Total Inventory Cost Research Articles

Penerapan Metode EOQ (Economic Order Quantity) dalam Pengendalian Persediaan Bahan Baku

The purpose of this study was to analyze raw material inventory control with the Economic Order Quantity (EOQ) method on CV. BJT with 47 Embroidery Sukabumi City. The research method used is descriptive quantitative to describe and describe the data. The data is processed using the EOQ method using the EOQ method to determine the total cost of inventory. The results show that there is a large difference if using the EOQ method, the savings are more efficient. The conclusion is that by applying the EOQ method, we can optimize raw material inventory by minimizing raw materials with increased inventory. 
 Keywords: Economic Order Quantity (EOQ), Raw Material Inventory

Mathematical modeling of inventory cost in a 3-tier supply chain with horizontal cooperation

Inventory together with the transport, location of the production factory, and storage represent important factors that influence the performance of a supply chain. It is thus important for organizations to maintain inventory for efficient and smooth running of their operations. Through cooperation, supply chain players at the same level of the market can work jointly to plan and execute supply chain operations, and achieve greater success than when acting in isolation. Accordingly, this work considers a 3-tier supply chain – Supplier, Manufacturer, and Distributor, and it develops a model for minimizing the cost of inventory across the 3-tiers with horizontal cooperation at the post-production inventory end of manufacturing tier only. A constrained mixed integer mathematical program was developed with the objective of minimizing total inventory cost across the three supply chain tiers. A test problem consisting of 3 suppliers, 3 manufacturers, 3 distributors, and 4 products was used to test the model; the resulting mathematical problem was solved using linear programming with and without post-production inventory horizontal cooperation scenarios. It was found that horizontal cooperation was of immense benefit to supply chain players, and offers great cost savings as against individual operation.

The Penerapan Metode Just In Time (JIT) Dalam Pengendalian Persediaan Budidaya Ikan Lele Untuk Meminimalkan Biaya Persediaan

Catfish farming is a business that is engaged in the fishing industry. An activity in which people raise catfish (including spawning, breeding, etc.) to be sold. Therefore, the just in time method is used to minimize costs by planning the inventory calculation of the cost of catfish cultivation needs such as seeds, marketing, raw materials so that costs are more optimal and market supplies more controlled. After analyzing the total cost of inventory in Pak Dedy Santoso catfish farming, it can be concluded that in the company's calculation method the level of raw material requirements is 6000 kg, with 12 times the quantity of delivery, the total cost of raw material inventory in catfish farming is Rp. 2,670. 750.00. Whereas in the calculation of the Just In Time system, namely delivery of 85 times with a total inventory cost of Rp. 289,684, - and it can be seen that the cost savings obtained are Rp. 2,381,066. Then about the tolerance value for defects, damage, loss, and others by 5%. At the inventory level of 6000 kg, assuming a tolerance level of 5%, it is known that the inventory in the company's calculation is 6,300 kg

Penerapan Metode Just In Time sebagai Alternatif Pengendalian Persediaan Bahan Baku Pada PT BEHAESTEX, Pandaan Pasuruan

This study aims to determine the most effective and cost-effective use of the yarn raw material inventory method at PT Behaestex, Pandaan, by comparing the conventional methods used in the company at this time with the Just In Time (JIT) method. The data used are the total inventory of yarn raw materials and data on purchasing raw materials for yarn at the PT Behaestex, Pandaan Company in 2020. This study uses a quantitative descriptive method so as to describe the data with numbers. From the analysis using the Just in time system, it can be concluded that the Just In Time system is more efficient in calculating the total inventory cost of approximately 87% than the conventional method used by the company today.Keywords: Inventory, Raw Materials, Cost and just in time (JIT).

