• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.587-591
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• 2003

This study develops a neural network for solving optimization problems. Hopfield network has been used for such problems, but it frequently gives abnormal solutions or non-optimal solutions. Moreover, it takes much time for solving a solution. To overcome such disadvantages, this study adopts a neural network whose output nodes change with a small value at every evolution, and the proposed neural network is applied to solve ALB (Assembly Line Balancing) problems . Given a precedence diagram and a required number of workstations, an ALB problem is solved while achieving even distribution of workload among workstations. Here, the workload variance is used as the index of workload deviation, and is reflected to an energy function. The simulation results show that the proposed neural network yields good results for solving ALB problems with high success rate and fast execution time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.51
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• pp.189-197
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• 1999

Assembly line balancing problem is known as one of difficult combinatorial optimization problems. This problem has been solved with linear programming, dynamic programming approaches. but unfortunately these approaches do not lead to efficient algorithms. Recently, genetic algorithm has been recognized as an efficient procedure for solving hard combinatorial optimization problems, but has a defect that requires long-run time and computational complexties to find the solution. For this reason, we adapt a new method called the Critical Node Method that is intuitive, easy to understand, simple for implementation. Fuzzy set theory is frequently used to represent uncertainty of information. In this paper, to treat the data of real world problems we use a fuzzy number to represent the duration and Critical Node Method based heuristic procedure is developed for solving fuzzy assembly line balancing problem.

• 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 Safety Management and Science Conference
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• 2002.05a
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• pp.91-97
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• 2002

In this thesis presents line balancing problems of two-sided and mixed model assembly line widely used in practical fields using genetic algorithm for reducing throughput time, cost of tools and fixtures and improving flexibility of assembly lines. Two-sided and mixed model assembly line is a special type of production line where variety of product similar in product characteristics are assembled in both sides. This thesis proposes the genetic algorithm adequate to each step in tow-sided and mixed model assembly line with suitable presentation, individual, evaluation function, selection and genetic parameter. To confirm proposed genetic algorithm, we apply to increase the number of tasks in case study. And for evaluation the performance of proposed genetic algorithm, we compare to existing algorithm of one-sided and mixed model assembly line. The results show that the algorithm is outstanding in the problems with a larger number of stations or larger number of tasks.

• Journal of the Korea Safety Management & Science
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• v.4 no.2
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• pp.83-101
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• 2002

In this thesis presents line balancing problems of two-sided and mixed model assembly line widely used in practical fields using genetic algorithm for reducing throughput time, cost of tools and fixtures and improving flexibility of assembly lines. Two-sided and mixed model assembly line is a special type of production line where variety of product similar in product characteristics are assembled in both sides. This thesis proposes the genetic algorithm adequate to each step in tow-sided and mixed model assembly line with suitable presentation, individual, evaluation function, selection and genetic parameter. To confirm proposed genetic algorithm, we apply to increase the number of tasks in case study. And for evaluation the performance of proposed genetic algorithm, we compare to existing algorithm of one-sided and mixed model assembly line. The results show that the algorithm is outstanding in the problems with a larger number of stations or larger number of tasks.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.4
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• pp.5-21
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• 1994

We have described the optimal process route selection model for the PCB(printed circuit board) auto-insertion line. This PCB assembly line is known as a FFL(flexible flow line) which produces a range of products keeping the flow shop properties. Under FFL environments, we have emphasized the balancing of work-loads in order to maximize total productivity of PCB auto-insertion line. So we have developed a heuristic algorithm based on a work-order selection rule and min-max concept for the job route selection model.

• Korean Journal of Computational Design and Engineering
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• v.13 no.1
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• pp.67-75
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• 2008

In spite of rapidly increasing interests in digital manufacturing, there still lacks of a systematic approach in manufacturing line flow analysis via modeling and simulation; currently, the parameters for designing manufacturing line are defined by being solely based on engineers experiences. The paper proposes an application of the genetic algorithm to a discrete event line simulation finding optimal set of parameters for manufacturing line balancing problem. The proposed method has been applied to two example problems-one is a simple manufacturing model and the other for shipyard industry-in order to demonstrate its validity and usefulness.

• IE interfaces
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• v.22 no.2
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• pp.144-152
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• 2009

Assembly line has been recognized as an efficient production system in mass production. However, the recent production environment characterized as mass customization urges production managers to transform a long assembly line to a number of short assembly cells. To maximize the utilization of resources in an assembly cell, it is important to have the line balanced. This paper presents a bucket brigade-based assembly cell. Bucket brigade is a way of coordinating workers who progressively perform a set of assembly operations on a flow line. Each worker follows a simple rule: perform assembly operations on a product until the next worker downstream takes it over; then go back to the previous worker upstream to take over a new assembly job. In this way, the line balances itself. The bucket brigade assembly cell is analyzed and compared with traditional assembly lines and general assembly cells. The paper also discusses some prerequisite requirements and limitations when the bucket brigade assembly cells are employed.

• Industrial Engineering and Management Systems
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• v.10 no.3
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• pp.197-202
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• 2011

In traditional production lines, such as assembly lines, each worker is usually assigned to a particular fixed work, and decreasing the task to master the assigned work is valuated. However, when an imbalance exists between workers' speeds, if a worker delays the overall work in the production line, the production rate of the particular line will also decrease. To avoid this problem, the "Self-Balancing Production Line" was introduced. In this type of production line, each worker is assigned work dynamically, and when specific conditions are satisfied, production remains balanced. Characteristics of these lines that can be preempted at any place have already been analyzed by some researchers. A previous paper examined the situation in which only a single worker can process one machine and cannot preempt processing, and the improved policy of an ordinary selfbalancing production line, which specifies which stations workers can process and how workers can behave. This policy achieveda high production rate with only four stations and two workers (Buzacott, 2002). In that paper, worker processing stations and the behavior of a specific worker were limited, andthe paper focused only on specific stations and workers. Therefore, it is not applicable to any worker sequence. In this paper, we focus on other ways to decrease cycle time. In this kind of line, a worker processes at his or her speed. Therefore, if a worker is assigned stations according to his or her speed, the line can decrease cycle time. To do so, we relax the assumptions of this type of line and set a new condition. Under these conditions, we compare our results to the results of previous papers.

• Industrial Engineering and Management Systems
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• v.12 no.3
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• pp.254-263
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• 2013

Disassembly of discarded products takes place in the process of remanufacturing, recycling, and disposal. The disassembly lines have been taken as available choice for automated disassembly; therefore, it has become essential that it be designed and balanced to work efficiently. The multi-objective disassembly line balancing problem seeks to find a disassembly sequence which provides a feasible disassembly sequence, minimizes the number of workstations and idle time, and balances the line for the disassembly of post consumed product by considering the environment effects. This paper proposes a multi-criteria decision making technique based heuristic for assigning the disassembly tasks to the workstations. In the proposed heuristic, the PROMETHEE method is used for prioritizing the tasks to be assigned. The tasks are assigned to the disassembly workstations according to their priority rank and precedence relations. The proposed heuristic is illustrated with an example, and the results show that substantial improvement in the performance is achieved compared with other heuristics.