• 한국해양학회지
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• v.11 no.2
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• pp.57-63
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• 1976

It was attempted to analyze the sensitivity of the oil prospect place named MARIA which placed inside Gulf of Alaska. For the analysis, P6031090, ECOANA( computer) which installed in the head office, Shell Oil Co was used and the data needed for computer programming were 1) Unit of Production data 2) Production Schedule 3) Total Gross Yearly Expenses and 4) Total Gross Capital and so on. The important data among the computer output 1) PVPAT (Present Value After Tax): $1,167,077,500 2) Payout After Tax: 3.14 Years (256,284,810 BBL Production) 3) Earning Power: 42% (After Tax) 4) PVPAT/BBL : $1.22 5) Capital/BBL : $2.00. On the other hand, the effect acted upon PVPAT with varying the Platform cost, Facility cost, Pipeline cost and Well cost was observed in comparion with the basic for range from 50% to 200%. Resultantly, the order was 1) Pipeline cost 2) Facility cost 3) Well cost 4) Platform cost for range form 100% to 200%. This project was completed by the contract with Shell Oil Co., and the geological data needed for this analysis were given by the head office and the development project started from Jan. 1976.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.3
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• pp.71-79
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• 1993

Dynamic production planning problems are to determine the optimal production times and production quantities of product for discrete finite periods. In previous many researches, the solutions for these problems have been developed through the algorithms using dynamic programming. The purpose of this research is to suggest the new algorithm using linear programming. This research is to determine optimal production quantities of product in each period to satisfy dynamic for discrete finite periods, minimizing the total of production cost and inventory holding cost. Cost functions are concave, and no backlogging for product is allowed. The new algorithm for capacity constrained problem is developed.

• The Journal of Fisheries Business Administration
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• v.9 no.2
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• pp.59-89
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• 1978

The analyzed results of the actual state of stow net fishery based on the cost expended are as follows. According to the calculation of interests, the total cost of this fishery comes to ￦38,010,653 and in this account, the production cost comes to ￦35,477,198(93.3%), the material cost, 14,567,239(38.3%), the labour cost, 12,740,274(33.5%), the expenses, ￦8,169,685(21.5%), the commision and administration expenses, 2,533,455(6.7%). The expenses for this fishery are paid out as production costs, and the expenses for sale and administration expenses are the lowest of them, and the 93% of expenses are paid out as production costs. The ratio of cost element to 100% is as follow. The wages, 28.4%, fuel, 15.2%, repair, 11.6%, deprecation, 9.5%, fishing gear, 8.7%, ice, 6.1%, container(box for fish), 5.2% administration expenses, 5.2%, food, 3.5%, ship grar, 3.2%, public welfare, 1.7%, commision for sale, 1.5%, insurance for crew, 0.2%, taxes, 0.2%. This fishery is managed with the larger fishing boat than it was and so, it demands better crews with higher wages. In the former fishery, the search for fishing ground is very difficult with long navigation and great fuel consumption. when the weak fishing gears are used, the expenses for their repair and for their gears are greatly paid out. The unit costs of catches to each box come to ￦2.807(￦187 each kg). As the ratio of cost of sales comes to 86.7%and the ratio of interests comes to ￦5,850,812(13.3%), and so the net profit comes to 13.3% of total profits. According to above the ratio of cost of sales is shown as a universal validity, Asthe total expenses comes to 86.7% to the money on sales in the break-even point, the break-even point comes to ￦26,209,168 Accordingly for the profit control the account of production should be raised, and by the saving method of expenditure the break-even point should be brought down for the development of total profits.

• Horticultural Science & Technology
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• v.34 no.6
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• pp.840-844
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• 2016

Quinoa (Chenopodium quinoa Willd.) is a grain crop with high nutritional value. The leaves and sprouts of quinoa can also be consumed either raw or cooked, providing considerably nutritional value as well as high antioxidant and anticancer activities. This study was carried out to obtain basic data to assist in the practical design of a plant factory with artificial lighting for the cultivation of quinoa as a leafy vegetable. We estimated the energy content of the quinoa and the electrical energy required to produce this crop. The yield was 1,000 plants per day, with a planting density and light intensity of $0.015m^2$ ($15{\times}10cm$) and $200{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, respectively. The total number of plants, cultivation area, and electricity consumption were estimated to be 25,000, $375m^2$, and $93,750{\mu}mol{\cdot}s^{-1}$, respectively. White fluorescent lamps were used at a power of 20.4 kW from 1,857 fluorescent lamps (FL, 55 W), and the cost for electricity was approximately 1,820 dollars (exchange rate of $1 = 1,200 won) per month. For a daily harvest of 1,000 plants per day in a closed plant factory, the estimated light installation cost, total installation cost, and total production cost would be 15,473, 46,421, and 55,704 dollars, respectively. The calculated production cost per plant, including labor costs, would be 27 cents for the 25-day cultivation period, with a marketable ratio of 80%. Considering the annual total expenses, income, and depreciation costs, the selling price per plant was estimated to be approximately 56 cents.