A joint replenishment production-inventory model as an MMAP[K]/PH[K]/1 queue

In this paper we analyze a continuous review finite capacity production-inventory system with two products in inventory. With stochastic order quantities and time between orders, the model reflects a supply chain that operates in an environment with high levels of volatility. The inventory is replenished using an independent order-up-to (s, S) policy or a can-order (s, c, S) joint replenishment policy in which the endogenously determined lead times drive the parameters of the replenishment policy. The production facility is modeled as a multi-type MMAP[K]/PH[K]/1 queue in which there are K possible inventory positions when the order is placed and the age process of the busy queue has matrix-exponential distribution. We characterize the system and determine the steady state distribution using matrix analytic methods. Using numerical methods we obtain the inventory parameters that minimize the total ordering and inventory related costs. We present numerical comparisons of independent and joint replenishment policies with varying lead times, order quantities, and cost reductions. We further demonstrate the interplay between the two products in terms of lead times, order quantities and costs.

Multi-warehouse, multi-product inventory control model for agri-fresh products – A case study

Warehouses that operate under controlled micro-climates are necessary to reduce the deterioration of fresh produce, but they are also costly to operate. Developing an efficient operation regime for these premises while considering energy costs, demand, and harvesting requirements is crucial to managing the food supply chain sustainably and profitably. This paper proposes a method to develop an operation regime by solving a multi-period, multi-product, multi-warehouse inventory control optimization problem that originates from the management of agri-fresh products from an Australian company. We propose a mixed-integer quadratic programming model for this problem. A significant challenge is that each product has a specific deterioration rate over storage, which differs in each warehouse mode. Our model allows for two different operational modes for warehouses, each with different electricity consumption, affecting the time the products remain fresh. The objective function of the model minimizes the total inventory costs. The model provides the optimal inventory flow of each product, the optimal number of active warehouses, the optimal operational length of warehouses, and the optimal mode of warehouses in each period. We solve the model using Gurobi and integrate three other solution approaches based on model properties, which reduce the computational time by half. The model is tested using real data from the case study, an Australian agri-fresh company. The results indicate a reduction in total cost by 8% and quantity of product deterioration by 20%. We also investigate the impacts of variations in demand and supply caused by growing or shrinking markets in our case study under different scenarios and instance sizes of the problem and analyze the impact in solution times that are observed in practice.

An intuitionistic fuzzy inventory model with waste disposal using the triangular intuitionistic fuzzy numbers

In the present study, we formulate an inventory model with waste disposal cost under the intuitionistic fuzzy environment. To optimize the best inventory policy under the intuitionistic fuzzy environment, the alpha-cut approach is used for the defuzzification of all intuitionistic fuzzy decision variables. This study aims to reduce the total inventory cost and adjust the waste outcomes during the production processes to keep a clean and green climate, which will be cost-effective for any organization, both environmentally and economically. A numerical example is presented regarding the proposed intuitionistic fuzzy model to validate the methodology.

예산제약을 고려한 다기간 Newsvendor 문제에서의 Q-learning 기법 적용

This paper considers a multi-period, multi-item Newsvendor problem under budget constraints in which a decision-maker orders items with aims to minimize the total inventory cost including inventory holding cost and backlog cost. In this decision process, the order quantities are constrained by two types of budget constraint: periodic budget and flexible budget. The problem is formulated as an action-constrained Markov Decision Process (MDP). To overcome the dimensionality and ambiguity, we employed a Q-learning method for solving the MDP model. In particular, we modified the conventional Q-learning procedure to handle a constrained action space by imposing penalties for constraint violations or incentives for constraint satisfactions on Q-values. The penalties and incentives are obtained by solving a quadratic optimization problem included in the learning procedure. Numerical analysis compares the performance of the proposed Q-learning method with others such as EOQ (Economic Order Quantity), Q-learning without the budget constraint, and a heuristic method. The experimental results showed that the proposed Q-learning method lowers the total inventory cost while increasing the chance of satisfying the budget constraint.

COMPARISON OF EFFECTIVENESS INVENTORY CONTROL OF EOQ METHOD WITH COMPANY METHOD IN STEEL MATERIAL FABRICATION KRAKATAU POSCO

PT. Krakatau Posco, is the largest steel manufacturing company in Southeast Asia that produces slabs and plates. This study aims to compare the effectiveness of controlling inventory of steel material fabrication workshop with the EOQ method and compared with the current method of the company in an effort to prevent the unavailability of such steel material fabrication. Inventory control using the EOQ method is expected to provide solutions for inventory control, and optimal ordering in order to obtain savings for inventory costs (Total Inventory Cost) at PT. Krakatau Posco. The method used is an interview and take the necessary data, then conduct an initial analysis using the ABC method to clarify the data that has been carried out at PT. Krakatau Posco, controls inventory using EOQ, determines safety stock, ROP and maximum inventory. By controlling the ordering and inventory also expected to provide significant savings for the company, by reducing inventory costs (Total Inventory Cost). The conclusion of this research is the EOQ method is the right method for controlling steel raw material fabrication to meet the production and repair processes at PT. Krakatau Posco and with this method the results of total inventory costs are also more efficient.

