Analysis Inventory Cost Jona Shop with EOQ Model

The purpose of this research is to determine and analyze the minimum order quantities and the supply cost through Economic Order Quantity (EOQ) Model without Stock Out, EOQ Model with Buffer Stock, and Robust Optimization. EOQ model without Stock Out is an inventory model with a fixed number of requests and a fixed period of demand so the goods are considered always available or there is no stock out. Whereas EOQ Model with Buffer Stock is an inventory model with uncertainty demand during the lead time that described with a uniform density function. Another model is Robust Optimization Model that is used for cases with uncertainty demand. The results showed that the minimum order quantities through EOQ Model without Stock Out and EOQ Model with Buffer Stock was almost the same value but the cost was more minimum with the EOQ Model with Buffer Stock. Whereas, through the Robust Optimization Model there are different minimum order quantities for each period with a minimum supply cost compared to the two previous models. This occurs in both types of Spuit, namely Spuit Terumo 3 mL and Spuit Terumo 5 mL.

Inventory management and transportation have been the principal areas of focus in industrial engineering and management for a long time. Inventory management attracts considerable attention in logistics and supply chain management today because new supply chain models have become more integrative and complex. New market forces have introduced many complex elements which affect the performance of the supply chain in general and inventory level in particular. Inventory decisions are high risk and high impact for supply chain management. Hence, this paper compiles all the derivations of classical deterministic lot size economic order quantity models and proposes a new method to verify the formula. Keyword: Inventory Management, Supply Chain Management (SCM), Economic Order Quantity (EOQ) I. INTRODUCTION At the very basic level any firm faces two main decisions concerning the management of inventory: When should new stock be ordered and in what quantities? With regard to the order quantity, that minimizes inventory related costs. The classical EOQ (economic order quantity) model remains the basic inventory model even when it is not applicable in real life business situations in most cases. In inventory related literature, the answer to the question of when to order is given with reference to the ROP (reorder point), and the point at which the replenishment order should be initiated so that the facility receives the inventory in time to maintain its target level of service. In the static and deterministic model, the ROP is the simple multiplication of the number of lead days and the daily demand. It means that every time the inventory falls to the ROP level, an order must be initiated. And the order quantity is given by the EOQ model which is based on cost minimization. Figure-1:~ A simple inventory model based on fixed demand and fixed lead time (1). The EOQ is the balance between order and holding costs attached with the inventory. The order cost is made up of fixed and variable costs, whereas the holding cost consist of costs of maintenance. The formula is: Q = √ (2CoD/Cc) Q is the order quantity per order, D is the demand per year Co is the fixed cost which the warehouse incurs every time it places an order Cc is the inventory carrying or holding cost per unit per year, and Notice that it highlights two important insights regarding the EOQ model. These are: 1. Optimum order size is a balance between the holding cost and the fixed order cost. 2. Total inventory cost is related with order size, but the relationship is not significant.

In this paper, economic order quantity (EOQ) models without shortages for single item and multi-items are presented. Here, the holding cost of the item is a continuous function of the order quantity. The costs involved in this model are imprecise in nature. The main contributions of this research are as follows: The proposed EOQ model is discussed in two cases by describing the model in an uncertain environment. In case-1, EOQ models with fuzzy parameters (like ordering cost, holding cost, and unit product cost) are considered. Here all the fuzzy parameters are represented by trapezoidal fuzzy numbers. The said EOQ model is carried out by using the signed-distance method. In case-2, EOQ models with interval parameters (like ordering cost, holding cost, unit product cost, and the total money investment for the quantities) are considered. This proposed model is solved by using interval linear programming problem (ILPP) technique based on the best and the worst optimum values of the objective function. Numerical examples are given to exemplify the proposed model and also the results of different models are compared.KeywordsEOQTrapezoidal fuzzy numberInterval numberSigned-distance methodInterval linear programming problem (ILPP)

