• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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• pp.71-79
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• 2012

In this paper, an evaluation of a product replacement ratio of irreparable items to the normally working ones is performed with a view to a warranty analysis. It is demonstrated that the replacement ratio during the warranty period can be estimated from the field data collected during the period of operation, and one can provide the management with a useful information regarding the appropriateness for the warranty period, which is vital to the product marketing strategy. Although warranty data usually take the form of multiply right censored interval data, the conventional reliability analysis method seems to be good enough as in this case. More sophisticated method such as warranty cost analysis and 2-dimensional warranty analysis is yet desired.

• Journal of Korean Society for Quality Management
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• v.42 no.1
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• pp.1-14
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• 2014

Purpose: In this paper, the minimal repair-replacement warranty policy is used to carry out a warranty cost analysis with warranty servicing times and failure times that are statistically correlated to bivariate distributions. Methods: Based on the developed approach by Park and Pham (2012a), we investigate the property of the Freund's bivariate exponential distribution and obtain the number of warranty services using the field data to conduct the warranty cost analysis. Results: Maximum likelihood estimates are presented to estimate the parameters and the warranty model is investigated using a Freund's bivariate exponential distribution. A numerical example is discussed to deal with the applicability of the developed approach in the paper. Conclusion: A novel approach of analyzing the warranty cost is proposed for a product in which failure times and warranty servicing times are used simultaneously to investigate the eligibility of a warranty claim.

• Journal of Applied Reliability
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• v.8 no.1
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• pp.1-13
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• 2008

A methodology for collection and analysis of automotive field reliability data is presented. Automotive warranty system usually covers a pre-determined period of time and/or mileage accumulation. Therefore mileage information for the vehicles that have not experienced any failure or problems during the warranty period is not available. In this paper, a reliability analysis method using the estimated mileage distribution from an additional survey for vehicles that have not any record during the warranty period is proposed. Methods of reliability analysis using the warranty information collected under the EU and US warranty policies are also provided.

• Proceedings of the Safety Management and Science Conference
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• 2012.04a
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• pp.525-534
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• 2012

The issue is all about the study of warranty data collection and the analysis method to get a reasonable information of the products and improve reliability. In this paper, we consider the classification of warranty data analyses into a parametric and non-parametric analysis and method to get a reasonable information of the products. Also, it is considered the research trend by grouping the relationship among the studies. This study would be used to find the effective application and the condition of warranty data analysis.

• Journal of the Korea Safety Management & Science
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• v.17 no.2
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• pp.241-247
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• 2015

The purpose of the warranty data analysis can be classified into two categories. Two goals is a failure cause analysis and life prediction analysis. In this paper first, we applied multivariate analysis method that can be estimated in consideration of various factors on the failure cause warranty data. In particular, we apply the Tree model and Cox model. The advantage of the Tree is easy to interpret this result as compared to other models. In addition Cox model can quantitatively express the risk. Second, this paper proposed a multivariate life prediction model (AFT) considering a variety of factors. By applying the actual warranty data confirmed the usability.

• Communications for Statistical Applications and Methods
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• v.18 no.3
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• pp.277-286
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• 2011

Global companies can sell their products with dierent warranty periods based on location and times. Customers can select the length of warranty on their own if they pay an additional fee. In this paper, we consider the warranty period and the repair time limit as random variables. A two-dimensional warranty policy is considered with repair times and failure times. The repair times are considered within the repair time limit and the failure times are considered within the warranty period. Under the non-renewable warranty policy, we obtain the expected number of warranty services and their variances in the censored area by warranty period and repair time limit to conduct a warranty cost analysis. Numerical examples are discussed to demonstrate the applicability of the methodologies and results using field data based on the proposed approach in the paper.

• Journal of Applied Reliability
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• v.11 no.1
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• pp.43-57
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• 2011

In the paper, we consider two-dimensional warranty policy with failure times and repair times. The failure times are considered within the warranty period and the repair times are considered within the repair time limit. Under the renewable warranty policy and non-renewable warranty policy, we consider the number of warranty services in the censored area by warranty period and repair time limit to conduct warranty cost analysis. We investigate the field data to check their dependency and implement our proposed approaches to conduct warranty cost analysis using the parametric methods. Numerical examples are discussed to demonstrate the applicability of the methodologies and results based on the proposed approach in the paper.

• IE interfaces
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• v.23 no.2
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• pp.176-181
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• 2010

Warranty claim data analysis is a useful tool for the manufacturer because it contains many useful informations regarding reliability of the product in the real-world environments. Because of the nature of uncertainty and the incompleteness of data, some bias patterns are observed on warranty claim rate known as 'spikes'. Two types of spikes are considered. One is due to manufacturing-related failures. The other is caused by customer's behavior. This paper proposes a model by considering two types of spikes. Warranty claim data is analyzed with the proposed model. To represent spikes observed on the early warranty period, we classify failures into manufacturing-related failures and usage-related failures. Uniform distribution is assumed for the time delayed to diagnose and report by customers. By reducing maximum value of the delayed time by customers, the proposed model characterizes customer's rush in the vicinity of the warranty expiration limit. Experimental results by using the real warranty claim data show that the proposed model is better than the existing one in respect to MSE(Mean Squared Error). Moreover it is expected to estimate the failure rate more realistically with proposed model because it considers the delayed time to diagnose and report by customers.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2017.05a
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• pp.266-267
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• 2017

As apartment buildings defect lawsuits become socioeconomic problems, an objective basis system for the term of warranty liability of reinforced concrete constructions is urgent. This study was carried out as a basic study for developing a basis system for the term of warranty liability. To do this, defect data actual collected in apartment complexes were collected and analyzed. As the result of checking the cumulative rate of defect occurrence in reinforced concrete construction by year, the point of time of reaching the 90% level was the 5th years, which was similar with the provision of the Apartment Building Management Act. However, the current Supreme Court precedent has decided that the term of warranty liability for the main structural parts in reinforced concrete construction shall be 10 years and the dispute is expected to continue in the future in the defect lawsuit.

• Proceedings of the Korean Reliability Society Conference
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• 2000.11a
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• pp.299-311
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• 2000

This paper is concerned with the method of estimating lifetime distribution for field data in warranty period and for a situation where some additional field data can be gathered after the warranty period. Implementing the proposed methods in this paper will result in obtaining the more precise product life time estimation and product improvement.