• Maxillofacial Plastic and Reconstructive Surgery
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• v.41
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• pp.27.1-27.9
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• 2019

Background: Implants are becoming the first choice of rehabilitation for tooth loss. Even though they have a high success rate, failures still occur for many reasons. The objective of this study is to analyze the reasons for recurring failure at the same site and the results of re-implantation. Methods: Thirteen patients (11 males and 2 females, mean age 60 ± 9.9 years) who experienced implant surgery failure at the same site (same tooth extraction area) two or more times in the Department of Oral and Maxillofacial Surgery, Seoul National University Bundang Hospital, between 2004 and 2017 were selected. The medical records on a type, sites, diameter, and length of implants; time and estimated cause of failure; and radiographs were reviewed. Data were collected and analyzed retrospectively, and the current statuses were evaluated. Results: A total of 14 implants experienced failure in the same site more than two times. Twelve implants were placed in the maxilla, while 2 implants were placed in the mandible. The maxillary molar area was the most common site of failure (57.1%), followed by the mandibular molar, anterior maxilla, and premolar areas (14.3% each). The first failure occurred most commonly after prosthetic treatment (35.7%) with an average period of failure of 3.8 months after loading. Ten cases were treated as immediate re-implantation, while the other 4 were delayed reimplantation after an average of 3.9 months. The second failure occurred most commonly after prosthetic treatment (42.9%), with an average of 31 months after loading; during the healing period (42.9%); and during the ongoing prosthetic period (14.3%). In 3 cases (21.4%), the treatment plan was altered to an implant bridge, while the other 11 cases underwent another implant placement procedure (78.6%). Finally, a total of 9 implants (64.3%) survived, with an average functioning period of 60 months. Conclusions: Implants can fail repeatedly at the same site due to overloading, infection, and other unspecified reasons. The age and sex of the patient and the location of implant placement seem to be associated with recurring failure. Type of implant, bone augmentation, and bone materials used are less relevant.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.9
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• pp.1325-1330
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• 2010

The breakdown of any critical component of a turbine results in the outage of power plants. Unexpected failure decreases equipment utilization and causes enormous economic losses. Currently, we conduct conservative preventive maintenance for a maintenance period that is proposed by a vendor. In the rapidly changing business environment, reliability-based maintenance is required in order to remain competitive and reduce maintenance costs while maintaining the reliability of equipment. In order to determine an appropriate maintenance period for guaranteeing reliability, we must determine the failure probability by carefully analyzing the failure history of the equipment. In this study, we created a database of failure history for power-plant turbines, predicted the best repair time using the Weibull function, and investigated how the appropriate maintenance cycle can be determined.

• International Journal of Reliability and Applications
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• v.18 no.1
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• pp.1-8
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• 2017

In this paper, we study an extended warranty model under minimal repair-replacement warranty (MRRW) which is suggested by Park, Jung and Park (2013). Under MRRW policy, the manufacturer is responsible for providing the minimal repair-replacement services upon the system failures during the warranty period. And if the failure occurs during the extended warranty period, only the minimal repair is conducted. Following the expiration of extended warranty, the user is solely responsible for maintaining the system for a fixed length of time period and replaces the system at the end of such a maintenance period. During the maintenance period, only the minimally repair is given for each system failure. The main purpose of this article is to suggest the extended warranty and replacement model with MRRW. Given the cost structures incurred during the life cycle of the system, we formulate the expected cost and the expected length of life cycle to obtain the expected cost rate.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.1
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• pp.31-36
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• 2010

Collecting all failures during life cycle of vehicle is not easy way because its life cycle is normally over 10 years. Warranty period can help gathering failures data because most customers try to repair its failures during warranty period even though small failures. This warranty data, which means failures during warranty period, can be a good resource to predict initial reliability and permanence reliability. However uncertainty regarding reliability prediction remains because this data is censored. University of Wuppertal and major auto supplier developed the reliability prognosis model considering censored data and this model introduce to predict reliability estimate further "failure candidate". This paper predicts reliability of telecommunications system in vehicle using the model and describes data structure for reliability prediction.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.1
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• pp.51-63
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• 1996

In this paper, we develop two replacement-type reliability acceptance sampling plans(RASPs) for the gamma lifetime distribution assuming that the shape parameter is known. The two plans are respectively based upon failure-free period and hybrid life tests. We then compare the plans in terms of expected test time to reach a decision, power, etc. Computational results indicate among others that the failure-free period RASP has a shorter expected completion time than the corresponding hybrid RASP when the true scale parameter is 'large'. Finally, sensitivity analyses reveal that the effects of the uncertainties involved in the assumed shape parameter on the producer and the consumer risks are in favorable directions for both parties for both types of plans.