The economic order quantity (EOQ) model has become an important instrument in inventory management to minimize costs by balancing ordering and holding costs. This study examines the alignment of the EOQ model with the principles of Maqasid Shari’a, including hifdzul din (protecting religion), hifdzul nafs (protecting the soul), hifdzul aql (protecting reason), hifdzul nasl (protecting descendants), and hifdzul maal (protecting property) and its relevance in the context of Islamic business. Qualitative data were collected through a literature review with a content analysis approach, then analyzed thematically to identify the relationship between EOQ characteristics and Maqasid Shari’a dimensions. The results of the study indicate that the EOQ model is in line with the five principles of Maqasid Shari’a, which include: 1) Hifdzul din: 2) Hifdzul nafs: 3) Hifdzul aql: 4) Hifdzul nasl: 5) Hifdzul maal: This study concludes that by integrating the EOQ model with Maqasid Shari’a, maslahah (common good) will be achieved in the form of economic efficiency and strengthening the ethical and social dimensions in business. The implications will encourage increased transparency, waste reduction, and environmental sustainability. These findings can be a conceptual basis for developing a holistic inventory management model following Islamic economics principles.

The purpose of this research is to see whether an Economic Order Quantity model can be used to reduce cost of inventory significantly in PT PQR, manufacturer of spring and sponge mattresses in Pekanbaru, Indonesia. The research was conducted on three main materials required in producing spring and sponge mattresses. Using Economic Order Quantity (EOQ) model to analyze historical demand on main materials, it is proven that with EOQ model the company can save by more than 45% from procuring and inventory costs of those materials. The research continues to forecast the sales demand to get the annual requirement of materials needed in 2014 and calculate the EOQ model again. The results show that, comparing with traditional practice done by company, EOQ model can reduce costs up to 118 million rupiah per year.

The presence of retail businesses in Indonesia has many positive impacts on the community, especially in improving the economy. The existence of buying and selling transactions involving suppliers, retailers, and the community as consumers can play a role in improving the national economy. Retail can be called a bridge for suppliers and consumers to meet their needs. The diversity of consumer needs requires retailers to provide a variety of products from many suppliers. Efforts that need to be made by retail businesses in order to minimize costs incurred are by controlling inventory. To prevent excessive expenditure, the inventory control method used is to apply the Economic Order Quantity (EOQ) model. The EOQ model can provide the optimum total inventory cost by adjusting the frequency of orders placed over a period of time. After obtaining the total inventory cost, the calculation of safety stock, reorder point, and maximum capacity can also be applied so that the inventory costs incurred can be minimal.

The effective supply chain scheduling is a crucial task in business management which can be determined by developing the optimum schedules. Here, this paper develops the optimum schedules using an EOQ model with dynamic demand pattern because in this era of globalization and dynamic environment the Economic Order Quantity (EOQ) model loses its importance when it is based upon the constant demand pattern. Therefore, it becomes indispensable to develop the EOQ model under an environment of dynamic demand pattern. Here, the dynamic demand pattern includes the relevant parameters which varies with time. The effects of such parameters are necessary to incorporate in determining the optimum schedules and hence the optimum inventory levels. Also, to establish a product in the market and to increase its customer base one can take the help of promotional efforts in the form of trade credit financing. This paper discusses the optimum scheduling for a part of supply chain system using an EOQ model where the demand is dynamic varies with time and one of the promotional effort in the form of a two-stage trade credit is considered. The applicability of the model can be well understood through the sensitivity analysis of the parameters and its managerial implications.

Through the investigation of an Economic Order Quantity (EOQ) model, it has been observed that the estimated inventory cost and starting time inventory cost are not necessarily the same. This arises as a result of the time gap in between the time of estimation and the starting time of the EOQ system, and a permissible delay in payment will affect the inventory total cost. Moreover, the political instability or uncertainty of a country (as well as the whole world) leads to a much more unstable situation in the present world economy. Thus, a change in inflation takes place, and the inflation rate is uncertain in nature. This study develops an EOQ model with a fuzzy inflation rate and fuzzy deterioration rate, and a delay in payment is also permissible. We have derived the corresponding fuzzy cost function, and the solution procedure has been explained with the help of a numerical example. A sensitivity analysis has also been carried out.

