• Korean Management Science Review
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• v.31 no.3
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• pp.13-26
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• 2014

This paper considers an integrated one-vendor multi-buyer production-inventory model where the vendor manufactures multiple products in lot at their associated finite production rates. In the model, it is allowed for each product to be shipped in lot to the buyers even before the whole product production is not completed yet. Each product lot is dispatched to the associated buyer in a number of shipments. The buyers consume their products at fixed rates. The objective is to the production and shipment schedules in the integrated system, which minimizes the total cost per unit time. The total cost consists of production setup cost, inventory holding cost and shipment cost. For the model, an iterative optimal solution procedure with shipment consolidation policy incorporated. It is then tested through numerical experiments to show how efficient and effective the shipment consolidation policy is.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1-7
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• 2003

This paper considers an Integrated one-vendor multi-buyer production-inventory model where the vendor manufactures multiple products In lot at Her associated finite production rates In the model. It is allowed for earth product to be shipped In lot to the buyers before the whole product production is not completed yet. Each product lot is dispatched to the associated buyer In a number or shipments. The buyers consume their products at fixed rates. The objective is to the production and shipment schedules in the Integrated system. which minimizes the mean total annual cost per unit time. The mean total annual cost consists or production setup cost inventory holding cost and shipment cost. For the model, an Iterative optimal solution procedure with shipment consolidation policy incorporated is derived. It is then tested through numerical experiments to show how efficient and effective He shipment consolidation policy is.

• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.107-120
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• 2010

In today's uncertain economic environment, the evaluation of safety for investment alternatives is of practical importance in manufacturing companies. This paper examines a method of quantitatively evaluating profitability and risk for multiple alternatives using the total-cost unit-cost domain. The paper assumes such factors as unit sales price, sales and production volume, unit variable cost, fixed cost, and yield for each alternative. The paper incorporates the relationship between production capacity and demand, distinguishing between cases of production capacity surplus and shortage for each year over the entire planning horizon. The paper investigates the case in which the values of each factor independently move in the direction of decreasing profit each year, and clarifies the procedure of comparing safety among multiple investment alternatives on a single consolidated total-cost unit-cost domain. The difficulty of the problem lies in the method of consolidating multiple total-cost unit-cost domains into a single domain since the combination of years of capacity surplus and shortage depends upon the change values in each factor under consideration. A systematic method of evaluating profitability as well as risk is presented, and the validity of the proposed method is verified using a numerical example.

• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.631-640
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• 2019

Thorium ($^{232}Th$) is four times more abundant than uranium in nature and has become a new important source of energy in the future. This is due to the ability of thorium to undergo the bombardment of neutron to produce uranium-233 ($^{233}U$). The aim of this study is to investigate the production cost of thorium oxide ($ThO_2$) resulted from the thorium extraction process. Four main parameters were studied which include raw material and chemical cost, total capital investment, direct cost and indirect cost. These parameters were justified to obtain the final production cost for the thorium extraction process. The result showed that the raw material costs were $63,126.00 - $104,120.77 (0.5 ton), $126,252.00 - $178,241.53 (1.0 ton), and $1,262,520.00 - $1,782,415.33 (10.0 tons). The total installed equipment and total cost investment were estimated to be approximately $11,542,984.10 and $13,274,431.715 respectively. Hence, the total costs for producing 1 kg $ThO_2$ were $6829.79 - $6911.78, $3540.95 - $3592.94, and $501.18 - $553.17 for 0.5, 1.0, and 10.0 tons respectively. The result concluded that with higher mass production, the cost of 1 kg $ThO_2$ would be reduced which in this scenario, the lowest production cost was $$501.18kg^{-1}$-$$553.17kg^{-1}$ for 10.0 tons of $ThO_2$ production.

• Journal of the Korea Safety Management & Science
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• v.5 no.4
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• pp.169-185
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• 2003

Recently many researchers contributed to the understanding of Quality Control System, but the use of economics in the design of quality assurance system is limited in treatment of the relationship between the average incoming quality level (or average process quality level) of the incoming lot and the average outgoing quality level of this lot. In this study, a traditional concept of sampling inspection plan for the quality assurance system is extended to a consideration of economic aspects in total production system by representing and analyzing the effects between proceeding and succeeding production process including inspection process. This approach recognizes that the decision at each manufacturing process (or assembly process), is to be determined not only by the cost and the average outgoing quality level of that process, but also by the input parameters of the cost and the incoming quality to the succeeding process. By analyzing the effects of the average incoming and outgoing quality, manufacturing or assembly process quality level and sampling inspection plan on the production system, mathematical models and solution technique to minimize the total production cost for a general product manufacturing system with specified average outgoing quality limit are suggested.

