• Journal of the Korean Operations Research and Management Science Society
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• v.7 no.2
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• pp.5-29
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• 1982

This paper presents the network models for general dynamic conveyor systems which are characterized by transporting and storing materials between work stations over time. With an appropriate choice of time-slice the conveyor system can be represented exactly as a dynamic flow network which can be solved by an efficient pure network algorithm.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1397-1406
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• 1996

In this paper, we propose a discrete model of conveyor systems, which is frequently used in flexible manufacturing systems to transfer work-in-process( WIP) between manipulators. In the case where the time required for transferring WIP's between manipulators are greater than that of manufacturing itself, as in many flexible assembly lines, the quantitative model of the transfer systems is needed to analyze the behavior and productivity of the whole manufacturing system. The proposed model is based upon the assumptions that the length of any unit conveyor component is integer multiple of the length of a pallet and hat the transferring speed of the conveyor is constant. Under these assumptions, the observation moments and the length of the conveyor can be quantized. Hence, the state of a conveyor can be represented by two kinds of Boolean variables: one representing the presence of a pallet on each quantize conveyor length and the other representing the mobility of this pallet. The whole conveyor system can be modeling as a network composed of branches and knots based on these two Boolean variables. The proposed modelling method was tested with various conveyor system configurations and showed that the model can be adopted successfully for the simulation of transfer systems and of the piloting of manufacturing processes.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.11-18
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• 2020

This study proposes a technique for the determination of outlet blockage using deep learning in a conveyor system. The proposed method aims to apply the best model to the actual process, where we train various CNN models for the determination of outlet blockage using images collected by CCTV in an industrial scene. We used the well-known CNN model such as VGGNet, ResNet, DenseNet and NASNet, and used 18,000 images collected by CCTV for model training and performance evaluation. As a experiment result with various models, VGGNet showed the best performance with 99.03% accuracy and 29.05ms processing time, and we confirmed that VGGNet is suitable for the determination of outlet blockage.

• IE interfaces
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• v.16 no.2
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• pp.229-239
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• 2003

The On-Line Analytical Processing (OLAP) tools access data from the data warehouse for complex data analysis, such as multidimensional data analysis, and decision support activities. Current research has lead to new developments in all aspects of data warehousing, however, there are still a number of problems that need to be solved for making data warehousing effective. View maintenance, one of them, is to maintain view in response to updates in source data. Keeping the view consistent with updates to the base relations, however, can be expensive, since it may involve querying external sources where the base relations reside. In order to reduce maintenance costs, it is possible to maintain the views using information that is strictly local to the data warehouse. This process is usually referred to as "self-maintenance of views". A number of algorithm have been proposed for self maintenance of views where they keep some additional information in data warehouse in the form of auxiliary views. But those algorithms did not consider a consistency of materialized views using view self-maintenance. The purpose of this paper is to research consistency problem when self-maintenance of views is implemented. The proposed "conveyor algorithm" will resolved a complete consistency of materialized view using self-maintenance with considering network delay. The rationale for conveyor algorithm and performance characteristics are described in detail.

• Journal of Power Electronics
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• v.12 no.4
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• pp.677-688
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• 2012

The vibratory conveyors with electromagnetic drive are used for performing gravimetric flow of granular materials in processing industry. By realizing free vibrations of variable intensity and frequency over a wide range through application of the electromagnetic actuator, suitable power converter, and the corresponding controller, continuous conveyance of granular materials have been provided for various operating conditions. Standard power output stages intended for control of vibratory conveyance using thyristors and triacs. Phase angle control can only accomplish tuning of amplitude oscillations, but oscillation frequency cannot be adjusted by these converters. Application of current controlled transistor converters enables accomplishing the amplitude and/or frequency control. Their use implies the excitation of a vibratory conveyor independent of the supply network frequency. In addition, the frequency control ensures operation in the region of mechanical resonance. Operation in this region is favourable from the energy point of view, since it requires minimal energy consumption. The paper presents a possible solution and advantages of the amplitude-frequency control of vibratory conveyors by means of a current controlled power converter.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.644-647
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• 2003

This paper describes a neural network based machine vision system designed for inspecting yellow beans in real time. The system consists of a camera. lights, a belt conveyor, air ejectors, and a computer. Beans are conveyed in four lines on a belt and their images are taken by a monochrome line scan camera when they fall down from the belt. Beans are separated easily from their background on images by back-lighting. After analyzing the image, a decision is made by a multilayer artificial neural network (ANN) trained by the error back-propagation (EBP) algorithm. We use the global mean, variance and local change of gray levels of a bean for the input nodes of the network. In an our experiment, the system designed could process about 520kg/hour.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.2
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• pp.153-165
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• 1995

Many closed queueing network models have been used as an effective tool to make a preliminary design of FMS. Although a loading/unloading function is an important factor to effect the utilization and throughput of FMS as well as a transfer function and a processing function, the Solberg's model did not clarify the loading/unloading function. In this paper, we propose a closed queueing network model for analyzing a flexible manufacturing system that consists of a load/unload station, a material handling system and a group of workstations for processing jobs, and define the expected utilization and the expected throughput of the FMS. As applications of the proposed model, the cases of a material handling system consisting of a conveyor and the FMS including an inspection station are also formulated.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.3 s.96
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• pp.91-102
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• 1999

Fieldbus provides real-time data communication among field devices in the manufacturing automation and process control systems. In this study, an experimental model of fieldbus-based manufacturing automation system is developed. Experimental model consists of two robots, two conveyor belts, NC machine, PLC, sensors and operator station. These machines are interconnected into the Profibus network, and exchange their data through the services provided by FMS(Fieldbus Message Specification), which is the application layer protocol of Profibus. The experimental model is used to measure the network-induced delay of variable and file data transmitted through FMS services. Network-induced delays are collected and analyzed on each sublayer of Profibus protocol stack. The results obtained from the experiment of this study can be effectively utilized when fieldbus is implemented on the practical manufacturing automation systems.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.109-116
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• 2023

This paper presents a network-based automation system for the detection of metallic objects in food and livestock. A metal detector is a core equipment used for the inspection required by HACCP. Since the existing metal detectors are manufactured as a single-body equipment, it is difficult to take into account various user requirements for the system. In order to overcome the drawback, this study presents a network-based automation system for metal detector utilizing an industrial fieldbus and modular components. The proposed system can effectively consider the various customer requirements and control schemes. The proposed system can also achieve the improvement in speed and success rate of detecting metallic objects. The effectiveness of the proposed system is demonstrated through a various experiments.

• IE interfaces
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• v.3 no.2
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• pp.39-51
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• 1990

One of the most important and powerful tools available for design and/or study of the operation of complex systems and processes is simulation. Since automated material handling systems like AS/RS are often quite complex, a network-based simulation model is developed to analyze an automobile part supplier's automated storage and retrieval system(AS/RS). The network simulation model is implemented in the SLAM Ⅱ on a VAX 8800 computer. Performance of the AS/RS was tested for 3 dispatching rules, 3 work load levels, 2 storage policies, 3 levels of stacker crane break-down, and 2 conveyor system layouts. Results indicate that the AS/RS performance is primarily affected by the dispatching rule and work load level.