Total Inventory Cost Research Articles

Controlling inventories in omni/multi-channel distribution systems with variable customer order-sizes

The fast growth of e-commerce and omni/multi-channel retailing brings new challenges for efficient inventory management. One such challenge concerns service differentiation across channels when upstream central warehouses satisfy both direct customer demand and replenishment orders from downstream retailers. Motivated by industry collaboration, we address this issue by developing a combined stock method for control of one-warehouse-multiple-retailer inventory systems with direct customer demand at the central warehouse. The combined stock method, used for service differentiation at the central warehouse, may be described as a critical level policy. The computationally efficient heuristics we present are designed to deal with real-life one warehouse multiple retailer inventory systems characterized by highly variable customer order-sizes, (R,Q) policies at all stock points, and fill rate constraints. A numerical study, including real data from two different companies, illustrates that the heuristics perform well; offering near optimal solutions close to target fill rates, with significant opportunities to reduce total inventory costs compared to existing methods.

Neutrosophic Cost Pattern of Inventory System with Novel Demand Incorporating Deterioration and Discount on Defective Items Using Particle Swarm Algorithm.

The potential to obtain defective or damaged items with non-defective commodities is common to experience at the production unit or when shipping products from one layer to another. This research focuses on the faulty things that retailers receive from suppliers. The retailer has set a restriction on the percentage of defective things, and the retailer receives a discount on the cost of purchasing defective items. The proposed inventory system handles the uncertainty in inventory costs and also considers the demand and deterioration of items with prioritized maximum product life. This work minimizes total inventory cost when demand rate as a function of reliability and power pattern of time under a crisp and triangular neutrosophic environment. The inventory system for degrading items considers the predictability and power pattern of time with a reasonable payment delay. The interest charges are applied only after a specific permissible time limit in the proposed inventory system. The neutrosophic number that defines three different kinds of membership functions representing the truth, hesitation, and falseness is applied in the inventory model in handling the uncertainty of the cost pattern. The proposed inventory model is investigated using a particle swarm optimization algorithm, and the results are validated using a numerical example and a sensitivity analysis for various parameters.

Analisis Peramalan Dengan Simulasi Monte Carlo dan Implementasi Pengendalian Persediaan Gula Berdasarkan EOQ

Inventory control has an important role to maintain the stability of the company's business continuity. With inventory control, companies can meet consumer needs and consumers will feel satisfied if the demand comes on time. On the other hand, with this focus on inventory control, company management must also be careful if the raw material inventory is too large, it will result in high inventory costs, on the other hand, if there is too little raw material inventory, it will result in unfulfilled consumer needs. The purpose of this study is to identify forecasting the amount of sugar demand in 2019 and determine the amount of inventory costs from the forecasting results using EOQ. It is hoped that in the future the company will not only be able to know the future demand side based on forecasting, but the company already has an estimate of the total cost of inventory. The need for sugar raw materials from the forecasting results is 170,173 kg. Where the most needs are in April and November 2019, the number of economic purchases is 5218 kg with a frequency of ordering 33 times a year. Based on company policy, there is currently no information on safety stock and reoder points set by the company. With the EOQ proposal, the results of the safety stock and reoder point are 34,349 kg and 70,875 kg, respectively. The TIC proposal based on the EOQ is able to reduce the total inventory cost which was originally with the company's policy of Rp. 1,805,785,530 to Rp. 1,805,138,304 where this figure saves Rp. 647,226

ANALISIS PERBANDINGAN METODE ECONOMIC ORDER QUANTITY (EOQ) DAN PERIODIC ORDER QUANTITY (POQ) DALAM PENGENDALIAN PERSEDIAAN BAHAN CUTTING DISK DAN CARBON GOUGING DI PT. STP

