• Journal of the Korea Society for Simulation
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• v.11 no.4
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• pp.69-80
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• 2002

This study deals with the productivity improvement on a flow production system with the consideration of line-balancing. In a flow production system, similar product models are produced on a same assembly line, the predefined process order and the limitation of total worker number. The system can be increased the work-in -process(WIP) inventory and the worker's idle time. In this study, the worker assignment model is developed to assign evenly workload of process to each product model in such a manner that each process has the different number of worker. This worker assignment model is the mathematical model that determines worker number in each process such that the idle time of processes is reduced and the utilization of worker is improved. We use a simulation technique to simulate the production line proposed by the mathematical model and apply real production line. With the result of simulation, this study analyzes the propriety of production line and proposes the alternatives of new production line

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.737-740
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• 1996

This paper suggests a boltzman machine neural network model to determine model input sequences in line balancing process of mixed model assembly line. We first present a proper energy function, next determine the value of parameters using simulation process.

• Journal of the Korea Safety Management & Science
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• v.7 no.3
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• pp.85-96
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• 2005

This paper is concerned with the integrated problem of line balancing and model sequencing in mixed model assembly lines(MMALBS), which is important to efficient utilization of the lines. In the problem, we deal with the objective of minimizing the overall line length To apply the GAs to MMALBS problems, we suggest a GA representation which suitable for its problems, an efficient decoding technique for the objective, and genetic operators which produce feasible offsprings. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that our algorithm is promising in solution quality.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.930-935
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• 2002

This paper presents a new method that can efficiently solve the integrated problem of line balancing and model sequencing in mixed-model U-lines (MMULs). Balancing and sequencing problem are important for an efficient use of MMULs and are tightly related with each other. However, in almost all the existing researches on mixed­model production lines, the two problems have been considered separately. In 1his research, an endosymbiotic evolutionary algorithm, which is a kind of evolutionary algorithm, is adopted as a methodology in order to solve the two problems simultaneously. Some evolutionary search capability, rapidity of convergence and population diversity. The proposed algorithm is compared with the existing evolutionary algorithm in terms of solution quality. The experimental results confirm the effectiveness of our approach.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.4
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• pp.411-420
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• 1999

A mixed model production line is a production line where a variety of product models are produced. In U-shaped production lines (called U-lines) used in just-in-time production system, the strategy of mixing product models is often used to provide various types of products to customers in time. Line balancing and model sequencing problems are important for an efficient use of mixed model U-lines. Although the two problems are tightly interrelated with each other, prior researches have considered them separately or sequentially. This paper presents a new method using a coevolutionary algorithm that can solve the two problems at the same time. To promote diversity and search efficiency, in this paper the evolutionary system is based on the localized interactions within and between populations. Methods of selecting environmental individuals and evaluating fitness are developed. Efficient genetic representations and operator schemes are also provided. When designing the schemes, we take into account the features specific to the problems. The experimental results demonstrate that the proposed algorithm is superior to existing approaches.

• Proceedings of the Safety Management and Science Conference
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• 2005.05a
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• pp.523-534
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• 2005

This paper is concerned with the integrated problem of line balancing and model sequencing in mixed model assembly lines(MMALBS), which is important to efficient utilization of the lines. In the problem, we deal with the objective of minimizing the overall line length To apply the GAs to MMALBS problems, we suggest a GA representation which suitable for its problems, an efficient decoding technique for the objective, and genetic operators which produce feasible offsprings. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that our algorithm is promising in solution quality.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.105-116
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• 2018

In this study, we consider the assembly line balancing (ALB) problem which is known as an very important decision dealing with the optimal design of assembly lines. We consider ALB problems with soft constraints which are expected to be fulfilled, however they are not necessarily to be satisfied always and they are difficult to be presented in exact quantitative forms. In previous studies, most researches have dealt with hard constraints which should be satisfied at all time in ALB problems. In this study, we modify the mixed integer programming model of the problem introduced in the existing study where the problem was first considered. Based on the modified model, we propose a new algorithm using the genetic algorithm (GA). In the algorithm, new features like, a mixed initial population selection method composed of the random selection method and the elite solutions of the simple ALB problem, a fitness evaluation method based on achievement ratio are applied. In addition, we select the genetic operators and parameters which are appropriate for the soft assignment constraints through the preliminary tests. From the results of the computational experiments, it is shown that the proposed algorithm generated the solutions with the high achievement ratio of the soft constraints.

• IE interfaces
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• v.10 no.2
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• pp.51-56
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• 1997

This paper concerns with the problem of mixed model assembly sequencing using neural net. In recent years, because of two characteristics of it, massive parallelism and learning capability, neural nets have emerged to solve the problems for which more conventional computational approaches have proven ineffective. This paper proposes a method using neural net that can consider line balancing and grouping problems simultaneously. In order to solve the mixed model assembly sequencing of the motor industry, this paper uses the modified ART1 algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.3
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• pp.515-532
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• 1997

When balancing mixed model assembly lines (MMALs), workload smoothness should be considered on the model-by-model basis as well as on the station-by-station basis. This is because although station-by-station assignments may provide the equality of workload to workers, it causes the utilization of assembly lines to be inefficient due to the model sequences. This paper presents a genetic algorithm to improve the workload smoothness on both the station-by-station and the model-by-model basis in balancing MMALs. Proposed is a function by which the two kinds of workloads smoothness can be evaluated according to the various preferences of line managers. To enhance the capability of searching good solutions, our genetic algorithm puts emphasis on the utilization of problem-specific information and heuristics in the design of representation scheme and genetic operators. Experimental results show that our algorithm can provide better solutions than existing heuristics. In particular, our algorithm is outstanding on the problems with a larger number of stations or a larger number of tasks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1439-1445
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• 2009

This paper introduces a simulation model regarding the process analysis of a digital doorlock mixed assembly process. The objective of the simulation model is to evaluate the performance of various design aspects of process alternatives. To develop the simulation model, a time study is performed for each process. Next, by using ARENA, a simulation model is conducted based on the process analysis and the line balancing methodology. We found out several problems for mixed assembly process, and then suggest several alternatives to improve the system.