• Journal of Korean Academy of Nursing Administration
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• v.21 no.3
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• pp.254-262
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• 2015

Purpose: This study was done to apply failure mode & effect analysis (FMEA) to chemotherapy in order to reduce prescribing, dispensing and administering errors related to treatment and provide patients with a safe medical environment. Methods: A one group pre-post test design was used to verify the effects using the tool for FMEA in chemotherapy. Results: There was a statistically significant decrease in prescribing errors from 11.47% to 3.18%; administering errors decreased but they were not statistically significant. In a addition, there was no change in dispensing errors. Conclusion: The results show that FMEA removed risk factors that might occur during the process of chemotherapy and that it was an effective tool for prevention of negligent accident occurring in actual patients.

• Women's Health Nursing
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• v.7 no.1
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• pp.30-43
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• 2001

This was a pre-experimental study to confirm the breast-feeding ability and effect of follow up care on the breast-feeding rate and the breast-feeding method by the mother-infant breast-feeding assessment tool for the mothers who got the breast-feeding education. The subjects were 46 mothers who experienced normal delivery of infants at a college hospital in K-city, Kyungsangbuk-do, from July 1 to October 21, 2000. The instrument for data obtainment were The Mother-Infant Breast-Feeding Assessment Tool of Johnson et al. (1999), and The Breast- Feeding Method Measurement Tool of Jeong, Geum-hee(1997). This instrument was reliable, showing Cronbach $\alpha$.751. This study classified them into 3 groups: at high risk for breast-feeding failure, at risk for breast-feeding problems, and at low risk for breast-feeding failure by the mother-infant breast-feeding assessment tool on the day of discharge from the hospital after delivering individual breast-feeding education to the subjects. This study investigated the breast-feeding rate and the breast-feeding method through mail questionnaire at the four week after childbirth, and through the phone counselling and the home visit for follow up care at the first week and the second week after childbirth. The sixth week after childbirth, this study investigated the breast-feeding rate by phone. The data analyzed the hypothesizes by $x^2$-test, paired t-test, ANOVA, Wilcoxon signed rank test, Wilcoxon rank sum test and trend analysis using SPSS/PC+ WIN 10.0 program. The results were as follows : 1) Hypothesis 1-1, "there won't be any difference the breast-feeding rate of a group at risk for breast-feeding failure by the time elapsed" was supported through constant the breast-feeding rate, because changes in the breast-feeding rate by the time elapsed after childbirth wasn't statistically significant(t= -1.501, p=.270). Hypothesis 1-2, "there won't be any difference the breast-feeding rate of group at low risk for breast-feeding failure by the time elapsed" was supported through constant the breast-feeding rate, because changes in the breast-feeding rate by the time elapsed after childbirth wasn't statistically significant(t=-1.732, p=.225). 2) Hypothesis 2-1, "there won't be any difference between the breast-feeding method of group at risk for breast-feeding failure for four weeks after childbirth and just after childbirth” was rejected, because the mean point of post test appeared to be higher than that of pre test(t=-7.267, p=.000). Hypothesis 2-2, "there won't be any difference between the breast-feeding method of the group at low risk for breast-feeding failure for four weeks after childbirth and just after childbirth" was rejected, because the mean point of post test appeared to be higher than that of pre test(t=-2.501, p=.012). 3)The 3rd hypothesis, "there won't be any difference between breast-feeding method of groups at risk for breast-feeding problems and at low risk for breast-feeding failure at the 4th week after childbirth and just after childbirth" didn't show any difference between the breast-feeding method of groups at risk for breast-feeding problems and at low risk for breast-feeding failure in the advance test(t=-1.521, p=.130) but there was difference between them in post test (t=-2.012, p=.044). As a result, the 3rd hypothesis was supported by pre test, but it was rejected by post test. In conclusion, this study confirmed breast- feeding education and follow up care just after childbirth were effective for the breast-feeding rate and method. Accordingly, it is proposed that successful nursing intervention of breast-feeding to be necessary by continuously providing follow up care through the mother-infant breast-feeding assessment tool as well as to execute individual breast-feeding education to mothers just after childbirth.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.42-49
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• 2009

This study proposes a web-based remote monitoring system for evaluating degradation of machine tools using ART2(Adaptive Resonance Theory 2) neural network. A number of studies on the monitoring of machine tools using neural networks have been reported. However, when normal condition is changed due to factors such as maintenance, tool change etc., or a new failure signal is generated, such algorithms need to be entirely retrained in order to accommodate the new signals. To cope with such problems, this study develops a remote monitoring system using ART2 in which new signals when required are simply added to the classes previously trained. This system can monitor degradation as well as failure of machine tools. To show the effectiveness of the proposed approach, the system is experimentally applied to monitoring a simulator similar to the main spindle of a machine tool, and the results show that the proposed system can be extended to monitoring of real industrial machine tools and equipment.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.48-55
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• 1997

A useful method to detect tool breakage suing neural network of cutting force signal is porposed and implemented in a basic cutting process. Cutting signal is gathered by tool dynamometer and normalized as a preprocessing. The cutting force signal level is continually monitored and compared with the predefined level. The neural network has been trained normalized sample data of the normal operation and cata-strophic tool failure using backpropagation learning process. The develop[ed system is verified to be very effective in real-time usage with minor modification in conventional cutting processes.

