• 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.

• IE interfaces
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• v.17 no.spc
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• pp.20-27
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• 2004

A flexible assembly system (FAS) is a production system that assembles various parts with many constraints and manufacturing flexibilities. This paper presents a new method for efficiently solving the integrated process planning and scheduling in FAS. The two problems of FAS process planning and scheduling are tightly related with each other. However, in almost all the existing researches on FAS, the two problems have been considered separately. In this research, an endosymbiotic evolutionary algorithm is adopted as methodology in order to solve the two problems simultaneously. This paper shows how to apply an endosymbiotic evolutionary algorithm to solving the integrated problem. Some evolutionary schemes are used in the algorithm to promote population diversity and search efficiency. The experimental results are reported.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.1-10
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• 2016

This paper presents a fast sequencing algorithm for a mixed model assembly line with multiple workstations which minimize the total utility work and idle time. We compare the proposed algorithms with another heuristic, the Tsai-based heuristic, for a sequencing problem that minimizes the total utility works. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm. The Tsai-based heuristic performs best in terms of utility work, but the fast sequencing algorithm performs well for both utility work and idle time. However, the computational complexity of the fast sequencing algorithm is O (KN) while the Tsai-based algorithm is O (KNlogN). Actual computational time of the fast sequencing heuristic is 2-6 times faster than that of the Tsai-based heuristic.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1123-1128
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• 1993

In this paper, utilizing the line balancing algorithm proposed to deal with various situations of automated assembly line, the optimal solution can be derived by the branch and bound method of analysis. By the application of line balancing algorithm to telephone assembly line, thoughput is improved by 3.38%. Therefore, in the proposed line, blicking phenomena were reduced and smooth line-flow was achieved, and uniform distribution of utilization rate of each machine is obtained.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.504-509
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• 1995

In this paper, we developed a position correction system of industrial robot for door-chassis assembly task. With the aid of a dedicated vision system, industrial robot accomplished visually acceptable door-chassis's assembly task. The alogorithm of the position detection of notch and 2 dimesional position correction algorithm are noteworthy. The obtained algorithms were satisfatorily implemented for a real door-chassis model.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.703-707
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• 1992

In the field of assembly processes, non-rigid parts such as wires, tubes, gaskets and 0-rings cannot be assembled automatically. And although many researches have been made for rigid part mating, there are not substantial studies in flexible parts assembly field. In this paper, assembly stages of flexible parts are classified and some analysis are made. FEM was used to estimate the relationship between deformation and reactive forces. An assembly algorithm adopting reciprocal twisting motion was proposed and the assembly tool design methodology was discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.411-416
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• 1990

A modelling process of a robotic assembly cell and a method for analysis of the assembly cell operation through simulation are presented. An assembly cell including industrial robots is the subject of the model. The states of the assembly cell elements are taken as the state variables and the relationships between the states are described mathematically using the operators. An algorithm for the cell operation is developed from the relationships between the states and the information on the assembly task, and efficient analyses are performed by the simulation results.

• Korean Journal of Computational Design and Engineering
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• v.10 no.6
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• pp.412-420
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• 2005

The integration of CAD and CAM is critical for computer aided process planning. Recently, STEP has been emerged and utilized as a product data exchange standard format in CAD/CAM areas. The assembly information consists of assembly component relations, assembly features, assembly directions and mating conditions. The purpose of this study is to develop an efficient algorithm to extract assembly information directly from the STEP based files and to generate automatically assembly process plan from the extracted assembly features. The developed algorithms will generate assembly information codes for STEP(AICS). The results from this study can be a reasonable link between design and manufacturing for developing better CAAPP(Computer-Aided Assembly Process Planning) systems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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• pp.80-93
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• 2008

This paper improves algorithms for an assembly-type flowshop scheduling problem in which each job is to assemble two types of components and makespan is the objective measure. For the assembly, one type of the components is outsourced with job-dependent lead time but the other type is fabricated in-house. When both components for a job are prepared, the assembly operation for the job can be started. This problem had been proved to be NP-Complete, so branch-and-bound (B&B) and heuristic algorithms have already been developed. In this paper, we suggest other dominance rules, lowerbound and heutistic algorithms. Also, we develop a new B&B algorithm using these improved bound and dominance rules. The suggested heuristics and B&B algorithm are compared with existing algorithms on randomly-generated test problems.