Policy Making in Optimizing Inventory Control with Continous and Periodic Review Method at PT. XYZ

PT. XYZ is a company enganged in the garment sector that produces office uniforms, polo t-shirts and t-shirts with the highest demand for polo t-shirt products from lacos 20S Black cloth. Based on company data and the results of interviews with informants, it found that companies often eperience stockout and overstock of supplies of lacos 20S black cloth due to fluctuating demand. This study to control inventory by comparing the company method with the method of Continuous Review (s,S) System, (S,Q) System and Periodic Review (R,s,S) System, (R,S) System to obtain minimum total cost of inventory. Based on the calculation using the company method, the total cost of inventory is Rp 643.487.400 and the minimum total cost of inventory using the Continuous Review (s,Q) System method is Rp 635.880.585 with savings of Rp 7.606.815 and the percentage of cost reduction is 1,18%. The forecasting needs for April 2021 to March 2022 using the Continuous Review (s,Q) System method, the order quantity is 378 Kg and the reorder point is 133 Kg with a total inventory cost is Rp 767.415.089.

Analisis dan Perancangan ROP, EOQ, Safety Stock Sistem Pengendalian Persediaan Bahan Baku Pada Rumah Makan Bubur Ayam Citarasa

Inventory is the most crucial aspect in restaurant business, good control is needed so that operational activities can run smoothly. In ‘RM Bubur Ayam Citarasa’, the quantity of raw material inventory purchased is based on estimates and intuition so that the inventory costs incurred are not efficient. The purpose of this study is to find out the economical order quantity for each raw material, how much safety stock should be provided and when reordering should be done. The type of data used is quantitative data and is equipped with qualitative data which is then analyzed using the EOQ, Safety Stock and Reorder Point formula. As a result, the company could save Total Inventory Costs for it’s twelve raw materials up to Rp2,290,219 with the EOQ Method. In order for the quantity of raw material can be monitored properly, researcher designed a simple inventory application using Ms. Excel.

THE ANALYSIS OF CONTROL RAW MATERIAL INJECTION PHYTON IN THE IMPLEMENTATION OF ECONOMIC ORDER QUANTITY (EOQ) IN PT. VICTORY CHYNGLUH INDONESIA

This study aimed to determine the inventory control of Python Injection (IP) raw materials at PT. Victory Chyngluh Indonesia. The method used in achieving data analysis objectives is to use the Economic Order Quantity (EOQ) form. Research results with the total cost of inventory using company policy are Rp. 2,622,540,500, - after using the Economic Order Quantity (EOQ) method is Rp. 2,419,006.133,-, thus the company can save the cost of raw material inventory for Python Injection (IP) of Rp.203,534,367,-

Analysis Control Of Inventory Of Non Subsidy Fertilizer Merchandise With Economic Order Quantity (EOQ) Method In CV. Dohar Agro Mandiri

Economic Order Quantity (EOQ) is a mathematical model that determines the number of items that must be ordered to meet the projected demand, with minimized inventory costs. The types of costs to run the business cycle are storage costs and ordering costs. The purpose of this research is to analyze "Analysis of Non-Subsidized Fertilizer Inventory Control with Economic Order Quantity (EOQ) Method at CV. Dohar Agro Mandiri. The total inventory obtained using the EOQ method is 11,003 with a purchase frequency of 3 times. Using the EOQ method the company must reorder when the merchandise inventory is 1,015 zak, with the EOQ method the maximum inventory that the company must maintain is 12,018 per day. The total inventory cost of fertilizer merchandise inventory is 24,648. In other words, inventory control using the EOQ method can help companies achieve an optimal level of inventory ordering and ordering frequency.