Material inventory is one of the important elements to simplify the production process in the company. PT. STP is a company that produces module structures. This company often uses consumable materials, namely Cutting Disk and Carbon Gouging to work on its orders. The company controls the inventory of both materials using the FIFO (First in First out) method. However, the inventory costs incurred by the company with this method are still quite large and cause excess material stocks. This study aims to analyze the comparison of EOQ (Economic Order Quantity) and POQ (Periodic Order Quantity) methods in controlling the inventory of Cutting Disk and Carbon Gouging materials in PT. STP. The results showed that with the EOQ method, the ordering frequency became 13 times a year with a quantity per order of 1434 boxes for Cutting Disk material and the ordering frequency was 8 times a year with a quantity per order of 656 boxes for Carbon Gouging material. Meanwhile, the results of the POQ method obtained that the order frequency to be 12 times a year with a quantity per order of 1,498 boxes for Cutting Disk materials and the ordering frequency to be 6 times a year with a quantity per order of 852 boxes for Carbon Gouging materials. The results of the EOQ method obtained the total inventory cost of Cutting Disk materials of Rp. 929,455,735, - and Carbon Gouging of Rp. 1,828,712,584, - with the total inventory cost (TC) of the two materials of Rp. 2,758,168,319,-. While the results of the POQ method obtained the total inventory cost of Cutting Disk materials of Rp. 929,294,252,- and Carbon Gouging of Rp. 1,828,902,262,- with the total inventory cost (TC) of the two materials of Rp. 2,758,196,514,-.

PERENCANAAN PERMINTAAN BAHAN BAKU DAN PENENTUAN UKURAN PEMESANAN (LOT SIZE) OPTIMAL DI GUDANG KIMIA MARUNDA

<p><em>This research was conducted on companies that store and distribute chemical raw materials (sodium sulfate) to industrial companies. The problem that occurs is that the company does not have a medium-term raw material demand plan to determine the optimal order size to suppliers as storage in the warehouse. Given that ordering is also important to note because it has an impact on the total cost of inventory from ordering costs and holding costs. The purpose of this study is to forecast to find out the demand for raw materials in the future so that the company has an estimate for planning future demand for raw materials and calculates several ordering methods (lot size) to get the optimal order size.</em></p><p><em>Solving problems using forecasting methods (Moving Average, Weight Moving Average, Exponential Smooth), and lot size methods (Economic Order Quantity, Period Order Quantity, Least Unit Cost, Part Period Balancing). The results of the analysis, forecasting to determine the demand for raw materials for the next year using the Exponential Smooth method because it has the smallest MAD MSE MAPE value, and the ordering lot size using the Part Period Balancing method because it has the minimum total inventory cost of Rp. 14,128,706,027 or 23.5% more efficient than the usual ordering used by companies.</em></p>

Analisis Manajemen Inventory Spare Parts Alat Berat Pelabuhan Model Consignment Stock Guna Meminimumkan Total Inventory Cost (TIC) di PT XYZ

ABSTRACT
 PT. XYZ is a service company engaged in the maintenance of port heavy equipment and modification of port heavy equipment as well as procurement of spare parts for port heavy equipment. In 2018 along with improving the work performance of PT. XYZ expands its wings to civil works in the port sector, starting from dock repair work, maintenance of port accessories, construction of structures and reclamation. In a maintenance service company and the provision of spare parts for port heavy equipment, the company's inventory must be guaranteed. at each site PT. XYZ especially PT. X has a limited warehouse, so it must maximize the company's inventory. In the company's existing condition, the amount of inventory still exceeds the number of user requests which will accidentally fill their warehouse and will increase the Total Inventory Cost (TIC). With this problem, TIC depreciation will be carried out with a periodic review policy (R, s, S) and a periodic review policy with a consignment stock inventory system. Based on the above method, the original TIC amounted to Rp. 43,063,451 with the periodic review method of TIC amounting to Rp. 38,318,736 or decreased by 11% and if using the periodic review method with the inventory consignment stock TIC system, the amount was Rp. 36,987,546 or decreased by 13%.