EES-EOQ model with uncertain acquisition quantity and market demand in dedicated or combined remanufacturing systems

This research aims to analyzing the MRP method to obtain the lowest inventory costs of product wine. The raw material planning system carried out by PT XYZ uses sales data from the PPIC division to order all raw materials at one time. Preparing MRP requires input in the form of an ind schedule through the netting, lotting (economic order quantity (EOQ), lot for lot (LFL)), and offsetting. The output of the MRP method is a plan for ordering raw material requirements based on lead time. This MRP method can provide improvements to PT XYZ through the formation of a master production schedule, ordering schedule, and reducing inventory costs. Comparing the company's inventory costs with the MRP method for wine raw materials produces savings of 15% per year, and EOQ is more economical. SiO2 raw material produces savings of 55% per year, and EOQ is more economical. Purifying enzyme raw materials produces savings of 41% per year, and EOQ is more economical. The MRP process is carried out at 28% annually, and EOQ is more economical. Fermented extract raw materials produce savings of 14% per year, and LFL is more economical

Price-sensitive demand for perishable items – an EOQ model

Deterministic Economic Order Quantity (EOQ) models have been studied intensively in the literature, where the demand process is described by an ordinary differential equation, and the objective is to obtain an EOQ, which minimizes the total cost per unit time. The total cost per unit time consists of a “discrete” part, the setup cost, which is incurred at the time of ordering, and a “continuous” part, the holding cost, which is continuously accumulated over time. Quite formally, such deterministic EOQ models can be viewed as fluid approximations to the corresponding stochastic EOQ models, where the demand process is taken as a stochastic jump process. Suppose now an EOQ is obtained from a deterministic model. The question is how well does this quantity work in the corresponding stochastic model. In the present paper we justify a translation of EOQs obtained from deterministic models, under which the resulting order quantities are asymptotically optimal for the stochastic models, by showing that the difference between the performance measures and the optimal values converges to zero with respect to a scaling parameter. Moreover, we provide an estimate for the rate of convergence. The same issue regarding specific Economic Production Quantity (EPQ) models is studied, too.

The rise of consumer rights has caused businesses to focus increasingly on product quality. The inability of businesses to identify defective items before selling them results in higher return costs, decreased sales revenue, damaged reputations, and decreased competitiveness. This study examines the economic order quantity (EOQ) model in which the retailer discovers defective goods among received products. Although retailers conduct quality inspections, the inspection process is imperfect. We assume that Type I and Type II inspection errors occur during product quality inspection and that the market demand rate is sensitive to Type II inspection errors. To improve inspection, the retailer invests capital to decrease Type II inspection errors. This study investigates the optimal order quantity and the power of the test to maximize total profit per unit time. Mathematical analysis is used to show the optimal solution exists. An algorithm is then developed to calculate the optimal solution. Finally, numerical examples demonstrate the solution process and sensitivity analysis with respect to major parameters is carried out.

This research aims to determine the role of the inventory management method, Economic Order Quantity (EOQ) in decision making for the amount of economic ordering and cost efficiency of raw material inventory. EOQ method is very effective applied to companies that have a high quantity of annual inventory. UD. NURISMA is a manufacturing company producing “krupuk uyel mentah” with annual demand of raw material is high enough, which is 3,423 sacks in 2016. This research was conducted at UD NURISMA for inventory cost efficiency and the determination of order quantity economical raw material inventory of “krupuk uyel mentah”. This research is a quantitative descriptive research and using raw material inventory data at UD. NURISMA which includes data on the quantity of raw material requirements, data of ordering cost and raw material storage data during 2016. This study compares raw material inventory management based on UD. NURISMA policy with EOQ inventory management.The result of this research is EOQ inventory management method is able to give efficiency of inventory cost equal to Rp 3,082,502, -. The cost efficiency is obtained from the difference between inventory cost based on UD NURISMA policy (Rp. 9.338.178,-), toward inventory cost with EOQ (Rp. 6.255.676,-). Researchers suggest UD. NURISMA to use the Economic Order Quantity (EOQ) method. Implementation of EOQ method provides benefits for the company to know how much raw materials to be ordered and when to make a re-order.

The classical economic order quantity (EOQ) model assumes that items produced are of perfect quality and that the unit cost of production is independent of demand. However, in realistic situations, product quality is never perfect, but is directly affected by the reliability of the production process. In this paper, we consider an EOQ model with imperfect production process and the unit production cost is directly related to process reliability and inversely related to the demand rate. In addition, a numerical example is given to illustrate the developed model. Sensitivity analysis is also performed and discussed.