The Establishment of Decision Making Support Tool for Inventory Control and Production Planning with Periodic Review System and Linear Programming Approach

PT. Mortars is an instant cement producer with many product variants. Some problems that PT. Mortars encountered are uncertainty of demand, limitation on production capacity, and inventory capacity, which caused product shortages and high inventory costs. The production scheduling process is produced manually so it requires a long time, relying on the ability and experience of the production planner which is vulnerable to mistakes. Therefore, new methods and tools are needed for inventory control and production scheduling to make sure goods are delivered to customer just in time while maintaining operational efficiency. Periodic review system (R,S) and (R, s, S) methods are proposed in this study to improve inventory parameters and reorder systems that have an impact on service levels and inventory costs. The tools are designed using Microsoft Excel software with solver add-ins functions and linear programming approaches to generate optimal production schedule decisions automatically. In order to determine the level of service and inventory costs generated by each method, a simulation is conducted by using the tools that have been made. The simulation of the existing method produces a service level of 98,64% and a total inventory cost of Rp. 1.167.160.494. The periodic review system (R, S) method resulted in increasing service level of 0,96% and lower inventory cost of Rp. 15.130.801 while the periodic review system (R, s, S) method resulted in increasing service level of 1,29% and a lower inventory cost of Rp. 448.653 compared to the existing method. The periodic review system (R, S) method produces the lowest inventory costs while the method (R, s, S) produces the highest service level compared to other methods.

Analysis Of Stock Control Of Raw Materials Of Dzohir Noodles In Bengkulu

This study aims to analyze the stock inventory control of Mie Dzohir's raw materials in Bengkulu. The analytical method used is Economic Order Quantity (EOQ), Reorder Point (ROP), Total Inventory Cost (TIC) and Safety Stock (SS). The results showed that to meet the raw material needs of 91,375 kg during the research period, from January 2020 to December 2020 (12 months), the number of economical purchases/EOQ of wheat flour raw materials that had to be made by the Mie Dzohir factory in Bengkulu was as much as 5,372 kg for each order with a purchase frequency of 17 times for a period from January 2020 to December 2020. Reorders or reorder points (ROP) can also be determined, namely reordering should be done when 345 kg of inventory is in warehouse, with a lead time of 1 days so as not to hamper the company's production process. The total inventory cost (TIC) can also be determined, namely the total cost of raw material inventory of Rp. 3.572.188, - therefore, it can save on inventory costs of Rp. 1.051.697,- .Safety stock (SS) of 95 kg which must be in the warehouse, this is intended therefore, there is no shortage of wheat flour raw materials if there is a delay in the delivery of raw materials.

An inventory hub location model for multi‐coal‐fired coastal power plants: a case study in Guangdong district

AbstractThe increasing demand for electric power is an established trend in China, of which coal power accounts for a large proportion. This paper proposes an inventory hub location model considering multi‐type coal to minimize the total transportation and inventory cost in a multi‐coal‐power supply chain. A second‐order cone programming method is adopted to convert the original model. The exact solutions of the small‐scale real case show that the model can greatly reduce the total costs by CPLEX. For real‐world large‐scale cases, a customized greedy randomized adaptive search simulated annealing algorithm is devised and tested to obtain near‐optimal solutions within a reasonable time. The research has strong practical guiding significance for the management of the thermal coal supply chain.

PENGENDALIAN PERSEDIAAN BAHAN BAKU MENGGUNAKAN METODE EOQ DAN MRP PADA CV. OZONE GRAPHICS DI MANOKWARI

This study aims to analyze the amount of banner raw material inventory in 2020, with the selected method, namely EOQ and MRP to get an economical amount of inventory on the next order. This study uses primary data from interviews and secondary data from inventory report data from CV. Ozone Graphics. The analysis used is Economic Order Quantity (EOQ) and Material Requirement Planning (MRP) with the Part Period Balancing (PPB) technique. The results of this study using the EOQ method the company will get an optimal inventory of 422.94 meters of Korean Flexy and 42.58 liters of Icontek ink, with the lowest total inventory cost of Rp. 3,571,694.39 Korean Flexy and Icontek ink of Rp. IDR 3,496,425.47. Meanwhile, with the MRP method, the results obtained are that the total cost of inventory is too high, namely Korean Flexy Rp 12,930,250 and Rp 17,034,520 Icontek ink. So that by using the EOQ method the company will get the optimal amount of inventory and can minimize inventory costs.

