Saline Inventory Management with Simulation Techniques

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Jarupong Banthao
Wijai Boonyanusith
Nuanpan Buransri
Panadda Sophatai
Pojjana Thankrathok

Abstract

This research aims to study an inventory system for managing saline in four categories at a community hospital. The objective is to conduct an Economic Order Quantity (EOQ) and Reorder Point (ROP) to improve the saline inventory management system. Monte Carlo Simulation technique was applied to analyze saline inventory management policies under uncertain demands, namely; s, Qmax(1), s, Qavg(2), s, Qmin(3), T, Qmax(4), T, Qavg(5), T, Qmin(6), T, S (7), and s, S(8). An optimization technique was used to conduct the suitable policy of saline inventory management. The simulation results stated that the most appropriate policy without affecting shortage and overstocking was s,Qmax policy. Moreover, the comparison of each demand quantity (bottle) in each type of saline (A, B, C, and D) among the proposed policies indicated that the s,Qmax policy yielded the lowest overstocking value compared to each demand in each saline type equal to 0.20, 0.38, 0.32, and 0.37, respectively. This study ca


 

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References

Soiraya, S., & Sookseksan, N. (2016). The appropriate inventory policy formulation by using Monte Carlo Simulation Technique: Case study in chemical cleaning products and chemical water treatment products manufacturer. Engineering Journal Chiang Mai University, 23(2), 47–59.

Viboonsunti, C., Kumprakorb, U., & Sirisa-ard, P. (2003). Stock management of drug inventory control in the Community Pharmacy Laboratory. The Thai Journal of Pharmaceutical Sciences, 27(3-4), 139–148.

Muensrichai, J. (2009). The economic order quantity under uncertainties by Monte Carlo Simulation method. Master of Industrial Management Engineering. King Mongkut’s University of Technology North Bangkok.

Jintaketkam, P. (2012). The application of Monte Carlo Technique for optimizing order quantity policy: A case study in light bulb industry. Master of Industrial Management Engineering. King Mongkut’s University of Technology North Bangkok.

Pongkrasint, P. (2013). Optimal order quantity for rigid PVC film by using Mote Carlo Simulation technique. Master of Industrial Management Engineering. King Mongkut’s University of Technology North Bangkok.

Phupha, W. (2014). An application of Monte Carlo Simulation for optimal order quantity : A case study of raw materials procurement in processed food industry. Kasetsart Engineering Journal, 27(88), 41–56.

Mohammed, S. A., & Workneh, B. D. (2020). Critical analysis of pharmaceuticals inventory management using the ABC-VEN Matrix in Dessie Referral Hospital, Ethiopia. Integrated Pharmacy Research & Practice, 9(1), 113–125.