Economic batch quantity

Last updated

In inventory management, Economic Batch Quantity (EBQ), also known as Optimum Batch Quantity (OBQ) is a measure used to determine the quantity of units that can be produced at the minimum average costs in a given batch or product run. EBQ is basically a refinement of the economic order quantity (EOQ) model to take into account circumstances in which the goods are produced in batches. [1] [2] The goal of calculating EBQ is that the product is produced in the required quantity and required quality at the lowest cost. [3] [4] [5]

Contents

The EOQ model was developed by Ford W. Harris in 1913, but R. H. Wilson, a consultant who applied it extensively, and K. Andler are given credit for their in-depth analysis. Aggterleky described the optimal planning planes and the meaning of under and over planning, and the influence of the reduction of total cost. [6] [7] Wiendahl used Harris and Andler's equation for the determination of the optimal quantity. [8] Härdler took into account the costs of storage and delivery in determining the optimal batch quantity (EBQ). [9] Muller and Piasecki asserted that inventory management is explained only with the basics of an optimal quantity calculation. [10] [11]

Background

There are basically two options of planning the batch quantity: planning a large batch of a product in long intervals, and planning a small batch of a product in short intervals. [7]

The advantages of planning a large batch of product are that the price of ordering a large batch, administrative costs, costs of tests and shipping are lower, and there is a lower risk of interruption of production because of the large stock. The disadvantages of planning a large batch are that there is higher tied-up capital, and storage costs of product inventory are also higher. [12]

The advantages of planning a small batch of product are that there is less tied-up capital, storage costs of product inventory are low, and there is a higher flexibility if quantities change at suppliers and buyers. The disadvantages of planning a small batch are that there will be costs of frequent ordering, and a high risk of interruption of production because of a small product inventory. [12]

Somewhere between the large and small batch quantity is the optimal batch quantity, i.e. the quantity in which the cost per product unit is the lowest. [12]

Variables and assumptions

Cost per piece v/s Batch size Chart EBQ Cost - Batch size Chart.jpg
Cost per piece v/s Batch size Chart

In the EOQ model, it is assumed that the orders are received all at once. However, in the EBQ model, this assumption is relaxed. [13]

There are two types of costs: those which increase with the batch size such as working capital investment in materials and labor, cost of handling and storing materials, insurance and tax charges, interest on capital investment, etc., and those which decrease with the batch size such as cost (per unit) of setting up machines, cost of preparing paper work that enters and controls the production of the order, etc. These costs, i.e., (a) and (b) are plotted and added graphically (figure).

The figure graphs the holding cost and ordering cost per year equations. The third line is the addition of these two equations, which generates the total inventory cost per year. The lowest (minimum) part of the total cost curve will give the economic batch quantity as illustrated in the next section. This graph should give a better understanding of the derivation of the optimal ordering quantity equation, i.e., the EBQ equation.

Thus, variables Q, R, S, C, I can be defined, which stand for economic batch quantity, annual requirements, preparation and set-up cost each time a new batch is started, constant cost per piece (material, direct labor and overheads), inventory carrying charge rate per year, respectively.

Some assumptions have been made for calculating economic batch quantity. They are: [14]

Calculations

If  is the cost of setting up a batch,  is the annual demand, is the daily rate at which inventory is demanded,  is the inventory holding cost per unit per annum, and  is the rate of production per annum, the total cost function is calculated as follows: [13]

In this case the ordering cost,  is often the setup cost for production.

The EBQ is calculated as the point where the total cost is minimum as follows: [13]

Where  is the cost of setting up a batch,  is the annual demand, is the daily rate at which inventory is demanded, is the inventory holding cost per unit per annum, and is the rate of production per annum. [13] Compared to the EOQ equation, there is a factor d/p introduced. This is due to the fact that when we produce a component while it is used in downstream production at the same time, inventory levels will not reach the same peak as when we order the components from a supplier and receive the batch at a single point in time. For instance, if we produce two different components (with the same processing time) intermittently then d/p is 0.5.

It is evident from this equation that the economic batch quantity increases as the annual requirements or the preparation and setup costs increase that is, they are (not directly) proportional to each other. Similarly, it is also clear that the economic batch quantity decreases as the cost per piece and inventory carrying rate increase.

Example

Set-up cost = $20 per set-up, Annual requirements = 1000, Inventory carrying cost = 10% of value/year, Cost per part = $2 In this example, the factor d/p is ignored.

Therefore, the number of batches to be made for manufacturing the parts are 1000/447 = 2.24. Nearest, 2 batches can be made and therefore the modified EBQ = 1000/2 = 500 parts. [15] This rounding off only makes sense if we produce the item during exactly one year, and we do not carry over stock from one year to the next.

