• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.11 no.2
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• pp.47-56
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• 1985

This paper considers a two-product three-facility production planning model, where facility 1 produces product 1 to satisfy its own market requirements and supplies input to facility 2, and facility 2 requires another input from facility 3 (outside supplier). The objective is to determine the optimal production amount in each period in order to satisfy the dynamic demands on time, which minimizes the total cost of production and storage. The set-up cost is incurred jointly from the multi-facility operations.

• Journal of the Korean Operations Research and Management Science Society
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• v.9 no.2
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• pp.15-22
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• 1984

A deterministic multiproduct, facility-in series multiperiod production planning model is analyzed, where each period demand for the product of a facility appear in a fixed proportion of that for the product of the immediately following facility. The model considers concave production and inventory costs, which can depend upon the production in different facilities. No backlogging is allowed. It is shown that the model is represented via a single source network, which facilitates development of efficient dynamic programming algorithms for computing the optimal production schedule.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.2
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• pp.89-97
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• 2012

This paper considers a manufacturer with a two-station make-to-stock and make-to-order serial production system. The MTS facility produces a single type of component and provides components for the MTO facility that produces customized products. In addition to the internal demand from the MTO facility, the MTS facility faces demands from the spot market with the option of to accept or reject each incoming demand. This paper addresses a joint component inventory rationing and batch production control which maximizes the manufacturer's profit. Using the Markov decision process model, we investigate the structural properties of the optimal inventory rationing and batch production policy, and present two types of heuristics. We implement a numerical experiment to compare the performance of the optimal and heuristic policies and a simulation study to examine the impact of the stochastic process variability on the inventory rationing and batch production control.

• 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.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.291-298
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• 2018

Supplier selection for energy production facility is a multi-criteria decision-making problem and is of strategic importance for cost efficiency of synthetic fiber production company. The purpose of this paper is to present an approach to select best energy production facility for a synthetic fiber production company. Toward this, we derived criteria to evaluate the energy production facility and develop an Analytic Network Process model to help decision makers set priorities on multiple criteria while considering both qualitative and quantitative aspects of the problem. The application of the proposed approach indicates that it can be successfully applied to facilitate the decision making process for selecting the best supplier of the energy production facility.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.171-178
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• 2010

The purpose of this research is to develop a standard model for the compilation of production results in molding business to establish the informatization system for the production facility among informatizadon projects which can generate the performance of medium and short term introduction of the project in implementing the system to small and medium industry. The theory on the development method for the standardization of informatization for production facility in molding business applies PSDM (Production System Development Method) for which a number of researches were already done while developing a standardization model by standardizing two processes of raw material demand/supply management and making sum total for production quantity which are main processes for production management process. On the basis of the result of this research, small and medium companies in molding business and relevant specialized IT companies which desire to establish production facility informatization systems will be able to establish more efficient system by applying standardized model, and the result of research will enable to facilitate the establishment of the system for them while providing reliability of the system. Through the application of the result of this research, it will be possible to accomplish the elimination of unreasonable factors in production process, the enhancement of product quality and the saving of production cost.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1169-1172
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• 2002

This paper presents the development of an expert system for monitoring and control of an oil production facility. The objectives of developing an expert system for the oil production facility are to monitor the Important processing parameters in different sections of the facilities and to control battery operations in real time. By providing consistent, fast, and reliable decision support to operators, the expert system can be used for automated monitoring and control of a petroleum production facility located south of Regina in Saskatchewan, Canada. The system was implemented in Visual Basic 6.0.

• Industrial Engineering and Management Systems
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• v.11 no.2
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• pp.170-175
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• 2012

In this paper, a procedure using a genetic algorithm (GA) and a heuristic local search (HLS) is proposed for solving facility rearrangement problem (FRP). FRP is a decision problem for stopping/running of facilities and integration of stopped facilities to running facilities to maximize the production capacity of running facilities under the cost constraint. FRP is formulated as an integer programming model for maximizing the total production capacity under the constraint of the total facility operating cost. In the cases of 90 percent of cost constraint and more than 20 facilities, the previous solving method was not effective. To find effective alternatives, this solving procedure using a GA and a HLS is developed. Stopping/running of facilities are searched by GA. The shifting the production operation of stopped facilities into running facilities is searched by HLS, and this local search is executed for one individual in this GA procedure. The effectiveness of the proposed procedure using a GA and HLS is demonstrated by numerical experiment.

• Journal of the Korean Operations Research and Management Science Society
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• v.10 no.2
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• pp.15-23
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• 1985

A multi-product multi=facility production planning model is in which known demands must be satisfied. The model considers concave production costs and piecewise concave inventory costs in the introduction of production capacity constraints. Backlogging of unsatisfied demand is permitted. The structure of optimal production schedules is characterized and then used to solve an illustrative numerical problem.