• Journal of Korean Institute of Industrial Engineers
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• v.5 no.1
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• pp.1-6
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• 1979

This paper discusses an application of discrete variable Servo Theory to the analysis of the effectiveness of production-inventory control system which uses exponential smoothing as a specific forecasting technique by establishing a new model which consists of such three departments as production planning, production, and inventory. The objective of the new production-inventory model is to keep the production to the optimal level of minimum production cost in production planning problem for obtaining, the stability of inventory subject to demand variation. On this basis, the dynamic characteristic of the system with the change of the parameters is clarified by the numerical analysis. The results of the numerical analysis show the effect that is obtained by the simultaneous stability of production and inventory as soon as possible.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2007.05a
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• pp.114-118
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• 2007

The space for production, such as studios and control rooms, is a space for TV program production, which is the main function of broadcast. A block planning for such space should be carefully designed, because it can significantly affect the efficiency of production, as well as future productivity and the development and expandability of production. From the results of comparative analysis of 7 local terrestrial broadcasters built since the late 1990s, this study will. propose an ideal block planning for the future construction of local terrestrial broadcasters. Also, the results can be used a basic data when constructing new buildings for local broadcasters.

• Korean Management Science Review
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• v.30 no.1
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• pp.25-41
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• 2013

This paper presents a supply chain framework with the ODM (Original Design Manufacturing)-OEM (Original Equipment Manufacturing) hybrid production of textile industry in FTA (Free Trade Agreements) environments between Korea and other countries. The proposed supply chain framework with ODM-OEM hybrid production is a unique supply chain that has both domestic production with non-tariff advantages in FTA environment and oversea production with low labor costs. To investigate the validity of the proposed supply chain, we first construct its strategic profit model and supply chain planning and then show that each member of supply chain network-yarn manufacturer, fabric manufacturer, and apparel manufacturer-can maximize their own profits without conflicts among the members. The efficiency of the ODM-OEM hybrid production system is analytically verified in comparison with the general OEM and ODM production model using profit models. Comprehensive numerical examples are provided to illustrate the advantages of the proposed system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.29
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• pp.23-29
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• 1994

In a newly developed production control system, a safety control ought to be included as a means of ensuring a more rational control system for achieving efficiency. Such a system does not hold any meaning in itself unless accompanied with appropriate ways to make it practicable. A firm would have a number of function groups. Each of these groups would have specific functions or duties to perform. Their production activities would be planned at the level of departmental management. The planning will take such forms as production, quality and safety planning, and so far as each department would order the line from its own standpoint, scientific production activities could not be expected. All the programmes must, therefore, be integrated and coordinated by a supervisor.

• IE interfaces
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• v.18 no.2
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• pp.148-157
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• 2005

The manufacturing industry with Make-to-Order production system is difficult to decide the standard information for the product and the demand is variable to estimate. In this paper, we concerned with the process planning method using data mining in the manufacturing industry with Make-to-Order environment. The subject of our study is the industry transformer plant which is received an diverse order of customer and then produced the product. Currently, process planning method is classified the standard information by hand based on the acquired knowledge through the experience. The standard information stored the various information, such as work sequence, time and so on. This process planning method needs an experts which possesses the field experience for several years. For the product specification which is varied in each order, current process planning method is not efficient due to need many times To solve this problem, we extract the information using data mining process for each processing time, and then construct the knowledge base. We propose a method which is the process planning of the industry transformer product in Make-to-Order environment using the knowledge base.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.159-168
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• 2015

Aggregate Production Planning determines levels of production, human resources, inventory to maximize company's profits and fulfill customer's demands based on demand forecasts. Since performance of aggregate production planning heavily depends on accuracy of given forecasting demands, choosing an accurate forecasting method should be antecedent for achieving a good aggregate production planning. Generally, typical forecasting error metrics such as MSE (Mean Squared Error), MAD (Mean Absolute Deviation), MAPE (Mean Absolute Percentage Error), and CFE (Cumulated Forecast Error) are utilized to choose a proper forecasting method for an aggregate production planning. However, these metrics are designed only to measure a difference between real and forecast demands and they are not able to consider any results such as increasing cost or decreasing profit caused by forecasting error. Consequently, the traditional metrics fail to give enough explanation to select a good forecasting method in aggregate production planning. To overcome this limitation of typical metrics for forecasting method this study suggests a new metric, WACFE (Weighted Absolute and Cumulative Forecast Error), to evaluate forecasting methods. Basically, the WACFE is designed to consider not only forecasting errors but also costs which the errors might cause in for Aggregate Production Planning. The WACFE is a product sum of cumulative forecasting error and weight factors for backorder and inventory costs. We demonstrate the effectiveness of the proposed metric by conducting intensive experiments with demand data sets from M3-competition. Finally, we showed that the WACFE provides a higher correlation with the total cost than other metrics and, consequently, is a better performance in selection of forecasting methods for aggregate production planning.

• Journal of the Korean Society of Safety
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• v.22 no.6
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• pp.74-80
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• 2007

In manufacturing industry, machining technology for metal cutting processes has been considered traditional and economic dimensions such as production cost, production time and quality of a final product. However, owing to governmental regulations and the change of owner's cognizance, the safety of the workers becomes important in those fields. In this paper, the operation planning system developed as a key component of CAPP(Computer Aided Process Planning) system is introduced for milling operations. The main issue in the system is to determine the cutting conditions in achieving a balanced consideration of productivity and worker's safety. For this reason, the system performs the modification process of standard cutting conditions to satisfy those requirements. Related to machining safety in metal cutting, representative and habitual mistakes that operators perform without considering carefully the characteristic of machine or work piece are described and then the detailed algorithm and functions of the developed system is introduced and discussed.

• Korean Management Science Review
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• v.1
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• pp.35-45
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• 1984

This paper deals with the case study of the establishment of decision supporting system in shipbuilding industory. Facts or information of shipbuilding, sales, finance, production strategic planning in shipbuilding industry are considered. General transportation model for shipyard production schedule is formulated, and shipbuilding demand forecasting scheme is also introduced. This paper shows the several methods of DSS in shipbuilding industry. But production schedule strategic planning system by OR technique is emphasized. For the realization of DSS in shipbuilding industry, another efforts (data gathering and programming etc.) should be given on the basis of these methods.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.3
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• pp.69-78
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• 2001

This paper presents a process and operation planning system and an NC code post-processor for effective machining of press dies for production of cars. Based on the machining feature, major parts of press dies are categorized into 15 groups and a standard process plan is defined for each group. The standard process plan consists of a series of processes where a process is defined as a group of operations that can be done with one setup. Details such as cutting tools, cutting conditions, and tool paths are decided at the operation planning stage. At the final stage of process and operation planning, the NC code post-processor adjusts feedrates along the tool path to reduce machining time while maintaining the quality. The adjustment rule is selected based on the machining load estimated by virtual machining.

• Journal of the Korea Safety Management & Science
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• v.6 no.3
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• pp.131-140
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• 2004

The company was focusing on production which was partial mission rather than acquiring the information of customer in intensive process industry. The company accepted loss which is from over-production, losing of opportunity. After changing to web environment, supply chain is more complicated and need of customer is more various. As a result the company hard works on controlling production rates, production quantities in production area and gathering exact information which is about available resource and available quantities. Cooperated demand planning have to get decreasing of inventory, improving of customer service in supply chain management. Specially demand planning that considers allocation of capacity is executed in Iron-Industry. Demand planning must be classified by customer, region and supply position level.