• IE interfaces
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• v.8 no.3
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• pp.249-257
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• 1995

Expert system is an effective approach for quality system to be automated and thus to be an essential integrating mechanism in any move towards CIM(Computer Integrated Manufacturing). A quality control expert system is introduced and its relationship to CIM is illustrated in a case study. Process control expert system developed by Kim and Sin[6] has been improved via ODBC(Open DataBase Connectivity) for efficient information network, graph representation using Windows API for rapid response and some new rules for identification of patterns in control charts.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1565-1568
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• 1997

In this paper, a fuzzy based machine-cell formation algorithm for cellular manufacturing is presented. The fuzzy lovic is employed to express the degree of appropriateness when alternative machnies are specified to process a part shape. For machine grouping, the similarity coefficient based approach is used. The algorithm produces efficient machine cells and part families which maximize the similarity values.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.89.3-89
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• 2002

Plasma processing plays a crucial role in fabricating integrated circuits (ICs). Manufacturing ICs in a cost effective way, it is increasingly demanded a computer model that predicts plasma properties to unknown process inputs. Physical models are limited in the prediction accuracy since they are subject to many assumptions. Expensive computation time is another hindrance that prevents their widespread used in manufacturing site. To circumvent these difficulties inherent in physical models, neural networks have been used to learn nonlinear plasma data. A generalized regression neural network (GRNN) [I] is one of the architectures that have been widely used to analyze complex chemical data. I...

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.46.2-46
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• 2002

Plasma processing plays a crucial role in fabricating integrated circuits (ICs). Manufacturing ICs in a cost effective way, it is increasingly demanded a computer model that predicts plasma properties to unknown process inputs. Physical models are limited in the prediction accuracy since they are subject to many assumptions. Expensive computation time is another hindrance that prevents their widespread used in manufacturing site. To circumvent these difficulties inherent in physical models, neural networks have been used to learn nonlinear plasma data [1]. Among many types of networks, a backpropagation neural network (BPNN) is the most widely used architecture. Many training variables are...

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.300-306
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• 1987

This paper deals with a modeling of manufacturing system and a model analysis by a SIMAN language. A flow of production process is analyzed, and a mathematical model on the basis of the analyzed data is simulated by a SIMAN language. An object of this study is to achieve an optimization of production a reduction of cost, and an improvement of quality by a applicable line-balancing technique and an optimization technique in a real factor induced an analysis and synthesis of the result of simulation.

• Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.1-13
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• 2016

The increase of consumer needs for quality metal cutting related products with more precise tolerances and better product surface roughness has driven the metal cutting industry to continuously improve quality control of metal cutting processes. In this paper, two different approaches are discussed. First, design of experiments (DOE) is used to determine the significant factors and then fuzzy logic approach is presented for the prediction of surface roughness. The data used for the training and checking the fuzzy logic performance is derived from the experiments conducted on a CNC milling machine. In order to obtain better surface roughness, the proper sets of cutting parameters are determined before the process takes place. The factors considered for DOE in the experiment were the depth of cut, feed rate per tooth, cutting speed, tool nose radius, the use of cutting fluid and the three components of the cutting force. Finally the significant factors were used as input factors for fuzzy logic mechanism and surface roughness is predicted with empirical formula developed. Test results show good agreement between the actual process output and the predicted surface roughness.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.4
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• pp.113-118
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• 2017

As the demand for industrial robots and Automated Guided Vehicles (AGVs) increases, higher performance is also required from them. Fuzzy controllers, as part of an intelligent control system, are a direct control method that leverages human knowledge and experience to easily control highly nonlinear, uncertain, and complex systems. This paper uses a $LabVIEW^{(R)}-based$ fuzzy controller with gain scheduling to demonstrate better performance than one could obtain with a fuzzy controller alone. First, the work area was set based on forward kinematics and inverse kinematics programs. Next, $LabVIEW^{(R)}$ was used to configure the fuzzy controller and perform the gain scheduling. Finally, the proposed fuzzy gain scheduling controller was compared with to controllers without gain scheduling.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.6
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• pp.175-182
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• 2012

Light characteristics of the monochromatic red(R), blue(B), green(G) and white(W) and the mixed LED (B-R LED) were investigated by light control a Spectrometer-MMS1 and an illuminometer. The power consumption of each LED was 1W and R LED has five wavelength bands(600nm, 640nm, 660nm, 680nm, 750nm). The light intensity of each LED was changed in a range 10~100%. As a results, the wavelength and the spectrum distribution of R LED increase with increasing light intensity but the wavelength of B, G, W LED decreases. It was found that illumination of each mononochromatic and B-R LED increases linearly with increasing light intensity. It was confirmed that the illumination intensity of R-B light has greater values than those obtained by monochromatic light at the same conditions.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.6
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• pp.8-14
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• 2014

Pulverized coal (PC) has become an important auxiliary fuel in the iron and steel industry since the technique of pulverized coal injection (PCI) was developed for iron making. The combustion efficiencies of pulverized coal in blowpipes and tuyeres under various operational conditions are numerically predicted to determine the performance levels with regard to different locations of the nozzles in a blast furnace. A variety of parameters, including the pulverized coal quantities, oxygen amounts, inlet temperatures of the tuyeres, and the mass flow rate of coal carrier gas are taken into consideration. Also, in order to develop greater efficiency than those of existing coal injection systems, this study applies a flame measurement system using a charge-coupled device (CCD) camera and a frame grabber. It uses auto sampling algorithms from the flame shape information to determine the device for the optimal location control for PCI. This study finds further improvements of the blast furnace performance via the control of the PCI locations.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.10
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• pp.80-87
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• 2021

Our study introduces an improved modular agricultural platform to provide convenience to agricultural workers. We upgrade the platform design in three parts, namely, by adding a 458 pattern tire, electricity control, and four-wheel steering function, to improve the platform performance. Results showed that the upgrades enhanced the platform performance and reduced its overall weight as compared with the existing platform. To demonstrate the performance of our improved platform, we conducted five types of experiments with respect to the climbing angle, variable width, attitude control, speed, and obstacle passing.