See also

Economic Order Quantity

Operations Management

Inventory Control

Related Research Articles

<span class="mw-page-title-main">Profit maximization</span> Process to determine the highest profits for a firm

In economics, profit maximization is the short run or long run process by which a firm may determine the price, input and output levels that will lead to the highest possible total profit. In neoclassical economics, which is currently the mainstream approach to microeconomics, the firm is assumed to be a "rational agent" which wants to maximize its total profit, which is the difference between its total revenue and its total cost.

Economies of scope are "efficiencies formed by variety, not volume". In economics, "economies" is synonymous with cost savings and "scope" is synonymous with broadening production/services through diversified products. Economies of scope is an economic theory stating that average total cost of production decrease as a result of increasing the number of different goods produced. For example, a gas station that sells gasoline can sell soda, milk, baked goods, etc. through their customer service representatives and thus gasoline companies achieve economies of scope.

<span class="mw-page-title-main">Break-even (economics)</span> Equality of costs and revenues

The break-even point (BEP) in economics, business—and specifically cost accounting—is the point at which total cost and total revenue are equal, i.e. "even". There is no net loss or gain, and one has "broken even", though opportunity costs have been paid and capital has received the risk-adjusted, expected return. In short, all costs that must be paid are paid, and there is neither profit nor loss. The break-even analysis was developed by Karl Bücher and Johann Friedrich Schär.

In economics, the marginal cost is the change in the total cost that arises when the quantity produced is incremented, the cost of producing additional quantity. In some contexts, it refers to an increment of one unit of output, and in others it refers to the rate of change of total cost as output is increased by an infinitesimal amount. As Figure 1 shows, the marginal cost is measured in dollars per unit, whereas total cost is in dollars, and the marginal cost is the slope of the total cost, the rate at which it increases with output. Marginal cost is different from average cost, which is the total cost divided by the number of units produced.

A limit price is a price, or pricing strategy, where products are sold by a supplier at a price low enough to make it unprofitable for other players to enter the market.

Economic Order Quantity (EOQ), also known as Financial Purchase Quantity or Economic Buying Quantity (EPQ), is the order quantity that minimizes the total holding costs and ordering costs in inventory management. It is one of the oldest classical production scheduling models. The model was developed by Ford W. Harris in 1913, but R. H. Wilson, a consultant who applied it extensively, and K. Andler are given credit for their in-depth analysis.

Cournot competition is an economic model used to describe an industry structure in which companies compete on the amount of output they will produce, which they decide on independently of each other and at the same time. It is named after Antoine Augustin Cournot (1801–1877) who was inspired by observing competition in a spring water duopoly. It has the following features:

The Stackelberg leadership model is a strategic game in economics in which the leader firm moves first and then the follower firms move sequentially. It is named after the German economist Heinrich Freiherr von Stackelberg who published Marktform und Gleichgewicht [Market Structure and Equilibrium] in 1934, which described the model. In game theory terms, the players of this game are a leader and a follower and they compete on quantity. The Stackelberg leader is sometimes referred to as the Market Leader.

<span class="mw-page-title-main">Continuous stirred-tank reactor</span> Type of chemical reactor

The continuous stirred-tank reactor (CSTR), also known as vat- or backmix reactor, mixed flow reactor (MFR), or a continuous-flow stirred-tank reactor (CFSTR), is a common model for a chemical reactor in chemical engineering and environmental engineering. A CSTR often refers to a model used to estimate the key unit operation variables when using a continuous agitated-tank reactor to reach a specified output. The mathematical model works for all fluids: liquids, gases, and slurries.

The economic lot scheduling problem (ELSP) is a problem in operations management and inventory theory that has been studied by many researchers for more than 50 years. The term was first used in 1958 by professor Jack D. Rogers of Berkeley, who extended the economic order quantity model to the case where there are several products to be produced on the same machine, so that one must decide both the lot size for each product and when each lot should be produced. The method illustrated by Jack D. Rogers draws on a 1956 paper from Welch, W. Evert. The ELSP is a mathematical model of a common issue for almost any company or industry: planning what to manufacture, when to manufacture and how much to manufacture.

The newsvendormodel is a mathematical model in operations management and applied economics used to determine optimal inventory levels. It is (typically) characterized by fixed prices and uncertain demand for a perishable product. If the inventory level is , each unit of demand above is lost in potential sales. This model is also known as the newsvendor problem or newsboy problem by analogy with the situation faced by a newspaper vendor who must decide how many copies of the day's paper to stock in the face of uncertain demand and knowing that unsold copies will be worthless at the end of the day.

