Optimal Inventory Cost Research Articles

Material Requirement Planning of Choco Roll Product with Least Total Cost (LTC) and Least Unit Cost (LUC) Method at PT. XYZ

PT. XYZ is one of corporate company engaged in the snack industry. One of PT. XYZ fast moving product is Choco Roll. Choco Roll product have many forming raw material. There is around 20 raw material and packaging material to make 1 box of Choco Roll. Problem that aries at PT. XYZ is in the the supply of raw materials related to the scheduling of ordering raw materials. The company wants to store enough raw material inventory to be able to immediately fulfill all production processes, but this method is not effective and efficient because it will increase storage costs, expiration may occur, and there is a risk of price drops at any time. When a company wants to try to reduce costs by decrease the level of inventory of raw materials on hand, namely the inventory of raw materials that are already in the warehouse, but this condition will disrupt the production process if there are frequent shortages or stockouts of raw materials. Therefore to reduce the inventory cost, it needs to be make best planning in determining the number of ordered of raw material. The company must use a more scheduled raw requirements planning method to obtain a more optimal inventory cost. The purpose of this study is to determine the exact number quantity and order frequency to reduce inventory cost. This research uses lotting technique Least Total Cost (LTC) and Least Unit Cost (LUC) base on Material Requirement Planning (MRP) method. Based on the result of the Choco Roll demand from June 2022 to May 2023 obtained the total inventory cost of IDR 67,683.53 decrease by 25% to company real planning.

Analysis of Consumable Material Inventory Control in Brake System Company

A good raw material and consumables control planning system is important in the production process so that the process runs according to schedule and target. Brake system company is a manufacturing company engaged in brake systems. Concerning the control of consumable material, this company often experiences overstock in warehouses, causing an overrun in inventory costs and investment cannot develop. One of these conditions can be influenced by the ordering method applied by the company which is still not appropriate. The purpose of this study is to find out and provide proposed to companies related to the cost of consumable inventory by comparing the three methods of determining lots based on Fixed Order Quantity (FOQ), Economic Order Quantity (EOQ), and Fixed Order Quantity Proposed (FOQ Proposed) is the FOQ method combined with the Lot for Lot (LFL) principle to determine the method with the most optimal inventory cost. From the results of the study, it is known that the Proposed FOQ method has the lowest total inventory cost compared to the other two methods. The proposed FOQ approach could reduce inventory costs by up to one-third times the previous cost.

An Artificial Neural Network Method for Managing Inventory of A Fertilizer Company in Bangladesh

Business organizations are always facing uncertainties in demand, supply and inventories. For this, it is important for them to make the strategic plans to cope up with the uncertainty accordingly. To sustain, the business organizations must plan the future in such a way that the inventory cost, labor cost will be minimized and the utilization of time, financial resources and profit will be maximized. The optimum planning of resources also help the organizations to avoid wastage. A good forecasting technique can help the manager of a company to deal with the uncertainties. In this paper, we will work on such a planning fora fertilizer company in Bangladesh. To minimize the inventory cost, we will apply a new approach known as Artificial Neural Network (ANN), which is recently used for the problem of prediction and analyze the main characteristics of a system through an iterative training process. For this, we will first forecast the demand of fertilizer by using existing forecasting methods. We will then apply ANN for forecasting the demand of fertilizer of the company. We will also identify Economic Order Quantity (EOQ) to minimize total cost including inventory costs of the company. We use programming language MATLAB for analyzing different forecasting methods including ANN. Finally, we will use these results to find out the right forecasting technique for the fertilizer company with optimal inventory cost. Dhaka Univ. J. Sci. 69(3): 133-142, 2022 (June)

Decision-Making Optimization of Risk-Seeking Retailer Managed Inventory Model in a Water Supply Chain

Water retailer managed inventory is a classical and inevitable inventory management mode in present economic society. Stochastic models can more clearly explain demand uncertainty and are closely related to water supply chains. Risk preferences are widely valued in behavioral operation management. Related to the risk preferences in inventory management, the research on risk aversion is dominant, while risk-seeking is insufficient. Based on the model assumptions, the risk-seeking retailer’s optimal decision-making inventory model with stochastic demand in a water supply chain is studied. The risk-seeking retailer’s optimal inventory quantity, optimal inventory cost, supplier profit, retailer profit, and the profit of the entire water supply chain are derived. The validity of the equations is proved. The sensitivity analysis of the risk-seeking retailer’s optimal inventory decision-making is carried out. The risk level effects on the five dimensions, the retail price, wholesale price, unit shortage cost, unit inventory cost, and unit residual value, are displayed through numerical simulation. The optimal inventory quantity and optimal inventory cost of the risk-seeking retailer are obtained.