Optimasi Inventori Material Bubuk Nylon pada Proses Coating dengan Pendekatan Probabilistik

<p><em>This research aims to optimize the supply of raw material for nylon powder for the manufacturing industry. The problem was found in the nylon powder warehouse which was out of stock so that it had to be replaced with plastic raw materials to keep the production process running. The change of raw material from nylon powder to plasco was done because the company did not make an emergency order for nylon powder. This is due to the high cost of emergency orders. The use of plasco powder makes the company accept a sizeable return of goods. Therefore it is necessary to do a good inventory management to overcome the out of stock. The method used to solve this problem is the probabilistic P back order model. Demand in the previous period was normally distributed. The results of processing with the P back order model produce a service level of 99.95%. It is hoped that the company will not experience out of stock again. In addition, a savings of 4.50% were obtained from the total costs incurred by the company. Inventory policy obtained using the P back order model with an order time of (T) 0.358 or for 130 days a new order will be made, and the total inventory cost is Rp.418,363,268 / year with a service level of 99.995%.</em></p>

Intelligent inventory management approaches for perishable pharmaceutical products in a healthcare supply chain

This study develops intelligent inventory management (IIM) approaches for managing perishable pharmaceutical products in a healthcare supply chain consisting of multiple regional hospitals and a central warehouse. The purchase price of the product is assumed to be age dependent, and the age distribution of the product is assumed to be known and is shared among all the supply chain members. Each agent representing a regional hospital or the central warehouse in the supply chain replenishes its stocks from its upstream agent. In IIM approaches, reinforcement learning methods, specifically Q-learning and Deep Q-network, are used to construct inventory policies. The IIM policies provide hospitals with near-optimal order quantities and remaining life distributions for products they order. Through many test instances, the performance of the IIM policies is compared to that of periodic review (R,s,S) policies obtained through a stochastic mixed integer programming model, solved using CPLEX and a genetic algorithm. The computational results demonstrate that the IIM policies are more cost-effective than the R,s,S policies, although the genetic algorithm has a speed advantage. Moreover, as compared with the R,s,S polices, the IIM polices have a lower possibility of product shortage, and thereby a higher service level for the patients, and a lower risk of product expiration. By implementing the IIM approaches, a healthcare system may also save storage space, in addition to having a lower total inventory cost. Sensitivity analyses are performed to derive managerial insights on the performance of the policies when the values of the key cost parameters change.

ANALISIS PERSEDIAAN BAHAN BAKU PT HAKAASTON MENGGUNAKAN METODE CONTINOUS REVIEW SYSTEM

Inventory control is a guarantee that the material to be used in the process must always be available at the minimum possible cost. PT HAKAASTON Sei Langsat is engaged in manufacturing asphalt concrete with asphalt and river stone which has not optimal inventory management, which is characterized by a shortage of raw materials when carrying out the production process and resulting in delays in fulfilling consumer demand. With this problem, a research on raw material inventory was conducted using the continuous review system method which aims to control raw material inventory better and optimally. After conducting analysis and calculations using a continuous review system, the optimal number of orders for asphalt is 44,037 Kg and river stone is 23,259 Kg, asphalt reorder point value is 22,665 Kg and river stone is 1,317,611 Kg, asphalt safety stock is 12,048 Kg and stone times, which is 719,394 Kg, while the total cost of inventory using the continuous review system method is Rp. 4,297,432,432, which is smaller than the total cost based on company policy, which is Rp. 5,408,267,366, and savings of Rp. 1,110,834,934 or 21%.