The economic production quantity model determines the quantity a company or retailer should order to minimize the total inventory costs by balancing the inventory holding cost and average fixed ordering cost. The EPQ model was developed by E.W. Taft in 1918. This method is an extension of the economic order quantity model. The difference between these two methods is that the EPQ model assumes the company will produce its own quantity or the parts are going to be shipped to the company while they are being produced, therefore the orders are available or received in an incremental manner while the products are being produced. While the EOQ model assumes the order quantity arrives complete and immediately after ordering, meaning that the parts are produced by another company and are ready to be shipped when the order is placed.

Field inventory management, commonly known as inventory management is the function of understanding the stock mix of a company and the different demands on that stock. The demands are influenced by both external and internal factors and are balanced by the creation of purchase order requests to keep supplies at a reasonable or prescribed level. Inventory management is important for every other business enterprise.

Material theory is the sub-specialty within operations research and operations management that is concerned with the design of production/inventory systems to minimize costs: it studies the decisions faced by firms and the military in connection with manufacturing, warehousing, supply chains, spare part allocation and so on and provides the mathematical foundation for logistics. The inventory control problem is the problem faced by a firm that must decide how much to order in each time period to meet demand for its products. The problem can be modeled using mathematical techniques of optimal control, dynamic programming and network optimization. The study of such models is part of inventory theory.

The dynamic lot-size model in inventory theory, is a generalization of the economic order quantity model that takes into account that demand for the product varies over time. The model was introduced by Harvey M. Wagner and Thomson M. Whitin in 1958.

The Silver–Meal heuristic is a production planning method in manufacturing, composed in 1973 by Edward A. Silver and H.C. Meal. Its purpose is to determine production quantities to meet the requirement of operations at minimum cost.

The profit model is the linear, deterministic algebraic model used implicitly by most cost accountants. Starting with, profit equals sales minus costs, it provides a structure for modeling cost elements such as materials, losses, multi-products, learning, depreciation etc. It provides a mutable conceptual base for spreadsheet modelers. This enables them to run deterministic simulations or 'what if' modelling to see the impact of price, cost or quantity changes on profitability.

<span class="mw-page-title-main">Monopoly price</span> Aspect of monopolistic markets

In microeconomics, a monopoly price is set by a monopoly. A monopoly occurs when a firm lacks any viable competition and is the sole producer of the industry's product. Because a monopoly faces no competition, it has absolute market power and can set a price above the firm's marginal cost.

The base stock model is a statistical model in inventory theory. In this model inventory is refilled one unit at a time and demand is random. If there is only one replenishment, then the problem can be solved with the newsvendor model.

The (Q,r) model is a class of models in inventory theory. A general (Q,r) model can be extended from both the EOQ model and the base stock model

References

  1. A Dictionary of Accounting (4 ed.). Oxford University Press. 2010.
  2. Jonathan Law Dictionary of Business and Management (5 ed.). Oxford University Press. 2009.
  3. Heizer, J; Render, B (2001). Principles of Operations Management (6 ed.). Upper Saddle River: Prentice Hall.
  4. Fogarty, W D; Blackstone, H J; Hoffman, R T (1991). Production and Inventory Management (2 ed.). Cengale Learning, Stamford.
  5. Slack, N; Chambers, S; Harland, C; Harrison, A; Johnson, R (1995). Operations Management. London: Pitman Publishing.
  6. Hax, A C; Candea, D (1984). Production and Operations Management. Englewood Cliffs, New Jersey: Prentice-Hall.
  7. 1 2 Aggteleky, B (1990). Fabrikplanung. München, Wien: Carl Hanser Verlag.
  8. Wiendahl, H P (2008). Betriebsorganistion für Ingenieure. München, Wien: Carl Hanser Verlag.
  9. Härdler, J (2012). Betriebswirtschaftslehre für Ingenieure. München, Wien: Carl Hanser Verlag.
  10. Muller, M (2011). Essentials of Inventory Management (2 ed.). New York: Amacom.
  11. Piasecki, D J (2009). Inventory Management Explained: A Focus on Forecasting, Lot Sizing, Safety Stock, and Ordering Systems. Kenosha: Ops Publishing.
  12. 1 2 3 Berlec, T; Kušar, J; Žerovnik, J; Starbek, M. Optimization of a Product Batch Quantity. Slovenia: Faculty of Mechanical Engineering, University of Ljubljana.
  13. 1 2 3 4 Russell, R; Taylor III, R. Operations Management – Creating Value along the Supply Chain (7 ed.). John Wiley & Sons Inc.
  14. Tawari, S. Implementation of Economic Batch Quantity at Mutual Industries in Order to Increase Productivity and Reduce Effective Cost in A Given Batch or Product Run. India: Mechanical Engineering Department, Vishwakarma Institute of Information Technology.
  15. Sindhuja, S. "Production Planning and Control". Business Management Ideas.