Inventory Management: Bi-objective Optimization Models for Mass Customization

In recent years, the problem of establishing the inventory levels in the manufacturing industry has considerably worsened due to the accelerated growth in demand for customized products, this behavior in the customers has created heterogeneous and unstable demands too difficult to forecast generating an increase in inventory levels. In response to this behavior, the strategy that companies have commonly used to offer a wide variety of products to meet this demand is Mass Customization. However, this response has created products with shorter life cycles significantly increasing the risks and costs in inventories due to deterioration, re-manufacturing, and obsolescence. Little attention has been paid to determining inventory levels when a company uses mass customization as its main production strategy. This paper develops two bi-objective optimization models to determine the optimal inventory levels for those industries that, due to the nature of the product, use mass customization to meet the needs of their customers. The performance of the models is compared with the performance offered by the traditional continuous review (Q,R) policy, the results show a significant reduction in total inventory costs while maintaining high levels of customer service level.

A New Approach for EOQ Calculation Using Modified Opportunity Cost

Introduction: Optimal inventory levels are necessary for a firm to avoid shortage/excess of an item. Shortage of an item leads to stock out conditions which results in loss of profit. When items are correlated with each other, stock out condition of one item may result in non purchase of its associated items also which, in turn, further brings down the profit. In this paper, this loss in profit is used to modify opportunity cost of an item resulting in its modified EOQ. Method: One illustrative example has been discussed which incorporates purchase dependencies in retail multi-item inventory management. The model discussed in this research paper will be motivational for researchers and inventory managers and provides a method for incorporating correlation among items while managing inventory. Result: The EOQs of items are estimated both by using traditional method and then by using modified opportunity cost (modeled as loss profit). Results show that in frequent item set A, B, D, EOQs of all three items increased when correlation among them is considered resulting in increase in profit. Conclusion: One of the major focus areas of inventory management is to determine when and how much quantity of items needs to be ordered so that total inventory cost can be minimized and profit of a firm can be maximized. However, while calculating the true value of an item and the profit it brings to the firm, it is very essential to analyze its effect on the sale of other items. Asso-ciation rule mining provides a way to correlate items by calculating support and confidence factor. Discussion: In inventory management system, for increasing the profit of a firm, EOQs of items need to be calculated in order to avoid shortage or excess of inventory. For explaining the approach a very small database is taken consisting of only 5 items and 10 transactions therefore the increase in profit is minimal however, when this approach applies on real database consisting of thousands of items and transactions, the increase in profit will be significant.

MODEL PERENCANAAN DAN PENGENDALIAN PRODUKSI DI INDUSTRI PENGOLAHAN BUAH CARICA (CARICA PUBESCENS)

The competition in the carica fruit processing industry is increasing, so that efforts are needed to increase production efficiency through good production planning and control (PPC). CV XYZ is one of the carica fruit processing companies which has PPC problems. PPC activities done intuitively and not systematically causing a decision in PPC is ineffective and production process is inefficient. Those problems can be resolved by developing a PPC model in accordance with CV XYZ’s business process. So, this research objective was to develop a PPC model at CV XYZ. The model consisted of four sub-models which were related to each other. The first sub-model was Sub-model of Demand Forecasting and the second sub-model was Sub-model of Carica Fruit Availability Forecasting. Those two sub-models used the Auto-regressive Integrated Moving Average (ARIMA). The third sub-model was Sub-model of Production and Packaging Planning using Integer Linear Programming (ILP). The fourth sub-model was Sub-model of Carica Fruit Inventory Control using Material Requirement Planning (MRP). PPC model can clarify the PPC system at CV XYZ and produce optimal plans. PPC model improves efficiency of total production cost up to 39.86% and total inventory cost up to 27.56%. Keywords: carica industry, model, optimal, production planning and control