• Korean Journal of Agricultural Science
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• v.31 no.2
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• pp.149-160
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• 2004

This study had carried out an analysis of leaf tobacco production cost by cost items, growing stages, and farm sizes per 10a to provide the basic data for determination of the purchasing price of leaf tobacco by KT&G. Considering the survey results of 12 tobacco farm households, the composition rates of production cost by items revealed as 7-10% for land service, 5-22% for depreciation, 13-25% for material costs, 50-65% for labour cost respectively. The production cost of leaf tobacco by growing stages were shown as 15.3% in nursery bed period, 32.3% in main growing period in field, 30.8% in harvesting period and 21.6% in packing period. The magnitude of wage expenditure was appeared as harvesting stage, packing stage, growing stage on main field and nursery bed stage in order. The amount of material costs were revealed as the growing stage in main field, harvesting stage, nursery bed stage and packing stage respectively. The production costs of leaf tobacco per 10a by farm sizes were shown as 1,615,879won for small farm, 1,446,896won for medium farm and 1,454,408won for large farm respectively. The production cost of leaf tobacco had shown decreasing tendency according to increasing farm sizes. To promote the international market competitiveness of leaf tobacco producing farms, labour saving production technologies and cost effective farm size to decrease tobacco production cost should be developed.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.27-46
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• 1992

This paper considers an (r, Q) policy for operation of a multipurpose facility. It is assumed that whenever the inventory level falls below r, the model starts to produce the fixed amount of Q. The facility can be utilized for extra production during idle periods, that is, when the inventory level is still greater than r right after a main production operation is terminated or an extra production operation is finished. But, whenever the facility is in operation for an extra production, the operation can not be terminated for the main production even though the inventory level falls below r. In the model, the demand for the product is assumed to arrive according to a compound Poisson process and the processing time required to produce a product is assumed to follow an arbitary distribution. Similarly, the orders for the extra production is assumed to accur in a Poisson process are the extra production processing time is assumed to follow an arbitrary distribution. It is further assumed that unsatisfied demands are backordered and the expected comulative amount of demands is less than that of production during each production period. Under a cost structure which includes a setup/ production cost, a linear holding cost, a linear backorder cost, a linear extra production lost sale cost, and a linear extra production profit, an expression for the expected cost per unit time for a given (r, Q) policy is obtained, and using a convex property of the cost function, a procedure to find the optimal (r, Q) policy is presented.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.8
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• pp.1209-1215
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• 2015

Since lamb is a commodity, producers cannot control the price of the product they sell. Therefore, managing production costs is a necessity. We explored the study of elasticities as a tool for basing decision-making in sheep production, and aimed at investigating the composition and elasticities of lamb production costs, and their influence on the performance of the activity. A representative sheep production farm, designed in a panel meeting, was the base for calculation of lamb production cost. We then performed studies of: i) costs composition, and ii) cost elasticities for prices of inputs and for zootechnical indicators. Variable costs represented 64.15% of total cost, while 21.66% were represented by operational fixed costs, and 14.19% by the income of the factors. As for elasticities to input prices, the opportunity cost of land was the item to which production cost was more sensitive: a 1% increase in its price would cause a 0.2666% increase in lamb cost. Meanwhile, the impact of increasing any technical indicator was significantly higher than the impact of rising input prices. A 1% increase in weight at slaughter, for example, would reduce total cost in 0.91%. The greatest obstacle to economic viability of sheep production under the observed conditions is low technical efficiency. Increased production costs are more related to deficient zootechnical indexes than to high expenses.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.20-32
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• 1995

This paper is concerned with the economic selection of both the lower limit and the process mean for a continuous production process. Consider a production process where items are produced continuously. All of the items are subject to acceptance inspection. The items for which the measured values of the quality characteristic are larger than the lower limit are accepted, and those smaller than the lower limit are rejected and excluded from shipment. The process mean may be set higher to reduce the costs incurred by imperfect quality. Using a higher process mean, however, results in a higher production cost when production cost is an increasing function of the quality characteristic. Assuming that the quality characteristic is normally distributed with known variability, cost models are constructed which involve production cost, cost incurred by imperfect quality, rejection cost, and inspection cost. Methods of finding optimal values of the lower limit and the process mean are presented and numerical examples are given.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.110-117
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• 2012

The demand for facility used in producing multi-products is changed dynamically for discrete and finite time periods. The excess or the shortage for facility is occurred according to difference of the facility capacity size and demand for facility through given time periods. The shortage facility is met through the outsourcing production. The excess facility cost is considered for the periods that the facility capacity is greater than the demand for the facility, and the outsourcing production cost is considered for the periods that the demand for facility is greater than the facility capacity. This paper addresses to determine the facility capacity size, outsourcing production products and amount that minimizes the sum of the facility capacity cost, the excess facility cost and the outsourcing production cost. The characteristics of the optimal solution are analyzed, and an algorithm applying them is developed. A numerical example is shown to explain the problem.