Impact of cost of substitution and joint replenishment on inventory decisions for joint substitutable and complementary items under asymmetrical substitution

In this paper, impact of cost of substitution and joint replenishment on inventory decisions for joint substitutable and complementary items under asymmetrical substitution has been studied. The phenomenon of substitution is considered in a stock-out situation and when items become out of stock due to demand then unfulfilled demand is asymmetrically substituted by another item. We formulate the inventory model mathematically and derived optimal ordering quantities, optimal total costs and extreme value of substitution rate for all possible cases. Moreover, pseudo-convexity of the total inventory cost function is obtained and the solution procedure is provided. Numerical example and sensitivity analysis have been presented to validate the effectiveness of the inventory model and substantial improvement in total optimal inventory cost with substitution with respect to optimal total inventory cost without substitution is seen.

Optimal Control of Multi-Supplier Inventory Management with Lead Time

In the current global competition, companies are required to save money in order to survive. One of the expenses that can be reduced is the cost of inventory control. To minimize these costs, we require a proper planning and management of the inventory. Ordering supplies should be performed at a certain time period, especially with uncertain demand. As such, the company must determine when to order at the suppliers and how many should be ordered. So there will be no excess inventory in the warehouse because of too much ordering or because of the inventory cannot meet demand due to late or too little order to suppliers. Consequently, in this research, a quadratic cost functional is used as the objective function in multi-supplier inventory management problem with different lead time. Optimal control theory, LQR (Linear Quadratic Regulator) is used to solve this problem. According to the simulation, we conclude that the smaller weight resulted in more optimal inventory cost.

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

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)

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

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.

OPTIMAL DECISION SUPPORT MIXTURE MODEL WITH WEIBULL DEMAND AND DETERIORATION

In this paper, the performance of an inventory model is explored with deteriorating items under imprecision environment where the demand follows a three-parameter Weibull distribution. Deterioration and holding cost is considered as a linear function of time. Fuzziness has been allowed to deal with imprecision. Mathematical observations of both crisp and fuzzy models have been illustrated to determine the optimal cycle time and optimal inventory cost. The demand distribution, deterioration rate and all costs of models are expressed as triangular, trapezoidal and pentagonal fuzzy numbers. Graded mean integration method is used for defuzzification. Numerical illustrations are provided to validate the applications of the model. Sensitivity analysis with useful graphs and tables are performed to analyze the variability in the optimal solution with respect to change in various system parameters. KEYWORDS: Weibull Demand, Triangular Fuzzy Number, Trapezoidal Fuzzy Number, Pentagonal Fuzzy Number, Graded Mean Integration MSC: 90B05

Purchasing Inventory Models for Deteriorating Items with Quadratic Demand

This paper deals with purchasing inventory replenishment policy for deteriorating items, considering the time-dependent quadratic demand and time-dependent backlogging. Two models were formulated and solved. First, it is for deteriorating items with quadratically time-dependent demand for deteriorating items. Second, quadratically time-dependent demand for deteriorating items and shortages. A mathematical model is developed to the fourth-order equation for each model. The optimal production lot size, which minimizes the total cost, is derived. Sensitivity analysis is carried out to demonstrate the effects of changing parameter values on the optimal solution of the system. Numerical examples are taken to illustrate the procedure of finding the optimal inventory cost, cycle time, and optimal lot size. The numerical experiment in this model was coded in Microsoft Visual Basic 6.0.

Inventory cost framework for managing the petroleum product reorder point and order quantity policies

This work developed the optimal inventory cost framework for managing the reorder-point and order quantity policies of a petroleum products service station experiencing frequent inventory outages. ...

