• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.317-322
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• 2004

This paper deals with a prediction method of tool life in view of the reliability assessment. In this study, the flank wear was studied among multi-factors deciding the tool wear state. Firstly, tool lift was predicted by correlation between flank wear and cutting time, based on the extended Taylor tool life equation of turning data, including parameters of cutting speed, feed rate, and cutting depth. Secondly, each of cutting conditions of endmilling was equivalently converted to apply ball endmill data to the extended Taylor equation. The web-based reliability prediction program for tool lift is being developed as one of reliability assessment programs to for the machine tools.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.5
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• pp.675-682
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• 2013

Reliability analysis and prediction of next failure time is critical to sustain weapon systems, concerning scheduled maintenance, spare parts replacement and maintenance interventions, etc. Since 1981, many methodology derived from various probabilistic and statistical theories has been suggested to do that activity. Nowadays, many A.I. tools have been used to support these predictions. Support Vector Regression(SVR) is a nonlinear regression technique extended from support vector machine. SVR can fit data flexibly and it has a wide variety of applications. This paper utilizes SVM and SVR with combining time series to predict the next failure time based on historical failure data. A numerical case using failure data from the military equipment is presented to demonstrate the performance of the proposed approach. Finally, the proposed approach is proved meaningful to predict next failure point and to estimate instantaneous failure rate and MTBF.

• Computers and Concrete
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• v.12 no.6
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• pp.775-783
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• 2013

A novel reliability-based work model of k/n (G) system has been developed. Unit failure probability is given based on the load and strength distributions and according to the stress-strength interference theory. Then a dynamic reliability prediction model of repairable k/n (G) system is established using probabilistic differential equations. The resulting differential equations are solved and the value of k can be determined precisely. The number of work unit k in repairable k/n (G) system is obtained precisely. The reliability of whole life cycle of repairable k/n (G) system can be predicted and guaranteed in the design period. Finally, it is illustrated that the proposed model is feasible and gives reasonable prediction.

• Journal of Industrial Technology
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• v.28 no.B
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• pp.215-226
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• 2008

MIL-HDBK-217 has widely been used for electronics reliability predictions. Recently, the $217Plus^{TM}$ has been developed by DoD RIAC and may replace MIL-HDBK-217. A overview of the $217Plus^{TM}$ has been performed in this paper. We first reviewed the overall concepts and reliability prediction procedures. We then explained the component models and the system level model with process grading concepts. Bayesian approach incorporating field data into the predicted failure rate is another feature of this methodology.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1419-1425
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• 2000

When we predict of software reliability, we can't know the testing stopping time and how many faults be residues in software the (the maximum value of data) during these software testing process, therefore we assume the maximum value and the training result can be inaccuracy. In this paper, we present neural network approach for software reliability prediction with unnormalized (actual or original collected) data. This approach is not consider the maximum value of data and possible use the network without normalizing but the predictive accuracy is better. Also, the unnormalized method shows better predictive accuracy than the normalized method given by maximum value. Therefore, we can make the best use of this model in software reliability prediction using unnormalized data.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1105-1108
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• 2004

As recently optical communication industry is developed, request of optical communication part is increased. Ferrule is very important part which determines transmission efficiency and quality of information in the optical communication part. Most of ferrule processes are grinding which request high processing precision. The ultra precision centerless grinding machine for ferrule grinding was designed. The centerless grinding machine is composed of the high damping bed, grinding wheel spindle unit, regulating wheel spindle unit, feeding table and dressing unit. Reliability prediction was very important for the high quality design. In this study, centerless grinding machine was predicted reliability.

• Journal of Power Electronics
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• v.6 no.2
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• pp.104-113
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• 2006

Satellites have provided the impetus for the orderly development of reliability engineering research and analysis because they tend to have complex systems and hence acute problems. They were instrumental in developing mathematical models for reliability, as well as design techniques to permit quantitative specification, prediction and measurement of reliability. Reliability engineering is based on implementing measures which insure an item will perform its mission successfully. The discipline of reliability engineering consists of two fundamental aspects; $(1^{st})$ paying attention to details, and $(2^{nd})$ handling uncertainties. This paper uses some of the basic concepts, formulas and examples of reliability theory in application. This paper emphasizes the practical reliability analysis of a Low Earth Orbit (LEO) Micro-satellite power subsystem. Approaches for specifying and allocating the reliability of each element of the power system so as to meet the overall power system reliability requirements, as well as to give detailed modeling and predicting of equipment/system reliability are introduced. The results are handled and analyzed to form the final reliability results for the satellite power system. The results show that the Electric Power Subsystem (EPS) reliability meets the requirements with quad microcontrollers (MC), two boards working as main and cold redundant while each board contains two MCs in a hot redundant.

• IE interfaces
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• v.21 no.1
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• pp.109-119
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• 2008

Reliability of embedded softwares, as one of factors which affect system reliability, is the probability of failure-free software operation for a specified period of time in a specified environment. and Embedded software is different from general package software because hardware and operating system are tightly coupled to each other. Reliability evaluation models for embedded softwares currently used do not separate estimation and prediction models clearly, and even a standard model has not been proposed yet. In this respect, we choose a reliability estimation model suitable for embedded softwares among software evaluation models being used, and modified the model so as to accomodate recent software environments. In addtion, based on the model, the web-based reliability prediction tool RPX is developed. Finally, an embedded software is analyzed using the tool.

• Journal of Applied Reliability
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• v.15 no.1
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• pp.44-51
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• 2015

In this study, we propose reliability prediction of a satellite by function analysis. To do so, the intended functions of the satellite are derived from using function structure block diagram, and defined as main, sub, and detailed functions. Furthermore, in order to generate function and reliability structure table, reliability model rule, duty cycle, and types of switch are assigned to the classified functions. This study also establishes reliability block diagram and mathematical reliability models to schematize the relationship among the functions. The reliability of the classified function is estimated by calculating the failure rate of parts comprising them. Finally, we apply the proposed method to a small satellite as a case study. The result shows that the reliability for the detailed function and the sub function as well as the main function could be predicted quantitatively and accurately by the proposed approach.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.10a
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• pp.485-486
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• 2006