scholarly journals Managing Spare Parts Inventory by Incorporating Holding Costs and Storage Constraints

2021 ◽  
Vol 11 (2) ◽  
pp. 139-144
Author(s):  
Babatunde Omoniyi Odedairo
Keyword(s):  
Raw Materials ◽  
Spare Parts ◽  
Inventory Model ◽  
Inventory Cost ◽  
Holding Costs ◽  
Spare Parts Inventory ◽  
Holding Cost ◽  
Total Inventory ◽  
Abc Analysis ◽  
Cost Components

AbstractA key factor for motivating intending buyers of raw materials is vendor responsiveness. Therefore, to meet demand, a pre-approved level of stocks is often maintained. In contrast, the decision to keep an uncontrolled amount of stock could be counter-productive with cost components associated with holding often ignored unintentionally. In this study, the objective is to develop a spare parts inventory model that incorporates ignored holding costs with a storage constraint for a motorcycle assembly plant (MAP). The inventory policy, structure of holding costs, and spare parts sales reports were consulted for relevant data. The spare parts were categorized and selected using ABC analysis. A spare parts inventory model, which considers ignored holding cost, was formulated. The model was executed using Lingo optimisation software release 18.0.56 to determine the pair of the order quantity (Ɋ) and reorder point (Ɍ). 177 spare part items were identified using ABC analysis. The parts categorisation revealed that 21, 31, 125 part items belong to categories A, B, and C with 81, 15 and 4% of annual sales value, respectively. From category A, nine items contributed significantly to overall sales. The demand pattern for these items was probabilistic based on their coefficient of variation. The pair (Ɋ, Ɍ) for items N, Z, AY, K, AM, J, P, AL and AZ are (174,688), (71,147), (78,150), (86,163), (18,15), (88,170), (128,118), (33,43) and (87,152), respectively. These pairs yielded a total inventory cost of ₦2,177,363 when compared to the current total inventory investment of ₦6,800,000 resulting in a 67.9% cost reduction. A model to manage spare parts inventory with relevant holding cost components was developed for MAP to ensure the availability of items, maximize usage of storage space, and minimize total inventory cost.

scholarly journals Inventory Model with Partial Backordering When Backordered Customers Delay Purchase after Stockout-Restoration

2016 ◽  
Vol 2016 ◽  
pp. 1-16
Author(s):  
Ren-Qian Zhang ◽  
Yan-Liang Wu ◽  
Wei-Guo Fang ◽  
Wen-Hui Zhou
Keyword(s):  
Layer Structure ◽  
Inventory Model ◽  
Inventory Cost ◽  
Cost Component ◽  
Lipschitz Optimization ◽  
Partial Backordering ◽  
Demand Rate ◽  
Holding Cost ◽  
Total Inventory ◽  
Inventory Holding

Many inventory models with partial backordering assume that the backordered demand must be filled instantly after stockout restoration. In practice, however, the backordered customers may successively revisit the store because of the purchase delay behavior, producing a limited backorder demand rate and resulting in an extra inventory holding cost. Hence, in this paper we formulate the inventory model with partial backordering considering the purchase delay of the backordered customers and assuming that the backorder demand rate is proportional to the remaining backordered demand. Particularly, we model the problem by introducing a new inventory cost component of holding the backordered items, which has not been considered in the existing models. We propose an algorithm with a two-layer structure based on Lipschitz Optimization (LO) to minimize the total inventory cost. Numerical experiments show that the proposed algorithm outperforms two benchmarks in both optimality and efficiency. We also observe that the earlier the backordered customer revisits the store, the smaller the inventory cost and the fill rate are, but the longer the order cycle is. In addition, if the backordered customers revisit the store without too much delay, the basic EOQ with partial backordering approximates our model very well.

scholarly journals Decreasing Total Inventory Cost by Controlling Inventory in Motorcycle Dealer

2020 ◽  
Vol 22 (2) ◽  
pp. 41-49
Author(s):  
David ◽  
Engmir ◽  
Irwan Budiman ◽  
Jusra Tampubolon
Keyword(s):  
Inventory Management ◽  
Demand Forecasting ◽  
Spare Parts ◽  
Order Quantity ◽  
Inventory Cost ◽  
Safety Stock ◽  
Safety Stocks ◽  
Forecasting Method ◽  
Total Inventory ◽  
Abc Analysis

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.

scholarly journals Controllable deterioration rate for time-dependent demand and time-varying holding cost

2014 ◽  
Vol 24 (1) ◽  
pp. 87-98 ◽  
Author(s):  
Vinod Mishra
Keyword(s):  
Linear Function ◽  
Inventory Model ◽  
Deteriorating Items ◽  
Inventory Cost ◽  
Deterioration Rate ◽  
Preservation Technology ◽  
Demand Rate ◽  
Holding Cost ◽  
Total Inventory ◽  
Dependent Demand