An EOQ model with random disruption and partial backordering

Perfect quality of batches is an assumption in the classic economic order quantity (EOQ) model (of inventory management); however, in practice some disruptions may occur in a supply chain. This paper presents an EOQ model with random disruption and partial backorders. So, when shortage occurs (due to quality problems or normal shortages), some customers are willing to wait for delivery until the next period. There is a finite probability that batches may be defective so an ‘all or none’ policy is used after inspection of batches. The optimal inventory cost and the corresponding decision variables are studied. A solution method is proposed to optimise the inventory cost, and then two numerical examples and a sensitivity analysis are provided to illustrate the results.

EPQ Model for Trended Demand with Rework and Random Preventive Machine Time

Economic production quantity (EPQ) inventory model for trended demand has been analyzed with rework facility and stochastic preventive machine time. Due to the complexity of the model, search method is proposed to determine the best optimal solution. A numerical example and sensitivity analysis are carried out to validate the proposed model. From the sensitivity analysis, it is observed that the rate of change of demand has significant impact on the optimal inventory cost. The model is very sensitive to the production and demand rate.

Economic production quantity models for deteriorating items with rework and stochastic preventive maintenance time

Economic production quantity (EPQ) models for deteriorating inventory have been investigated by many researchers in recent years. In this paper, we develop EPQ models for deteriorating items with rework and stochastic preventive maintenance time. The models are solved using a search method, since a closed form solution cannot be derived. A numerical example and sensitivity analysis are provided to evaluate the models. The sensitivity analysis shows that the deteriorating cost has a significant effect on the optimal inventory cost; however, the production and the demand rate have the most significant effect on the optimal total cost and the optimal production up-time period.

A Stock Dependent Economic Order Quantity Model for Perishable Items Under Inflationary Conditions

Problem statement: In most of the earlier inventory models, effect of inflation has been ignored, which is playing pilot role in present environment. In this article, we have proposed an economic order quantity model for deteriorating items having stock dependent demand (whose demand varies with the stock) under the effect of inflation. Approach: Firstly, problem is framed in the form of linear differential equation model and then this model has been solved with general solution technique of linear differential equations. Using the solution the expression for total cost of inventory has been obtained. Results: Using total cost equation an optimal order quantity is obtained and convexity of various costs is also studied. This model helps retailer to decide his economic order quantity for deteriorating items having stock dependent demand. The consideration of effect of inflation makes this model more relevant for present business environment. Conclusion: The convexity of various costs proves the validity of this model. The effect of inflation with two different rates is also studied in tables below considering both constant as well as stock dependent demand. The graph of these tables shows that the optimal inventory cost increases with increase in number of cycles it increases rapidly in starting but becomes stable for large number of cycles. The proposed model can be extended in several ways. For instance, we may generalize the model to allow for shortages, quantity discounts, time value of money, finite replenishment rate, permissible delay in payments and others.

Improving agility of supply chains using base stock model and computer based simulations

PurposeThe purpose of this paper is to deal with the application of the stochastic inventory model to the three‐tier supply chain and verify the values obtained by mathematical model in physical simulation.Design/methodology/approachThe paper investigates three‐stage serial supply chain with stochastic demand and fixed replenishment lead‐time. Inventory holding costs are charged at each stage, and each stage may incur a consumer backorder penalty cost charged by primary supplier to secondary supplier. The customer‐demand follows Poisson distribution. The base stock model is implemented for inventory control at both suppliers. Physical simulation is then designed in such a way that it satisfies all the assumptions for mathematical model. Simulation is run to verify the values obtained from mathematical model.FindingsComputer simulation is designed to include all the assumptions made by mathematical model. Hence, mathematical base stock model and computer simulation model are comparable. Demand follows Poisson distribution in both cases. The backorder cost and inventory holding cost are calculated in each phase of simulation and summarized. The paper infers that the total inventory cost is optimum in phase II, in which reorder point is same as that calculated by mathematical model. In phase I, total inventory cost is more than that of phase II because of backorders. In phase III, excess inventory increased the total cost. Thus, the values obtained from mathematical model produce optimal inventory cost. Base stock model is effective when the demand is not deterministic and service factor assumed in mathematical model is 0.9, which is quite acceptable. Base stock model assumes replenishment order quantity as 1 and the total inventory cost decreases with replenishment lead time. Base stock model is beneficial for supply chains having short replenishment lead time. Computer simulation results indicate that discrete event simulations can be used to model stochastic systems like organizational supply chains and to validate the results from mathematical models.Originality/valueThe paper offers a review of simulation work aiming to support improvement of agility in the supply chain.