MANAJEMEN PERSEDIAAN BAHAN BAKU BAWANG PUTIH GORENG PADA UKM SOFIE LOCALFOOD DI KOTA PALU

Garlic Sofie Localfood is one of the businesses engaged in agro-industry that utilizes garlic as the main raw material. Sofie Localfood's fried garlic products still have difficulty in regulating the production process, due to delays in ordering raw materials, so SMEs buy raw materials elsewhere and require more costs and sometimes the raw materials are not as expected. Raw materials are one of the most important production factors because they support the smooth running of the production process. This study aims to find out how much economic raw material purchases (EOQ) for the supply of raw materials to SMEs Sofie Localfood, to find out how much safety stock (Safety Stock) to SMEs Sofie Localfood, to find out when is the right time for SMEs Sofie Localfood to do reordering (ROP) of raw material inventory, and to find out the total inventory cost (TIC) of raw materials at UKM Sofie Localfood, This research was conducted at UKM Sofie Localfood on Jalan Zebra IV, Lorong 1 No. 5 Palu City. The selection of this location was done purposively, with the consideration that Sofie Localfood is one of the businesses that produces garlic as the main raw material for making tempeh in Palu City. This research was conducted from April to June 2021. Respondents are owners and employees of UKM Sofie Localfood who were selected as sources of information in the study, the total number of respondents is 3 people. Based on data to be obtained from Sofie Localfood's business regarding raw material inventory management issues tempe, the data analysis used is Economic Order Quantity (EOQ), Safety Stock (Safety Stock), reorder (ROP) and total inventory cost (TIC). The results of this study indicate that the management of raw material inventory at SMEs Sofie localfood using the (Economic Order Quantity) method in JanuaryDecember 2020 an average of 31.17 kg/month. Safety stock (Safety Stock) of raw materials that is always available at UKM Sofie Localfood is 14.92 kg/month. The reorder point (reorder point) that SMEs Sofie Localfood must make in April-June 2021 is an average of 77.26 kg/month. The total cost of raw material inventory for garlic in the UKM Sofie Localfood is an average of Rp.58.157.86/month.

Penerapan Pengendalian Persediaan Bahan Baku Ban dengan Model Probabilistik dan Sistem Kuantitas Pemesanan Tetap

Inventory of raw materials is very important for the smooth production of the company and meet consumer demand for the company in market demand. The demand for tire production fluctuates and causes the demand for products not to need to be met to order, due to the shortage of raw materials. To solve the shortage of raw materials, the company holds special orders in consideration of savings in ordering the cost of ordering messages. To overcome the shortage of raw materials, the company holds special orders or sudden orders which will increase the cost of the message. The purpose of this study is to determine the optimum ordering of raw materials to minimize total inventory costs by using a probability model of raw material inventory control with a fixed order quantity system (Q method). From the results of research using the probabilistic model of inventory control method Q method, obtained the optimal order quantity (q*), reorder point (rop), and safety stock (ss) with total inventory costs more efficient compared to the total inventory costs of the company's current policies. what is to be achieved in inventory control is to minimize the cost of ordering, and the cost of savings to the company.

예산제약이 존재하는 다기간, 다제품 재고관리문제에서 강화학습 기법의 효율성 개선 방안 연구

This paper considers the use of reinforcement learning for a multi-period, multi-item inventory control problem with a budget constraint. In the problem, we decide the order quantities of multiple items considering budget constraints so as to minimizes the total inventory cost including inventory holding cost and backlog cost. The previous literature proposed a modified Q-learning that include an optimization model in the Q-learning procedure to handle budget constrained actions, but it lacks the scalability. To address this issue, this paper proposed a two-stage method: the Q-learning learns actions without considering the budget constraint in the first stage, and an optimization model adjusts the learned actions so as to satisfy the budget constraint in the second stage. Numerical study compares the performance of the proposed two-stage method with others such as a conventional Q-learning without the budget constraint and the modified Q-learning in the literature. The numerical experiments reveal that the proposed method significantly reduces the computation time without increasing the total inventory cost.

Pengendalian Persediaan Bahan Baku Penolong Menggunakan Metode Economic Order Quantity di Industri Makanan Olahan

CV. XYZ is a company engaged in food processing, it processes meat as the main raw material. Beef rollade is one of the products produced by CV. XYZ using "Fort Quarter" (FQ) beef as raw materials and auxiliary ingredients, i.e spices, eggs, onions, TVP (Texture Vegetable Protein) Red, and flour. TVP Red is an important auxiliary raw material in beef rollade production. A shortage of auxiliary materials for TVP Red during the production process will disrupt the process and if production continues, the product quality will decrease. Currently, the inventory policy carried out by CV. XYZ is to check the inventory of and auxiliary materials just before carrying out production activities so that if there is a shortage of auxiliary materials, new orders are made at that time. Therefore, the aim of this study is to determine the number of orders and the optimal frequency of ordering TVP Red using the EOQ method and determining the total cost of TVP Red inventory before and after using the EOQ method. Based on the results of calculations carried out using the EOQ, it can be concluded that the number of economical purchases of TVP Red is 1,007.6 Kg per order. With that number of purchases, the frequency of ordering by CV. XYZ is reduced to 13 times in one year. The difference in the frequency of these purchases is 25 times in one year. With purchase frequency of 13 times in one year, it can save the total inventory cost of Rp. 163.972,4.

