 9(2), 110–116. https://doi.org/10.30656/intech.v9i2.5820

Issue

Vol. 9 No. 2 (2023): Desember

Section

Articles