• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.4
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• pp.420-427
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• 2016

Diverse research on gearing systems have been made to resolve gear NVH problems for many decades, and transmission error (T.E.) has been identified as one of the main sources generating gear noises. While gear profiles and amounts of tooth modifications have influences on gear noise in the design aspect, it is found that bad manufacturing conditions such as burrs, bumps and damage, which result in improper gear operating conditions, produce gear noise with respect to manufacturing process. In this paper, T.E. measurement system was introduced to examine the gears damaged or improperly manufactured, while they are assembled, by comparing T.E. values and various gear conditions with theoretical ones. This T.E. measurement system, following grinding machining process, has been installed in a manufacturing line in 2014, and it results that the transmission rework to resolve manufacturing problems is not needed at the end of line.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1564-1569
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• 1991

In this paper we describe Flexible Manufacturing Systems (FMS) using Petri nets, since Petri nets provide a powerful tool for modeling dynamical behavior of discrete concurrent processes. We deal with off-Line and on-Line rule-based scheduling of FMS. The role of the rule-base is to generate appropriate priority rule for resolving conflicts, that is, for selecting one of enabled transitions to be fired in a conflict set of the Petri nets. This corresponds to select a part type to be processed in the FMS. Towards developing more Intelligent Manufacturing Systems (IMS) we propose a conceptual framework of a futuristic intelligent scheduling system.

• Journal of the Korea Safety Management & Science
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• v.12 no.2
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• pp.65-73
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• 2010

In an automated industry PLC plays a central role to control the manufacturing system. Therefore, fault free operation of PLC controlled manufacturing system is essential in order to maximize a firm's productivity. On the contrary, distributed nature of manufacturing system and growing complexity of the PLC programs presented a challenging task of designing a rapid fault finding system for an uninterrupted process operation. Hence, designing an intelligent monitoring, and diagnosis system is needed for smooth functioning of the operation process. In this paper, we propose a method to continuously acquire a stream of PLC signal data from the normal operational PLC-based manufacturing system and to generate diagnosis model from the observed PLC signal data. Consequently, the generated diagnosis model is used for distinguish the possible abnormalities of manufacturing system. To verify the proposed method, we provided a suitable case study of an assembly line.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.93-100
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• 2013

Mixed model production system means that various products are manufactured alternately in a line, and it has become a popular system in the era of multi-product small-quantity production. However, in the mixed model production system using flow line, the unbalance among stations is not inevitable because the workloads of stations cannot be the same. Thus, flow line system has been replaced to cellular manufacturing system for reducing the loss of waiting due to the unbalance of stations. In this paper, we introduce the simulation case study of an automated welding line which produces the parts of excavator. The factory has considered replacing the mixed model flow line to the cellular manufacturing system based on FMC concept. The increase of production quantity is estimated about 26.7%, and the lead time is reduced more than 55%. Furthermore sensitivity analyses are conducted considering the changes of product-mix.

• 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 the Korea Society for Simulation
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• v.9 no.1
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• pp.1-9
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• 2000

When a new manufacturing line is constructed, its production capacity can be substantially affected in its design stage. Computer simulation often provides better design by evaluating feasible alternatives. In this paper we study an automobile engine manufacturing line which is under construction. Three alternatives are considered in the design; (1) to use machining tools of longer life; (2) to reassign the buffer space to each sequential processes while maintaining the same total buffer length; and (3) to reduce the machine repair time to 30 minutes using TPM and maintenance team. Simulation results using AutoMod indicates that employing the three alternatives will save about 1.5 million dollars per year.

• Korean Journal of Computational Design and Engineering
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• v.10 no.3
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• pp.199-209
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• 2005

In this paper, a digital simulation model for an automotive assembly line is constructed by adapting a digital manufacturing methodology. Applied methodology is a simulation for a plant level of the assembly production line. The first significance of this methodology is a validation of the production planning based on various scenarios. The second is pre-verification for the new production plan or production method. The third is a visualization of the production process. Several models were implemented and those models were verified. Then, it was possible to find a most efficient production scenario and production method.

• Korean Journal of Computational Design and Engineering
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• v.14 no.5
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• pp.323-329
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• 2009

Auto-makers can only remain competitive by producing high quality vehicles in an efficient way. In designing a production line, one of the most important objectives of digital manufacturing is to verify design errors as early as possible. In terms of the cost and time saving, it is very essential to start the construction of a production line with a proven design which is error-free. Likewise, this paper aims to implement PLC verification using an example. The verification in automobile manufacturing means verifying PLC program, which control automatic devices. In this paper, we built a virtual factory to implement PLC simulation and introduced verification procedure using PLC Studio. Finally, we can prove the availability for the PLC verification.

• Journal of Korea Foundry Society
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• v.10 no.1
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• pp.23-30
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• 1990

• Journal of Korea Foundry Society
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• v.10 no.2
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• pp.119-128
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• 1990