• Proceedings of the Fisheries Business Administration Society of Korea Conference
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• 2007.12a
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• pp.167-184
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• 2007

The objectives of this paper are to identify the causes of the corporate distress and to develop a distress prediction model with the financial information in fishery industry. In this study, the corporate distress is defined as economic failure and technical insolvency. Economic failure occurs by reduction, shut-down, or change of the business and technical insolvency results from failure to pay the financial debt of companies. The 33 distressed firms from 1991 to 2003 were composed by 14 economic failure companies, 15 technical insolvency companies. 4 companies applied to the both cases. The analysis of distress prediction of fishery companies were accomplished according to the distress definition. The analysis was carried out as two steps. The first step was the univariate analysis, which was used for checking the prediction power of individual financial variable. The t-test is used to identify the differences in financial variables between the distressed group and the non-distressed group. The second step was to develop distress prediction model with logistic regression. The variables showed the significant difference in univariate analysis were selected as the prediction variables. The financial ratios, used in the logistic regression model, were selected by backward elimination method. To test stability of the distress prediction model, the whole sample was divided as three sub-samples, period 1(1990$\sim$1993), period 2(1994$\sim$1997), period 3(1998$\sim$2002). The final model built from whole sample appled each three sub-samples. The results of the logistic analysis were as follows. the growth, profitability, stability ratios showed the significant effect on the distress. the some different result was found in the sub-sample (economic failure and technical insolvency). The growth and the profitability were important to predict the economic failure. The profitability and the activity were important to predict technical insolvency. It means that profitability is the really important factor to the fishery companies.

• The Journal of Fisheries Business Administration
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• v.39 no.2
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• pp.61-79
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• 2008

The objectives of this paper are to identify the causes of the corporate distress and to develop a distress prediction model with the financial information in fishery industry. In this study, the corporate distress is defined as economic failure and technical insolvency. Economic failure occurs by reduction, shut - down, or change of the business and technical insolvency results from failure to pay the financial debt of companies. The 33 distressed firms from 1991 to 2003 were composed by 14 economic failure companies, 15 technical insolvency companies. 4 companies applied to the both cases. The analysis of distress prediction of fishery companies were accomplished according to the distress definition. The analysis was carried out as two steps. The first step was the univariate analysis, which was used for checking the prediction power of individual financial variable. The t - test is used to identify the differences in financial variables between the distressed group and the non - distressed group. The second step was to develop distress prediction model with logistic regression. The variables showed the significant difference in univariate analysis were selected as the prediction variables. The financial ratios, used in the logistic regression model, were selected by backward elimination method. To test stability of the distress prediction model, the whole sample was divided as three sub-samples, period 1(1990 - 1993), period 2(1994 - 1997), period 3(1998 - 2002). The final model built from whole sample appled each three sub - samples. The results of the logistic analysis were as follows. the growth, profitability, stability ratios showed the significant effect on the distress. the some different result was found in the sub - sample (economic failure and technical insolvency). The growth and the profitability were important to predict the economic failure. The profitability and the activity were important to predict technical insolvency. It means that profitability is the really important factor to the fishery companies.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.12-19
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• 2003

This paper presents the effect of boundary conditions in various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the aid of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.263-271
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• 1997

This paper presents a preventive maintenance model for determining the preventive replacement period of a system in which a failure rate is affected by the cumulative damage of fault and inspection. Especially, the failure rate function is considered to be a function of the cumulative damage of the fault and inspection time. Types of replacement considered are preventive replacement and failure replacement. Failure rate and expected cost function between replacement are derived. An optimal policy is obtained that minimizes the average cost per unit time for preventive replacement, failure replacement, inspection and repair.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1177-1183
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• 2013

In this paper, the analysis of inspection period bases on reliability is suggested in the field of traction power system. Even though there are several maintenance models, the most commonly used maintenance assessment has been focused on time based maintenance in real traction power systems. The maintenance intervals are selected on the basis of long-time experience. It ensures high availability and exact planning of staff. Reliability centered maintenance, which evaluates criticality and severity of each failure mode, achieves the operation, maintenance, and cost-effective improvement that will manage the risks of equipment. This paper deals with electrification in railway inspection frequency and applied reliability based inspection frequency instead of constant intervals. The distribution function of failure rate in traction power system belongs to Weibull function. Also, the fault data and the number of installed equipments for electrifications are collected. The failure history is investigated and classified in detail. Though these complicated procedures, it contribute to extend equipment lifetime and to reduce maintenance costs.