• IE interfaces
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• v.9 no.2
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• pp.39-45
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• 1996

This paper investigates the problems of grouping N products on an assembly line with an objective of maximizing the option grouping rate. Before developing a mixed model grouping algorithm, simulation studies are committed for developing operating rules and evaluating the layout production systems. A mixed model grouping algorithm is suggested and it is applied to the color selection lane in automobile production system, which reveals a high mixed model grouping rate.

• Korean Management Science Review
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• v.13 no.1
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• pp.1-12
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• 1996

This paper deals with production scheduling of block assembly shop in shipbuilding company. The Objectives of the schedule are leveling of daily total workload and fair assignment of workload to each department of the shop. Optimizing the objectives, we consider some restrictions which consisit of block due dates, workability of each department, and space restriction. We formulate the problem in mathematical form. But the model is too complex to find the optimal solution (the problem is NP-complete) and we use the genetic algorithm to find a good solution.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.427-431
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• 1996

A modeling of the dynamics of two cooperating robot manipulators doing assembly job such as peg-in-hole while coordinating the payload along the desired path is proposed. The system is uncertain due to the unknown mass and moment of inertia of the manipulators and the payload. To control the system, a robust control algorithm is proposed. The control algorithm includes fuzzylogic. By the fuzzy logic, the magnitude of the input torque of the manipulators is controlled not to go over the hardware saturation with keeping path tracking errors bounded.

• IE interfaces
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• v.22 no.2
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• pp.116-125
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• 2009

We revisit the assembly block storage location assignment problem (ABSLAP) at a shipyard, in order to compensate for the deficiency in performance verification of the heuristic ABSLAP algorithm developed by the previous study. In this paper, we formulate a mathematical programming model of the ABSLAP, refine elaborately the heuristic ABSLAP algorithm, and show the performance of the developed mathematical programming model and the revised heuristic ABSLAP algorithm. In addition, we explain simulation experiments conducted using the revised heuristic ABSLAP algorithm to investigate the influences of block stockyard layouts and production schedule instability on the block stockyard operations.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.715-718
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• 2009

The assembly line is one of the typical process hard to analyze with mathematical methods including even stochastic approaches, because it includes many manual operations varying drastically depending on operators' skills. In this paper, we suggest the simulation optimization method to design the optimal assembly line of a gas oven. To achieve the optimal design, firstly, we modeled the real gas oven assembly line with actual data, such as assembly procedures, operation rules, and other input parameters and so on. Secondly, we build some alternatives to enhance the line performance based on business rules and other parameters. The DOE(Design Of Experiment) techniques were used for testing alternatives under various situations. Each alternatives performed optimization process with evolution strategy; one of the GA(Genetic Algorithm) techniques. As a result, we can make about 7% of throughputs up with the same time and cost. By this process, we expect the assembly line can obtain the solution compatible with their own problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.1-16
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• 1997

This paper improves the autonomy for supplier's schedule and the flexibility of the final assembly line. The final assembly line is a single work station and each product taking different assembly time is considered. In the assembly schedule, the heuristic method based on the goal chasing method is used. Consequently, suppliers can independently determine their output rates and thus, change their workload pattern according to their needs and priorities. Moreover, this flexibility can help to avoid expensive final-assembly-line stoppages in case of sudden part supply disruptions. The sequencing method can be easily implemented into an existing just-in-time system. In addition, the mathematical model was formulated and the algorithm was explained through the flow chart. The numerical example was given and the efficiency of this method is shown through the analysis of computational results of that example.

• IE interfaces
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• v.18 no.2
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• pp.136-147
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• 2005

This paper introduces a simulation study regarding the operation of the Painted Body Storage (PBS) in an automobile factory. In the paint shop of the factory, same colored bodies are grouped together in order to increase the effectiveness of process, for example decrease the loss of cleaning the painting-gun when the color of body changes from one to another. However the production of automobiles in the assembly shop is a typical example of the mixed model assembly production. Therefore PBS locates between the paint shop and the assembly shop for control the input sequence of bodies to the assembly shop, and it enables to meet the smoothing requirement of assembly sequence. There are highly restricted constraints on the assembly sequence in a assembly shop. Those are spacing restriction and smoothing restriction. If such restrictions are violated, conveyor-stop or utility work will be necessary. Thus the major objective of PBS is to control the assembly sequence in a way to meet the two restrictions. In this paper a case study of PBS in an automotive factory is introduced. The storage/retrieval algorithms are suggested and the proposed system is verified using simulation models. Sensitivity analysis for operating factors is also conducted.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.298-308
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• 2000

In this paper a new two-arm cooperative assembly(or insertion) algorithm is proposed. As a force-guided control method for the cooperative assembly the adaptive accommodation controller is adopted since it does not require any complicated contact state analysis nor depends of the geometrical complexity of the assembly parts. Also the RMRC(resolved motion rate control) method using a relative jacobian is used to solve inverse kinematics for two manipulators. By using the relative jacobian the two cooperative redundant manipulators can be formed as a new single redundant manipulator. Two arms can perform a variety of insertion tasks by using a relative motion between their end effectors. A force/torque sensing model using an approximated penetration depth calculation a, is developed and used to compute a contact force/torque in the graphic assembly simulation . By using the adaptive accommodation controller and the force/torque sensing model both planar and a spatial cooperative assembly tasks have been successfully executed in the graphic simulation. Finally through a cooperative assembly task experiment using a humanoid robot CENTAUR which inserts a spatially bent pin into a hole its feasibility and applicability of the proposed algorithm verified.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.11
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• pp.509-516
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• 2008

The Minimum Letter Flips (MLF) model and the Weighted Minimum Letter Flips (WMLF) model are for solving the haplotype assembly problem. But these two models are effective only when the error rate in SNP fragments is low. In this paper, we first establish a new computational model that employs the related genotype information as an improvement of the WMLF model and show its NP-hardness, and then propose an efficient genetic algorithm to solve the haplotype assembly problem. The results of experiments on random data set and a real data set indicate that the introduction of genotype information to the WMLF model is quite effective in improving the reconstruction rate especially when the error rate in SNP fragments is high. And the results also show that genotype information increases the convergence speed of the genetic algorithm.

• 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.