Inventory Management with EOQ Method at “Nitra Jaya” Fashion-Making Company in Badung

Inventory management is an activity carried out by a company that is needed in making decisions, so that material needs for the needs of company activities both production and sales can be fulfilled optimally, with the smallest possible risk. Over-inventory is a waste because it causes storage and maintenance loads that are too high during storage in the warehouse. This research was conducted at Nitra Jaya which aims to determine the proper inventory management of the management system for Nitra Jaya using the EOQ (Economic Order Quantity) method. This study uses quantitative data and qualitative data obtained by conducting interviews with the company and observing the object under study. The results showed that Nitra Jaya inventory management was still not efficient. By using the conventionally applied method in 2019, the total inventory cost incurred was IDR 27,150,000. If Nitra Jaya uses the EOQ (Economic Order Quantity) method in 2019, the total inventory cost incurred is IDR 14.247.886, and the company can save IDR 12.902.114 (47.5%) The implication of this research is that it is expected to be able to provide advice to the owner of the Nitra Jaya to review the total cost of inventory more efficiently through the optimal quantity and frequency of purchasing raw materials, the company should apply the EOQ method in carrying out inventory management.

Inventory Policy for Retail Stores: A Multi-Item EOQ Model Considering Permissible Delay in Payment and Limited Warehouse Capacity

The retail industry such as minimarkets has many products consisting of several types of products that have expiration dates. Their warehouses have limited capacity, making it difficult to make decision about optimum inventory. Most of the suppliers will give permissible delay in payment, that can be used to increase income potential through earned by considering the risk of fines imposed if payments are exceeded and help companies raise capital before generating sales. These three factors must be considered when developing the inventory model. The purpose of this study is to develop a multi-item inventory model by considering perishable or damaged products, permissible delay in payment in limited warehouse. Model development is carried out in 2 stages. The first stage was the development of a multi-item EOQ model by considering product defects and permissible delay in payment. The second stage model is by adding a capacity constraint factor to the model. The results obtained are getting the optimal order quantity by considering the number of product types, product damage factors, late payments in limited warehouses, the best ordering policy can be found, and it is known that the total inventory costs to changes in parameters are good and sensitive to changes in percentage, interest percentage, payment allowances, and warehouse capacity through sensitivity tests.

An EOQ model for non-instantaneous deteriorating items with time-dependent demand under partial backlogging

This article discusses an economic order quantity model for non-instantaneous deteriorating items in which the demand is assumed to be a linear function of time over an infinite planning horizon. In addition, the salvage value associated with the deteriorated units is also considered. The shortages are allowed and partially backlogged. A mathematical model is framed to obtain the replenishment policy which aids the retailer to minimize the total inventory cost. The objective of this work is to minimize the total inventory cost and to find the optimal length of replenishment and the optimal order quantity. The theory developed in this article is illustrated using numerical examples. A computational algorithm is designed to find the optimal solution. Sensitivity analysis is carried out to study the changes in the effect on the optimal solutions and some managerial insights are obtained.

An inventory system with time-dependent demand and partial backordering under return on inventory investment maximization

In this article, we study an inventory system for items that have a power demand pattern and where shortages are allowed. We suppose that only a fixed proportion of demand during the stock-out period is backordered. The decision variables are the inventory cycle and the ratio between the initial stock and the total quantity demanded throughout the inventory cycle. The objective is to maximize the Return on Inventory Investment (ROII) defined as the ratio of the profit per unit time over the average inventory cost. After analysing the objective function, the optimal global solutions for all the possible cases of the inventory problem are determined. These optimal policies that maximize the ROII are, in general, different from those that minimize the total inventory cost per unit time. Finally, a numerical sensitivity analysis of the optimal inventory policy with respect to the system input parameters and some useful managerial insights derived from the results are presented.