• The Journal of Fisheries Business Administration
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• v.46 no.3
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• pp.129-141
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• 2015

Because land based aquaculture is restricted by high investment per rearing volume and control cost, good management planning is important in Land-based aquaculture system case. In this paper master production planning was made to decide the number of rearing, production schedule and efficient allocation of water resources considering biological and economic condition. The purpose of this article is to build the mathematical decision making model that finds the value of decision variable to maximize profit under the constraints. Stocking and harvesting decisions that are made by master production planning are affected by the price system, feed cost, labour cost, power cost and investment cost. To solve the proposed mathematical model, heuristic search algorithm is proposed. The model Input variables are (1) the fish price (2) the fish growth rate (3) critical standing corp (4) labour cost (5) power cost (6) feed coefficient (7) fixed cost. The model outputs are (1) number of rearing fish (2) sales price (3) efficient allocation of water pool.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.67-74
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• 1989

This paper considers single-product production and inventory management problem where cumulative demands up to each time period are mutually independent random variables(known) having continuous probability distributions and the associated cost-minimizing production schedule (when to produce and how much to produce) need be determined in rolling horizon environment. For the problem, both the production cost and the inventory holding and backlogging costs are included in the whole system cost. The probability distributions of these costs are expressed in terms of random demands, and utilized to exploit a solution procedure for a production schedule which minimizes the expected unit time system cost and also reduces the probability of rist that, for the first-period of each production cycle (rolling horizon), the cost of the "production" option will exceed that of the "non-production" one. Numerical examples are presented for the solution procedure illustration.cedure illustration.

• Journal of the Korean Regional Science Association
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• v.12 no.2
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• pp.21-36
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• 1996

This thesis focused on the extent of the area-by-area gap of the unit production cost that should be taken into account without exception in supply of the local public goods production cost. With the advent of the local autonomy era, what should be considered in the local governmen's production of the local public goods are the government's fiscal capacity and the environmental difference that shows up in accordance with the area's characteristics. Though with the same level of the fiscal capacity, an occurrence of environmental difference will lead inevitably to the different level of actual supply of the local public goods. The method of analysis used in this thesis was first to bring out implicit price, to combine this with induced expenditure function, to separate demand function parameter and cost function parameter, and then to analyzed the impact of environmental variables on the production cost. The environmental variables were set on the basis of the ones that affected expenditure per person of the public goods. The analysis was conducted in distinction of city areas and county areas. The results showed that, in cases of cities, more production cost of the public goods was in presence in urban areas and in areas where there was sluggish development. In other words, distinction could be drawn between areas where there was a large consumption of production cost resulting from poor environmental sparked by slow development and those where additional costs were required due to population concentration caused by a certain level of accomplished development. In the meantime, in cases of county areas, the results were around the same. However, a comparison between city areas and county ones told that overall difference between city areas was not that big in the production cost while that in county areas was large enough. In times ahead, in implementation of grant-in-aid scheme, production cost index for local public goods could be used as it was written in consideration of environmental characteristics of areas concerned.

• Korean Journal of Agricultural Science
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• v.39 no.2
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• pp.227-242
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• 2012

Accurate estimation of milk production cost is very important for dairy farmers in establishing strategies for business management (e.g. planning a program for milk production, deciding the size of business and investment, determining the milk price for sale). Since the estimated cost of milk production is used as an important index to determine the basal price of milk in Korea, there has been much interest and debate on the method used to estimate milk production cost among the stakeholder. This study was thus carried out to identify problems in the current methodology for estimating cost of milk production, and to find a better way to improve it. We propose several alternatives and better ways to improve the current method for estimating cost of milk production. Estimation of the income and cost per head should be based on the number of cattle converted to grown cows. Cost estimation per liter of milk should be made for both whole milk and 3.4% milk fat corrected milk. The value of purchased cows and raised replacement heifers should be the same as their market value. The productive life span of cows should be less 4 years, and the terminal or salvage value of cows needs to be 30 to 40% less than her initial value. When calculating depreciation of cows over the productive life span, however, the salvage value should be 0 or 1 Korean won. On calculating labor costs, the farm labor wage corresponding to the average wage of nonfarm industrial workers should be assumed. Beside of these, better estimation procedures for other items are also given. The proposed methods from this study should improve the accuracy of estimation of milk production cost and help to achieve consensus among the stakeholder.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.117-126
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• 2015

This paper is to analyze an integrated production and inventory model in a single-vendor multi-buyer supply chain. The vendor is defined as the manufacturer and the buyers as the retailers. The product that the manufacturer produces is supplied to the retailers with constant periodic time interval. The production rate of the manufacturer is constant for the time. The demand of the retailers is constant for the time. The cycle time of the vendor is defined as the elapsed time from the start of the production to the start of the next production, while the cycle times of the buyer as the elapsed time between the adjacent supply times from the vendor to the buyer. The cycle times of the vendor and the buyers that minimizes the total cost in a supply chain are analyzed. The cost factors are the production setup cost and the inventory holding cost of the manufacturer, the ordering cost and the inventory holding cost of the retailers. The cycle time of the vendor is investigated through the cycle time that satisfies economic production quantity with the production setup cost and the inventory holding cost of the manufacturer. An integrated production and inventory model is formulated, and an algorithm is developed. An numerical example is presented to explain the algorithm. The solution of the algorithm for the numerical examples is compared with that of genetic algorithm. Numerical example shows that the vendor and the buyers can save cost by integrated decision making.