Inventory Control Analysis of Plastic Raw Materials Using Monte Carlo Simulation Approach

Wulandari, Lusi Mei Cahya and Putri, Laurensia Dilawati Indrianto (2021) Inventory Control Analysis of Plastic Raw Materials Using Monte Carlo Simulation Approach. OPSI Jurnal Optimasi Sistem Industri, 14 (1). pp. 104-114. ISSN p-ISSN 1693-2102 / e-ISSN 2686-2352

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Abstract

Excess inventory of goods is one of the factors to increase production costs and can reduce the profits earned by the company. The company's ability to control the supply of raw materials is the key to the continuity of the production process. This research was conducted plastic-based packaging industry that focuses on injection and blows molding to determine an inventory control system that can minimize the cost of raw material inventory, especially PET (Polyethylene Terephthalate) type plastic seeds. The inventory model is Economic Order Quantity (EOQ), Economic Order Interval (EOI), and Min-Max. The Monte Carlo simulation approach determines the right inventory model in the future, with Perpetual Inventory Simulation, Periodic Inventory Simulation, and Min-Max Simulation. Based on current demand, the EOQ method produces an economic order quantity of 20,055 kilograms, safety stock 12,687 kilograms, reorder point 53,380 kilograms, with a total inventory cost of Rp 116,237,173. On the other side, the Monte Carlo simulation approach for the next 34 weeks of demand, the EOQ method also produces minimal inventory costs, compared to other models. The EOQ method can be a solution to companies in inventory policies.

Item Type:	Article
Uncontrolled Keywords:	EOQ; EOI; Min-Max; Inventory; Monte Carlo Simulation
Subjects:	H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Divisions:	Fakultas Teknik > Prodi Teknik Industri
Depositing User:	Lusi Mei Cahya Wulandari
Date Deposited:	10 Jul 2021 13:10
Last Modified:	09 Jan 2023 09:28
URI:	http://repositori.ukdc.ac.id/id/eprint/821

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