scholarly journals Pengendalian Stok Spareparts Mobil Dengan Metode EOQ dan Min-Max Inventory

2021 ◽  
Vol 6 (3) ◽  
Author(s):  
Mia Juliana Siregar

This research was conducted in the distributor of car spare parts and the object studied was car glass glue. This item is a product that experiences a stacking stock in the warehouse, so it needs inventory control to reduce the stacking stock. The character of the product which does not have expired date as long as it is not used and small size, the company never make an optimal estimate of the order, so the activity of ordering goods is only based on its own estimates. The method used in this research is EOQ to obtain the economical amount of the product to be ordered. The calculation process using EOQ method is done against 2019 sales data predicted to 2021 using Trend Linear forecasting method, with function form is Y=1,8776x+256,21. Furthermore, the minimum and maximum stock quantity is determined using the Min-Max Inventory method. From the result of the study found that the economic Q per ordered is 386 pcs with the frequency of bookings 8 times a year. The minimum inventory is 108 pcs and the maximum is 144 pcs with the amount of safety stock is 72 pcs and ROP is 108 pcs. By using EOQ method, the company can make savings of Rp3,939,330 per year and reduce storage cost by Rp10,119,635 per year.

2020 ◽  
Vol 22 (2) ◽  
pp. 41-49
Author(s):  
David ◽  
Engmir ◽  
Irwan Budiman ◽  
Jusra Tampubolon

This research was conducted at one of the motorcycle dealers in Indonesia. Besides selling motorcycles, this dealer also provides services to repair motorcycles and sells genuine motorcycle parts. Inventory management which the company carried out is still not good enough because there are still demand for spare parts from consumers that cannot be fulfilled by the company. The purpose of this study is to draw up a plan to control spare parts by paying attention to the spare parts that need to be considered, estimating the exact number of spare parts demand, knowing the smallest total inventory cost, knowing the amount of safety stock needed, and knowing when to reorder. In preparing the spare parts control, the methods used are ABC analysis, demand forecasting method, and EOQ method. The results of this study are plans to control the inventory of Tire, Rr. such as the forecasting sales of Tire, Rr. as many as 17338, economic order quantity of Tire Rr are 2158 units, the number of safety stocks of Tire, Rr. needed in 2020 are 1738 units, and the reorder point in 2020 is 8 times with the total inventory cost for Tire, Rr. in 2020 is Rp. 30,009,005.


2014 ◽  
Vol 519-520 ◽  
pp. 1390-1394
Author(s):  
Jin Dong Gao ◽  
Yong Zhang ◽  
Fang Jun Zhou ◽  
Hong Long Mao

Control model for spare parts inventory is established based on the optimal replenishment cycle. The replenishment cycle impact on the spare parts inventory control is analyzed as well as the demand forecasting. First, the optimal replenishment cycle is given by using the method of the lowest cost of inventory. Then according to the demand characteristic of the spare parts, the safety stock can be calculated. Finally on the basis of the demand forecasting, the calculation method of spare parts replenishment quantity is given. A numerical example is presented to verify the validity and practicability of the model.


2017 ◽  
Vol 16 (2) ◽  
Author(s):  
Endah Budiningsih ◽  
Wakhid Ahmad Jauhari

<em>PT. Prima Sejati Sejahtera as one of the subsidiaries of PT. Pan Brothers Tbk. which is engaged in garment production. The company's mechanical department in managing spare part inventory is still using intuitive method, where the number of spare part order for certain periods based on spare part demands data onto the previous period. The company’s mechanical department often stock out of spare parts. Spare part’s inventory management becomes a complex issue because of the need for fast response to handle the downtime of machines, and the risk of obsolescence of spare parts. So in this research will discuss about spare part inventory control which is started with spare parts grouping by using ABC analysis method to determine the appropriate inventory control method for each group. There are 23 spare parts which included in group A. The forecast of spare part’s demands to use Croston, Syntetos-Boylan Approximation (SBA) and Single Exponential Smoothing (SES). Comparison of each forecasting method will be determined by the value of forecasting errors (MAD). It is known that there are 12 spare parts with Croston method in the best forecasting method, 6 spare parts in Syntetos-Boylan Approximation (SBA) method and 5 spare parts with Single Exponential Smoothing (SES) method. Based on the best forecasting result, it will be calculated the value of safety stock (SS), reorder point (ROP) and the optimal number of ordering (Q) using Continuous Review method for each spare part.</em>


2018 ◽  
Vol 31 ◽  
pp. 11015 ◽  
Author(s):  
Alzena Dona Sabila ◽  
Mustafid Mustafid ◽  
Suryono Suryono

The inventory control system has a strategic role for the business in managing inventory operations. Management of conventional inventory creates problems in the stock of goods that often runs into vacancies and excess goods at the retail level. This study aims to build inventory control system that can maintain the stability of goods availability at the retail level. The implementation of Vendor Managed Inventory (VMI) method on inventory control system provides transparency of sales data and inventory of goods at retailer level to supplier. Inventory control is performed by calculating safety stock and reorder point of goods based on sales data received by the system. Rule-based reasoning is provided on the system to facilitate the monitoring of inventory status information, thereby helping the process of inventory updates appropriately. Utilization of SMS technology is also considered as a medium of collecting sales data in real-time due to the ease of use. The results of this study indicate that inventory control using VMI ensures the availability of goods ± 70% and can reduce the accumulation of goods ± 30% at the retail level.


2000 ◽  
Vol 51 (10) ◽  
pp. 1184 ◽  
Author(s):  
L. W. G. Strijbosch ◽  
R. M. J. Heuts ◽  
E. H. M. van der Schoot

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