• 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.

• The Journal of Fisheries Business Administration
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• v.8 no.2
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• pp.1-19
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• 1977

The results analyzed of the actual state of medium size two-boat trawler fishery based on the cost expended in 1975 are as follows: According to the calculation of interest, the total cost of this fishery comes to ￦ 55,353,807, and in this account, the production cost comes to ￦ 49,747,383 (89.9%) and the material cost comes to ￦ 27,027,662(48.8%), the labour cost comes to ￦ 10,381,013 (18.8%) the expenses, ￦12,338,708(22.3%) and commision and interest comes to ￦ 5,606,424 (10.1%). As above the fishery comes is 90% of production cost for the expense of production. The ratio of cost element to the total cost 100 is as follow: Fuel: 23.6%, allocation: 14.3%, fishing gear: 14.1%, boat repair: 13.0%, fish box: 8.5%, ice: 14.1%, commission: 6.9%, food cost: 4.5%, interest: 3.2%, transportation fee: 2.8%, consumption: 2.6%, tax: 2.5%, depreciation: 2.4%, administrative expense: 1.6%. The unit cost of catches to each box, including the interest, cames to ￦ 2,167 and not calculating the interest it comes to ￦ 2,098. The cost production to each kg comes to ￦ 114 including interest, without interest, it comes ￦110. When the production cost comes to 90.6%, it comes to 9.4% of total revenue. The reason which this fishery brings low income is that the boats are almost old and semi-diesel engine is used. So, fuel expense and repaire expenses needs too much. Acconding to above this fishery needs to replace new boat and new engine. And new are for this fishery needs to bring under cultivation in order to bring good income with the new method for this fishery. Specially, this fishery brings low income from July to September because of its rest from labour. And so, the expenses, item, and account of money, and the trust money the cost element are not showed in August.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.153-158
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• 2010

This study presents a single machine scheduling algorithm to minimize total cost(lateness cost, earliness cost and failure cost) by controlling machining speed. Generally, production scheduling uses the information of process planning and machining speed is not changed at production scheduling. And failure cost is not consider for scheduling algorithm. Therefore, the purpose of this study is to consider the change of machining speed for efficient production scheduling. And performance criteria for algorithm considers total cost. Especially, failure cost of product by increasing machining speed is considered.

• Korean Management Science Review
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• v.32 no.4
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• pp.19-28
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• 2015

This study presents a mathematical programming model to develop production planning in the manufacturing processes for photovoltaic silicon ingots and wafers. The model is formulated as a linear programming model that maximizes total growth margin, which is composed of production cost, inventory cost, shortage cost, and sales profit while considering the constraints associated with the production environments of photovoltaic materials. In order to demonstrate the utility of the model for production planning, we run operations for a planning horizon of a year for a case study. When the primary results of this mathematical programming are compared with the historical records, the model could have resulted in the considerable increase of the total growth margin by effectively reducing inventory cost if a decision maker had employed the model as a decision support system with perfect information for sales demand.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.1
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• pp.157-165
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• 1998

This paper considers the single-product production and transportation problem with discrete time, dynamic demand and finite time horizon, an extension of classical dynamic lot-sizing model. In the model, multiple freight container types are allowed as the transportation mode and each order (product) placed in a period is shipped immediately by containers in the period. Moreover, each container has type-dependent carrying capacity restriction and at most one container type is allowed in each shipping period. The unit freight cost for each container type depends on the size of its carrying capacity. The total freight cost is proportional to the number of each container type employed. Such a freight cost is considered as another set-up cost. Also, it is assumed in the model that production and inventory cost functions are dynamically concave and backlogging is not allowed. The objective of this study is to determine the optimal production policy and the optimal transportation policy simultaneously that minimizes the total system cost (including production cost, inventory holding cost, and freight cost) to satisfy dynamic demands over a finite time horizon. In the analysis, the optimal solution properties are characterized, based on which a dynamic programming algorithm is derived. The solution algorithm is then illustrated with a numerical example.