• IE interfaces
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• v.16 no.1
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• pp.27-33
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• 2003

The maintenance cost in K Steelworks has been continuously increased in proportion to the production cost. However, there seems to be a possibility of reducing cost through the optimization of maintenance actions. The failure types of the equipment in steelworks ate various with different failure cost. Thus the failure rate and cost of each type of failures should be considered simultaneously when the optimum maintenance period is to be determined. It is considered that the equipment undergoes periodic replacement and a specified number of incomplete preventive maintenance actions are performed during a replacement period. Assuming that the time to failure follows a Weibull distribution, the parameters of the failure rate are estimated using the maximum likelihood estimation. The optimal replacement period is determined to minimize the average cost per unit time. As the result of analysis it is suggested that the existing maintenance period for a hot-rolling equipment can be extended significantly.

• Journal of the Korean Society of Safety
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• v.26 no.6
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• pp.104-110
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• 2011

In FMEA, the risk priority number(RPN) is used for risk evaluation on each failure mode. It is obtained by multiplying three components, i.e., severity, occurrence, and detectability of the corresponding failure mode. Each of the three components are usually determined on the basis of the past experience and technical knowledge. But this approach is not strictly objective in evaluating risk of a given failure mode and thus provide somewhat less scientific measure of risk. Assuming a homogeneous Poisson process for occurrence of the failures and causes, we propose a more scientific approach to evaluation of risk in FMEA. To quantify severity of each failure mode, the mission period is taken into consideration for the system. If the system faces no failure during its mission period, there are no losses. If any failure occurs during its mission period, the losses corresponding to the failure mode incurs. A longer remaining mission period is assumed to incur a larger loss. Detectability of each failure mode is then incorporated into the model assuming an exponential probability law for detection time of each failure cause. Based on the proposed model, an illustrative example and numerical analyses are provided.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.301-307
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• 1998

This paper proposes free warranty interval for repairable items when the failure types of item are considered. Failure types are classified into major failure and minor failure. If major failure occurs during warranty period, the item is replaced and if minor failure occurs during warranty period, the item is minimally repaired. This paper determines the optimum free warranty interval which minimizes total expected cost of the free warranty cost model. Numerical example is shown in which failure time of item has weibull distribution.

• Journal of the Korea Safety Management & Science
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• v.3 no.4
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• pp.65-76
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• 2001

Field data have been recorded as the time to failure or the number of failure of systems. We consider the time to failure and covariate variables in some pre-specified follow-up or warranty period. This paper aims to investigate study on the reliability estimation when some additional field data can be collected within-warranty period or after-warranty period. A various likelihood-based methods are outlined and examined for exponential or Weibull distribution.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.4
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• pp.507-517
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• 1995

The failure rate of an item depends on operational environment. When an item has a chance failure period and a wearout failure period in sequel, the severity of operational environment causes the increase in the slop of wearout failure rate or the increase in the magnitude of chance failure rate. For such a change of operational environment, this paper concerns the change of optimal preventive replacement time. Two preventive replacement policies, age replacement policy and periodic replacement policy with minimal repair, are considered. Investigated properties are: (a) in age replacement policy, optimal preventive replacement time increases as the chance failure rate increases and optimal preventive replacement time decreases as the slope of wearout failure rate increases, and (b) in periodic replacement policy with minimal repair, optimal preventive replacement time increases as the slope of wearout failure rate increases; however, the change of chance failure rate does not alter the optimal preventive replacement time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.28-35
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• 2019

Since guided missiles with the characteristics of the one-shot system remain stored throughout their entire life cycle, it is important to maintain their storage reliability until the launch. As part of maintaining storage reliability, period of preventive test is set up to perform preventive periodic test, in this case failure detection rate has a great effect on setting up period of preventive test to maintain storage reliability. The proposed method utilizes failure rate predicted by the software on the basis of MIL-HDBK-217F and failure mode analyzed through FMEA (Failure Mode and Effect Analysis) using data generated from the actual field. The failure detection rate of using the proposed method is applied to set periodic test of the actual guided missile. The proposed method in this paper has advantages in accuracy and objectivity because it utilizes a large amount of data generated in the actual field.

• Journal of Korean Society for Quality Management
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• v.19 no.2
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• pp.117-124
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• 1991

In this paper, it is assumed that a system is composed of an essential unit and a nonessential unit. During the running of the system, an essential unit is replaced at periodic replacement time T or at nth failure of essential unit whichever occurs first. Nonessential unit is replaced at its failure and at the replacement of essential unit. This paper derive optimal replacement period which minmises the total expected cost for replacement. The unimodality of totoal maintenance cost function is proved under the assumption that hazard rate of each component is continuous and monotone increasing failure rate(IFR). Based on this condition, it is shown that the optimal replacement period is finite and unique.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.2
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• pp.81-90
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• 1988

This paper is concerned with warranty cost models for a product with two types of failure ; type 1 failures corrected by minimal repair and type 2 failures removed only by replacement. Two warranty policies involving an initial free service period followed by a pro-rata period are considered ; the difference is whether the warranty is renewed or not when type 2 failure occures during its free service period. Expected warranty costs under the two policies are obtained, and their behaviors are examined for the case where type 1 and 2 failure distributions are Weibull and exponential, respectively.

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.115-120
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• 2005

This paper introduces models for preventive maintenance policies and considers periodic preventive maintenance policy with minimal repair when the failure of system occurs. It is assumed that minimal repairs do not change the failure rate of the system. The failure rate under prevention maintenance received an effect by a previously prevention maintenance and the slope of failure rate increases the model where it considered. Also the start point of failure rate under prevention maintenance considers the degradation of system and that it increases quotient, it assumed. Per unit time it bought an expectation cost from under this prevention maintenance policy. We obtain the optimal period time and the number for the periodic preventive maintenance by using Nakagawa's Algorithm, which minimizes the expected cost rate per unit time. Finally, it suppose that the failure time of a system has a Weibull distribution as an example and we obtain an expected cost rate per unit time the optimal period time and the number when cost of replacement and cost of minimal repair change.

• 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.