• Journal of the Korean Operations Research and Management Science Society
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• v.1 no.1
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• pp.151-170
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• 1976

There are many cases of production processes which intermittently produce several different kinds of products for stock through one set of physical facility. In this case, an important question is what size of production run should be prduced once we do set-up for a product in order to minimize the total cost, that is, the sum of the set-up, carrying, and stock-out costs. This problem is used to be called scheduling of multiple products through a single facility in the production management field. Despite the very common occurrence of this type of production process, no one has yet devised a method for determining the optimal production schedule. The purpose of this study is to develop quantitative analytical models which can be used practically and give us rational production schedules. The study is to show improved models with application to a can-manufacturing plant. In this thesis the economic production quantity (EPQ) model was used as a basic model to develop quantitative analytical models for this scheduling problem and two cases, one with stock-out cost, the other without stock-out cost, were taken into consideration. The first analytical model was developed for the scheduling of products through a single facility. In this model we calculate No, the optimal number of production runs per year, minimizing the total annual cost above all. Next we calculate No$_{i}$ is significantly different from No, some manipulation of the schedule can be made by trial and error in order to try to fit the product into the basic (No schedule either more or less frequently as dictated by) No$_{i}$, But this trial and error schedule is thought of inefficient. The second analytical model was developed by reinterpretation by reinterpretation of the calculating process of the economic production quantity model. In this model we obtained two relationships, one of which is the relationship between optimal number of set-ups for the ith item and optimal total number of set-ups, the other is the relationship between optimal average inventory investment for the ith item and optimal total average inventory investment. From these relationships we can determine how much average inventory investment per year would be required if a rational policy based on m No set-ups per year for m products were followed and, alternatively, how many set-ups per year would be required if a rational policy were followed which required an established total average inventory inventory investment. We also learned the relationship between the number of set-ups and the average inventory investment takes the form of a hyperbola. But, there is no reason to say that the first analytical model is superior to the second analytical model. It can be said that the first model is useful for a basic production schedule. On the other hand, the second model is efficient to get an improved production schedule, in a sense of reducing the total cost. Another merit of the second model is that, unlike the first model where we have to know all the inventory costs for each product, we can obtain an improved production schedule with unknown inventory costs. The application of these quantitative analytical models to PoHang can-manufacturing plants shows this point.int.

• Asian-Australasian Journal of Animal Sciences
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• v.7 no.1
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• pp.49-55
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• 1994

This study was conducted to compare the of rearing native and cross-bred dairy cows and returns received from them. For this purpose, 144 cows of 132 household from 24 villages were randomly selected. of them, 96 were native cows and 48 were cross-bred cows. The study revealed that among the structure of cost components, labour charge occupied the major share in the total cost of milk production per litre. The total cost of rearing native and cross-bred cows was Tk. 14,155 and Tk. 19,854 per annum, respectively. The average net cost of milk production per litre was Tk. 14.12 for native cows and Tk. 0.52 and for cross-bred cows were Taka 3.40. The benefit-cost ratio of milk per litre was higher (1:1.33) in cross-bred cows than native ones (1:1.04). The study further showed that in comparing with bulk line cost, the price of milk per litre received by the farmers was higher in cross-bred cows than native cows. Therefore, the study recommends dairying with cross-bred cows as encouraging and viable commercial enterprise in Banfladesh.

• The Journal of Fisheries Business Administration
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• v.7 no.1
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• pp.27-41
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• 1976

The results analyzed of the actual state of the stow net fisheries based on the cost expended in 1975 areas follows; The total cost of this fisheries will be 1, 672, 238 won; the production cost, 1, 588, 060 won (95%) ; the material cost in proportion to total cost (100%)408, 480won (24.4%);the labour cost, 1, 006, 480 won (60.2%) ; the expenses, 173, 100won(10.4%)and the commission and the interest payment, 84, 178won(5%). As above the commission and the interest payment doesn't need to be paid much, but only production cost should be paid in case of small scale inshore fisheries. The cost per unit of caches (per Kg) becomes 12 won, the ratio cost of sales (83.4%), the ratio of profit, 16.%. According to the adove, in case of the powered vessel; it shows a tendency of spending too much expenses owing to excessive payment of oil. And in case of nonpowered vessels, it shows a tendency of spending less expenses but still get much gains, due to the fact that the commission and the interest payment are less, and none is paid for fuel procurement.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.95-100
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• 2020

Machines and facilities are physically or chemically degenerated by continuous usage. One of the results of this degeneration is the process mean shift. The representative type of the degeneration is wear of tool or machine. According to the increasing wear level, non-conforming products cost and quality loss cost are increasing simultaneously. Therefore a periodic preventive resetting the process is necessary. The total cost consists of three items: adjustment cost (or replacement cost), non-conforming cost due to product out of upper or lower limit specification, and quality loss cost due to difference from the process target value and the product characteristic value among the conforming products. In this case, the problem of determining the adjustment period or wear limit that minimizes the total cost is called the 'process mean shift' problem. It is assumed that both specifications are set and the wear level can be observed directly. In this study, we propose a new model integrating the quality loss cost, process variance, and production volume, which has been conducted in different fields in previous studies. In particular, for the change in production volume according to the increasing in wear level, we propose a generalized production quantity function g(w). This function can be applied to most processes and we fitted the g(w) to the model. The objective equation of this model is the total cost per unit wear, and the determining variables are the wear limit and initial process setting position that minimize the objective equation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.269-277
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• 1998

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 proceding/succeeding production process including inspection. This approach recognizes that the decision to be made at one manufacturing process (or assembly process) determine not only the cost and the average outgoing quality level of that process but also 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/assembly quality level and sampling inspection plan on the production system, mathematical models and solution technique to minimize the total production cost for a single product manufacturing system with specified average outgoing quality limit (AOQL) are suggested.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.119-125
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• 1998

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 / succeeding production process including inspection. This approach recognizes that the decision to be made at one manufacturing process (or assembly process) determine not only the cost and the average outgoing quality level of that process but also 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 / assembly quality level and sampling inspection plan on the production system, mathematical models and solution technique to minimize the total production cost for a single product manufacturing system with specified average outgoing quality limit(AOQL) are suggested.