• Journal of Korean Institute of Industrial Engineers
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• v.35 no.1
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• pp.15-39
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• 2009

Advanced planning and scheduling (APS) refers to a manufacturing management process by which raw materials and production capacity are optimally allocated to meet demand. APS is especially well-suited to environments where simpler planning methods cannot adequately address complex trade-offs between competing priorities. However, most scheduling problems of APS in the real world face both inevitable constraints such as due date, capability, transportation cost, set up cost and available resources. In this survey paper, we address three crucial issues in APS, including basic scheduling model, job-shop scheduling (JSP), assembly line balancing (ALB) model, and integrated scheduling models for manufacturing and logistics. Several evolutionary algorithms which adapt to the problems are surveyed and proposed; some test instances based on the practical problems demonstrate the effectiveness and efficiency of evolutionary approaches.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.506-512
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• 2006

In this paper, we propose a lot-sizing and scheduling problem that seeks to minimize the sum of production cost and inventory cost over a given planning horizon while considering idle state of a machine in a batch production system. For this problem, we develop an integer programming model. And, we develop an efficient 2-phase heuristic algorithm to find a high quality feasible solution within reasonable time bounds. In the first phase, we seek to minimize the production cost by assigning batches to machines. Then, in the second phase, we find a production sequence of batches that reduces the inventory cost, while considering adding or deleting idle states between batches. Computational results show that the developed heuristic algorithm finds excellent feasible solutions within reasonable time bounds. Also, we could significantly reduce the total cost consisting of production cost and inventory cost by using the developed heuristic algorithm at a real manufacturing system that produces zinc alloys.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.175-178
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• 2003

In recent years, several researchers have presented the extensive research reports on network optimization problems. In our real life applications, many important network problems are typically formulated as a Maximum flow model (MXF) or a Minimum Cost flow model (MCF). In this paper, we propose a Genetic Algorithm (GA) approach used a priority-based chromosome for solving the bicriteria network optimization problem including MXF and MCF models(MXF/MCF).

• Journal of the Society of Naval Architects of Korea
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• v.54 no.1
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• pp.57-62
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• 2017

These days, shipbuilding companies are making an effort to adopt the IT technology in order to improve the production efficiency. One such effort is to utilize a planning and scheduling system to predict the production cost in advance. In this system, assessing the welding material quantity is an important factor. Unfortunately, obtaining the welding material quantity in the early design stage is extremely difficult because the detailed production information, which is essential in deriving the cost associated with welding, is normally available at a later stage. This paper aims at developing a computerized program that produces an index to estimate the welding material quantity in the early design stage. By using only three-dimensional geometric information, the program analyzes the production process and estimates the welding material quantity at any design or production stage when no production information is available. The results can be used for the planning and scheduling system.

• IE interfaces
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• v.16 no.4
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• pp.463-472
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• 2003

In this study we consider the problem of MPS(master production planning) of TFT-LCD(Thin Film Transistor - Liquid Crystal Display) production factory. Due to the complexities of the TFT-LCD production processes, it is difficult to build effective MPS. This study presents an algorithm having a concept of IDPQ(Ideal Daily Production Quantity) that considers line balancing of TFT-LCD production process. In general, the MPS building procedure does not consider line balancing in non-bottleneck processes. MPS without considering line balancing may make ineffective schedule. We present algorithms for building MPS considering factory capacity and line balancing according to the sales order.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.45-52
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• 2012

The purpose of this study is to investigate the perceived quality toward user performance and corporate performance in production information systems. For this purpose, a research model and hypotheses are developed based on the relevant literature reviews. Data have been collected from 132 enterprises which have implemented production information systems, and the research hypotheses were tested by covariance structural model analysis. The results of this empirical study are summarized as follows. First, production information quality and support service quality are confirmed to have a positive effect on user's satisfaction, however, I found no evidence of a statistically significant relationship between system quality and user's satisfaction. Second, all of three quality factors which are production information quality, system quality, and support service quality have positive influence on system usage. Third, user's satisfaction has positive influence on system usage, and both of user's satisfaction and system usage have positive influence on performance improvement. Based on these findings, this study suggested the implications, as well as limitations and further research directions.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1025-1035
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• 2016

Luenberger observer (LO)-based sensorless multi-loop control of a converter requires an iterative trial-and-error design process, considering that many parameters should be determined, and loop gains are indirectly related to the closed-loop characteristics. Robust H∞ control adopts a compact sensorless controller. The algebraic Riccati equation (ARE)-based and linear matrix inequality (LMI)-based H∞ approaches need an exhaustive procedure, particularly for a low-order controller. Therefore, in this study, a novel robust H∞ synthesis approach is proposed to design a low-order sensorless controller for boost converters, which need not solve any ARE or LMI, and to parameterize the controller by an adjustable parameter behaving like a "knob" on the closed-loop characteristics. Simulation results show the straightforward closed-loop characteristics evaluation and better dynamic performance by the proposed H∞ approach, compared with the LO-based sensorless multi-loop control. Practical experiments on a digital processor confirmed the simulation results.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.2
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• pp.215-219
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• 1999

This study aims to make detail examination of smallholder dairy farming systems in the Nongpho Dairy Cooperative. Forty-three dairy farms were selected from three geographical areas i.e. irrigated area, municipality area, and factory area. Within each area some number of sample farms were selected from each of the three levels of farm and animal crowdedness (very crowded, crowded, and not crowded farms). Detail data were collected during 1996 to 1997, they were socio-economic conditions of the sample farms and farmers, dairy production systems and management of resources (animals, bam, feeds, stocking rates, herd structure, animal body conditions, milk yield and milk quality, manure and farm wastes management, and other related items). Detail information useful for the improvement of farm production efficiency were discussed. It was very clear that much improvement of smallholder dairy production can be achieved if the recommendations given by this study were implemented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.191-194
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• 2003

Location-allocation problem is known as one of the important problem faced in Industrial Engineering and Operations Research fielde. There are many variations on this problem for different applications, however, most of them consider no obstacle existing. Since the location-allocation problem with obstacles is very complex and with many infeasible solutions, no direct method is effective to solve it. In this paper we propose a hybrid Genetic Algorithm (hGA) method for solving this problem. The proposed hGA is based on Lagrangian relaxation method and Dijkstra's shortest path algorithm. To enhance the proposed hGA, a Fuzzy Logic Controller (FLC) approach is also adopted to auto-tune the GA parameters.

• Journal of the Korea Safety Management & Science
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• v.9 no.2
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• pp.113-122
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• 2007

Recently, the strategy of the age of limitless competition for existence of manufacturing company appears for the enhancement of productivity through the automatic system, the reduction for the cost for standardization and the decision making process for the information system. Especially the critical success factors in manufacturing company can be summarized for the establishment of production visibility through the production management, material & work-in-process management, the establish of the flexible manufacturing system for the changed order priority and the establish of the quality system for improvement of product and process quality. The existing production management systems supply only simple information about production results on real time, can delay quick decision making. And it can prevent acquiring the information about various customer needs and the communication problems with other systems. In this paper, it will show MES system, a solution for the problems of existing production management systems. And through a case study of D company, it will reveal improvement effect on shipment error using MES system and economic analysis for MES itself.