In this paper, we develop an inventory model for non-instantaneous deteriorating items under the consideration of the facts: deterioration rate can be controlled by using the preservation technology (PT) during deteriorating period, and holding cost and demand rate both are linear function of time, which was treated as constant in most of the deteriorating inventory models. So in this paper, we developed a deterministic inventory model for non-instantaneous deteriorating items in which both demand rate and holding cost are a linear function of time, deterioration rate is constant, backlogging rate is variable and depend on the length of the next replenishment, shortages are allowed and partially backlogged. The model is solved analytically by minimizing the total cost of the inventory system. The model can be applied to optimizing the total inventory cost of non-instantaneous deteriorating items inventory for the business enterprises, where the preservation technology is used to control the deterioration rate, and demand & holding cost both are a linear function of time.

scholarly journals A Procedure for Scheduling Inventory of an Industry by Merging Forecasting and Linear Programming

2020 ◽  
Vol 68 (1) ◽  
pp. 65-70
Author(s):  
AKM Selim Reza ◽  
Sayma Suraiya ◽  
M Babul Hasan
Keyword(s):  
Linear Programming ◽  
Raw Materials ◽  
Minimum Cost ◽  
Inventory Cost ◽  
Model Combining ◽  
Forecasting Method ◽  
Holding Cost ◽  
Optimum Order ◽  
Total Inventory ◽  
Inventory Holding

In this paper, we develop a mathematical model combining forecasting and linear programming for a business organization of Bangladesh to calculate optimum order quantity and inventory cost. We test the model using raw data of the demand for the raw materials and spare inventory for the industry and find out minimum total inventory cost along with ordering cost and inventory holding cost. The developed model make a match between the forecasted demand of raw materials and spare inventory and the minimum total cost of inventory. Finally comparing minimum cost, we observe that our estimated appropriate forecasting method gives optimal inventory cost. Dhaka Univ. J. Sci. 68(1): 65-70, 2020 (January)

scholarly journals Inventory Optimization using Simulation Approach

2018 ◽  
Vol 3 (2) ◽  
pp. 38-47
Author(s):  
Nuridawati Baharom ◽  
Pa’ezah Hamzah
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Raw Materials ◽  
Current System ◽  
Inventory System ◽  
Inventory Cost ◽  
Manufacturing Firm ◽  
Inventory Optimization ◽  
Holding Cost ◽  
Total Inventory

Inventory creates a significant cost to a firm in the form of the ordering cost, shortage cost, holding cost and also the cost of the goods itself. Managing inventory is always a big challenge for firms in order to balance these operating costs and maintain customer’s service. In this paper, a case study of an electronics manufacturing firm was used to illustrate the use of the Monte Carlo simulation to improve the current inventory system for sensor cable. A simulation model mimicking the current inventory system was developed, and used to study the current system and alternative reorder point policies.  Various reorder points were experimented to determine the reorder policy that results in the lowest average total inventory cost per week. The simulation experiments allow the decision maker to make good purchasing decisions in order to avoid ordering excessive raw materials which lead to higher inventory cost to the company.   Keywords: inventory, optimization, Monte Carlo Simulation

scholarly journals An Optimal Order Quantity Of Spare Parts To Minimize Total Inventory Cost Using Periodic Review Approach (R,s,s) Method In PT. XYZ Bandung

2017 ◽  
Vol 1 (02) ◽  
Author(s):  
Feviana Betsi Purba ◽  
Luciana Andrawina ◽  
Murni Dwi Astuti
Keyword(s):  
Spare Part ◽  
Spare Parts ◽  
Optimal Order ◽  
Periodic Review ◽  
Order Quantity ◽  
Inventory Cost ◽  
Inventory Policy ◽  
Total Saving ◽  
Manufacturing Company ◽  
Total Inventory

The availability of spare parts is very crucial thing for manufacturing company in order to support the continuity of production activities. PT XYZ is a manufacturing company which produces thread into fabric. In this case, inventory control of spare part is not properly managed. Inventory position of spare parts in warehouse is always more than inventory policy of the company itself or called overstock which causes total inventory cost is always high. Company only consider on the order fulfillment of spare parts to prevent downtime on the machine that increase performance of production. Hence, order quantity of spare parts is always excessive or not optimal. In this research, global inventory policy conducted in order to minimize total inventory cost is periodic review approach (R, s, S) method. This inventory policy will be calculated using power approximation and obtained total saving cost of holding cost by 31 % while total saving cost of order cost decreased by 7 %. Overall, total inventory cost minimized by 7 % or equal to Rp138.902.742.

scholarly journals Preventive Maintenance Interval Prediction: a Spare Parts Inventory Cost and Lost Earning Based Model

2015 ◽  
Vol 5 (3) ◽  
pp. 811-817
Author(s):  
O. A. Adebimpe ◽  
V. Oladokun ◽  
O. E. Charles-Owaba
Keyword(s):  
Preventive Maintenance ◽  
Spare Parts ◽  
Manufacturing Firms ◽  
Inventory Cost ◽  
Manufacturing Firm ◽  
Interval Prediction ◽  
Spare Parts Inventory ◽  
Optimal Maintenance