The use of parametric programming and simulation-optimisation approaches for stochastic inventory control in the food markets under fuzzy deterioration rate

In this study, we address the stochastic inventory control problem of green vegetables deteriorating in a fruit and vegetable wholesaler. The problem is to re-order green vegetables periodically to meet demand of the green markets. The aim is to decide the order quantity and the order-up-to level for each period minimising the total inventory cost. In the fruit and vegetable wholesaler, a staff separates the fresh and non-fresh products to sustain freshness in the green vegetable crates. The behaviour of the wholesaler staff on selecting the non-fresh green vegetables is personal reasoning that fuzzy logic can help to deal with the uncertainty. Accordingly, we introduce a stochastic integer linear programming model accounting for the uncertain demand. We represent the deterioration rate indicated in the model by fuzzy numbers and transform the resulting fuzzy model into an α-parametric programming model. As a solution method, we propose a simulated annealing based simulation-optimisation algorithm. The models and the heuristic algorithm are applied to a case study that reflects the real settings of a food market in Turkey. The numerical analysis is conducted on the case study to understand the effect of the fuzziness on the solution quality and time under varying cost parameters and deterioration rates. As a result, the numerical analyses demonstrate that the proposed models allow us better to estimate the total costs and the waste quantity. The heuristic algorithm yields near-optimal solutions. The solutions approach approximately 3% difference on average for the medium and long term decisions. The heuristic algorithm results in significantly shorter computation times compared to the proposed model.

CONTROL OF RAW MATERIALS INVENTORY PROBABILISTIC MODEL USING MONTE CARLO SIMULATION AND DYNAMIC SYSTEM

Increasing efficiency and effectiveness is a fundamental problem for every company. Optimization of raw material inventory is an effort for this problem. PT XYZ is a company engaged in manufacturing various flavors of beverages, one of which is sugar. The level of sugar usage in each month is probabilistic and dynamic. PT XYZ's raw material inventory is determined based on field assumptions, causing a shortage or excess of raw material inventory. This study aims to determine the policy of raw material inventory P backorder model with the integration of Monte Carlo simulation and Dynamic System. The raw material inventory policy is determined based on the order time interval, safety stock, and maximum capacity and compares the actual total inventory cost with the Monte Carlo simulation. Dynamic system simulation is carried out to ensure that the P backorder model inventory policy can be applied. The results showed that the total inventory without Monte Carlo was better than the total cost of the Monte Carlo simulation of Rp198.846.582,98 with an order time interval of 0,30929 years, a maximum inventory capacity of 11149,8 kg and a safety stock of 4335,83 kg. From the results of the comparison using the one sample T-test, it was found that there was no statistical difference between the results of the dynamic system simulation and the results from the calculation of the P backorder model so that the P backorder model policy could be applied to PT XYZ to determine the minimum inventory cost.

Determination of the Inventory of Cassava Raw Materials UD Rezeky Baru Medan Based on the Economic Order Quantity (EOQ) Method

The need for an inventory control system basically arises because of problems faced by the company in the form of excess or shortage of company inventory. The EOQ (Economic Order Quantity) method is one of the inventory control methods used to determine the number of economic orders, namely the number of orders that meet the minimum total inventory cost. The purpose of this study was to determine the optimal amount of cassava raw material inventory at UD Rezeky Baru with the EOQ method and the comparison of the total cost of raw material inventory between costs according to the company and costs according to the EOQ method. Based on the results of calculations using the EOQ method, the optimal number of orders for cassava raw materials in 2019 is 18.722,62 kg. The total cost of raw material inventory using the EOQ method is Rp. 1.497.809,00, while according to the company, it is Rp. 9.467.640,00. The company can save on inventory costs by Rp. 7.969.830,00.