• Structural Engineering and Mechanics
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• v.16 no.1
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• pp.47-62
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• 2003

The nonlinear dependence aspect of various conical tool indentation parameters leading to an optimum tool semi angle value for easiest perforation is plotted and discussed explicitly in this work with the conclusion that tool angle has an optimum response towards most of the indentation parameters. Around this optimum angle, the aluminium sheets showed minimum fracture toughness as well as minimum work input to overcome the offered resistance. At the end, the mechanism leading to this phenomenon is presented with the conclusion that plastic flow dominates as the dimple semi cone angle reaches 35 and both pre and post plastic flow perforations lead the tool semi cone angle value towards this dimple cone semi angle of plastic flow initiation for its optimum performance. It is also concluded that specimen material failure is solely under tensile hoop stress and hence results into radial cracks initiation and propagation.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.9
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• pp.31-37
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• 1996

This Paper is concerned with effective signal identification method for tool breakage and micro chipping using discrete wavelet transform of feed motor current in milling operations. The wavelet transform uses an analyzing waveletfunction which is localized in both frequency and time domain to detect subtle time localized changes in input signals. The changing pattern of wavelet coefficient is continuously compared to detect tool breakage and micro chipping over one spindle revolution. The results indicate that the wavelet transform can identify tool failure with much greater sensi- tivity than the time domain monitoring and frequency domain monitoring such as FFT. Experimental results are presented to support the proposed scheme.

• Journal of the Korean Society for Precision Engineering
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• v.6 no.4
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• pp.71-83
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• 1989

The optimization in the machining process has been a long-standing goal of the manufacturing community. The optimization is composed of two main subjects;one is to select an optimum cutting condition, and the other is to detect the emergency situation and take necessary actions in real-time base. This paper proposes a reliable and practical guide system whose purpose is the optimization of cutting conditions, and the detection of tool failure in the machining process. The optimal cutting conditions are determined through the estimation of tool wear rate and the establishment of access- ible field from the measured cutting temperature and force. Tool breakage is detected by the normal force component acting on minor flank face extracted from on-line sensed feed force and radial force. In experiments, the proposed guide system has proved availability for the decision of reliable cutting conditions for the given tool-work system and the detection of tool breakage in ordinary cutting environments.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1069-1074
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• 2008

Tool condition monitoring (TCM) is crucial for improvement of productivity in manufacturing process. However, TCM techniques have not been applied to monitor tool failure in an industrial gear shaving application. Therefore, this work studied a statistical TCM method for monitoring gear shaving tool condition. The method modeled the shaving process using beta probability distribution in order to extract the effective features. Modeling includes rectifying for converting a bi-modal distribution into a unimodal distribution, estimating parameters of beta probability distribution based on method of moments. The usefulness of features obtained from the proposed method was evaluated and discussed.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2003.04a
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• pp.139-142
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• 2003

As composite materials are gaining wide acceptance in aircraft structure, repair of damaged composite is becoming an important issue. The issues in composite repair include high cost, material interchangeability, water ingression, and structural integrity. To address these problems, researchers have studied on the composite repair in various aspects. In this paper, an Internet-based advisory service (called Repair Advisory Service, RAS) for composite repair is proposed to increase efficiency for repair process. In the RAS system the web browser is used as its user interface, which provides easy access to the service. The RAS server provides web-based tools for failure prediction, Structural Repair Manual (SRM), automated prepreg cutting process, material properties, inventory and knowledge base. The computer codes implemented for repair design estimate the tensile failure and shear failure of repaired structures. The prediction of failure is based on the maximum strain criterion for tensile failure while elastic-perfect plastic shear failure model is applied for interfacial failure. The OEM's SRM is provided in the PDF format for viewing and searching by web browsers instead of looking up paper version SRM. The knowledge base in this site offers a room to share and distribute ideas, memos, publications, or suggestions from the repair engineers. The fabrication tool of RAS reads repair geometry from engineers then generates a CNC toolpath to cut prepreg patches. The RAS service is open to public and available at http://nano.gsnu.ac.kr/. Broad feedback from field technicians and engineers is welcome to improve the usefulness of RAS.

• Advanced Composite Materials
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• v.18 no.3
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• pp.233-249
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• 2009

Safe installation and operation of high-pressure composite cylinders for hydrogen storage are of primary concern. It is unavoidable for the cylinders to experience temperature variation and significant thermal input during service. The maximum failure pressure that the cylinder can sustain is affected due to the dependence of composite material properties on temperature and complexity of cylinder design. Most of the analysis reported for high-pressure composite cylinders is based on simplifying assumptions and does not account for complexities like thermo-mechanical behavior and temperature dependent material properties. In the present work, a comprehensive finite element simulation tool for the design of hydrogen storage cylinder system is developed. The structural response of the cylinder is analyzed using laminated shell theory accounting for transverse shear deformation and geometric nonlinearity. A composite failure model is used to evaluate the failure pressure under various thermo-mechanical loadings. A back-propagation neural network (NNk) model is developed to predict the maximum failure pressure using the analysis results. The failure pressures predicted from NNk model are compared with those from test cases. The developed NNk model is capable of predicting the failure pressure for any given loading condition.