In this paper, some preventive maintenance parameters in manufacturing firms were identified and used to develop cost based functions in terms of machine preventive maintenance. The proposed cost based model considers system’s reliability, cost of keeping spare parts inventory and lost earnings in deriving optimal maintenance interval. A case of a manufacturing firm in Nigeria was observed and the data was used to evaluate the model.

scholarly journals PENGENDALIAN PERSEDIAAN BAHAN BAKU DALAM PROSES PRODUKSI DENGAN MENGGUNAKAN METODE ECONOMIC ORDER QUANTITY (EOQ)

2019 ◽  
Vol 1 (2) ◽  
pp. 415-423
Author(s):  
Elia Rahayu R ◽  
Nor Norisanti ◽  
Acep Samsudin
Keyword(s):  
Raw Materials ◽  
Raw Material ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Analysis Method ◽  
Inventory Cost ◽  
Total Inventory ◽  
The Difference ◽  
Quantitative Descriptive

The purpose of this study is to control the supply of raw materials using the Economic Order Quantity (EOQ) method in Tahu Nugraha Jaya Sukabumi UKM. The data analysis method used is quantitative descriptive to describe and describe the data to be examined and then processed using EOQ. This study uses the EOQ method to determine the total inventory cost. The data needed in this study are the number of purchases of raw materials, the amount of use of raw materials, storage costs, and ordering costs. The results of this study indicate that by applying the EOQ method can further optimize the supply of raw materials by minimizing raw materials with increased inventory. With the application of the Economic Order Quantity (EOQ) method it shows more efficient than conventional methods of the company. Conclusions, seen from the difference in the TIC of the two methods, the more efficient method is the Economic Order Quantity (EOQ) method that is equal to 244,392.94 while the calculation used by the company is 374,325. so that it can be obtained that there is a difference between the Company TIC and the EIC method TIC. Keywords: Raw Material Inventory, Production Process

scholarly journals Analysis and Design of Information Systems for Control of Raw Materials in UD. YRS Alumunium Work Using EOQ Method

Tech-E ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. 30
Author(s):  
Assaji Assaji ◽  
Rudy Arijanto
Keyword(s):  
Information Systems ◽  
Raw Materials ◽  
Order Quantity ◽  
Sequence Diagrams ◽  
Inventory Cost ◽  
Safety Stock ◽  
Analysis And Design ◽  
Total Inventory ◽  
Manual Recording ◽  
Class Diagrams

In the current era of globalization, information technology and information systems are developing very fast. YRS Alumunium Work is a furniture company that manufactures cupboards, stove racks, sinks, and especially for storage of household items. The problems currently being faced by businesses, among others; (a) recording still using stationery and books or still using manual recording methods, (b) ineffective stock checking, (c) sudden out of stock, to solve the problem it is proposed to make a system using the web that can be integrated into stock by a calculation method. With UML scenario depiction (activity diagrams, usecase diagrams, class diagrams, sequence diagrams). To check the inventory of goods easily done effectively, know the minimum amount of stock, and must place an order again using the EOQ (Economic Order Quantity) method. By using the eoq method, it takes into account that for bolts to get an economical amount of inventory as much as 522.01 with a safety stock of 21 will place an order again when the stock becomes 50 and the total inventory cost is 110 458.4418.

scholarly journals Inventory model for deteriorating items with negative exponential demand, probabilistic deterioration and fuzzy lead time under partial back logging

2020 ◽  
Vol 30 (3) ◽  
Author(s):  
Nabendu Sen ◽  
Sumit Saha
Keyword(s):  
Inventory Management ◽  
Lead Time ◽  
Probability Distributions ◽  
Optimal Strategies ◽  
Inventory Model ◽  
Deteriorating Items ◽  
Optimal Time ◽  
Inventory Cost ◽  
Total Inventory ◽  
Negative Exponential

The effect of lead time plays an important role in inventory management. It is also important to study the optimal strategies when the lead time is not precisely known to the decision makers. The aim of this paper is to examine the inventory model for deteriorating items with fuzzy lead time, negative exponential demand, and partially backlogged shortages. This model is unique in its nature due to probabilistic deterioration along with fuzzy lead time. The fuzzy lead time is assumed to be triangular, parabolic, trapezoidal numbers and the graded mean integration representation method is used for the defuzzification purpose. Moreover, three different types of probability distributions, namely uniform, triangular and Beta are used for rate of deterioration to find optimal time and associated total inventory cost. The developed model is validated numerically and values of optimal time and total inventory cost are given in tabular form, corresponding to different probability distribution and fuzzy lead-time. The sensitivity analysis is performed on variation of key parameters to observe its effect on the developed model. Graphical representations are also given in support of derived optimal inventory cost vs. time.

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